We introduce Gaussian Garments, a novel approach for reconstructing realistic simulation-ready garment assets from multi-view videos. Our method represents garments with a combination of a 3D mesh and a Gaussian texture that encodes both the color and high-frequency surface details. This representation enables accurate registration of garment geometries to multi-view videos and helps disentangle albedo textures from lighting effects. Furthermore, we demonstrate how a pretrained graph neural network (GNN) can be fine-tuned to replicate the real behavior of each garment. The reconstructed Gaussian Garments can be automatically combined into multi-garment outfits and animated with the fine-tuned GNN.

With the development of 5G-Advanced, traditional industries are gradually transforming towards intelligentization. However, the uncertainty of wireless communication has an impact on the stability of industrial wireless network control system (IWNCS). Therefore, this paper mainly studies the stability optimization problem of IWNCS in ultra-reliable and low-latency communications (URLLC). We quantify system stability through real-time instability probability, which accounts for control-communication dependencies, and propose an interference-aware greedy clustering and deep reinforcement learning (IAGC-DRL) optimization algorithm to enhance control stability. Specifically, in large-scale networks, we propose a Proximal Policy Optimization (PPO) combined with greedy search to dynamically allocate uplink resource blocks (RBs) and power resources for each sampling period. This approach enables real-time adjustment of transmission performance across diverse industrial equipment, thereby optimizing the system’s instability probability. Simulation results show that the proposed algorithm outperforms other algorithms in improving the stability. And the real-time instability probability demonstrates superior performance in enhancing IWNCS stability when used as the optimization objective.

Benefiting from wide coverage and low expense, satellite constellations show potential in numerous applications. As satellite constellations expand with more diverse and smarter payloads, traditional networking methods become increasingly rigid. This rigidity hinders the flexible and efficient use of on-board resources in mega-constellations, and limits the ability of satellite networks to provide customized services. Hence, a taskoriented clustering (TOC) method based on Markov process is proposed for multi-layer mega-constellations, enabling flexible networking of satellites with different payloads according to task requirements. Finally, numerical simulation results demonstrate that the TOC method outperforms existing works.

Uplink grant-free (GF) transmission with K-repetition can facilitate hyper-reliable and low-latency communication (HRLLC) among industrial internet of things (IIoT) devices by saving the time of requesting/waiting for the scheduling grant. Reliability analysis based on packet loss rate (PLR) establishes essential theoretical foundations for system evaluation. However, assessing the PLR in GF uplink IIoT networks for multiple HRLLC services in dynamic interference environments remains a critical challenge. This paper proposes a unified framework for evaluating the PLR, which first employs an interference-aware optimal clustering algorithm to systematically identify all possible interference patterns affecting a terminal. For each identified interference pattern, the PLR is analyzed independently. Therefore, a comprehensive PLR of each service is obtained by combining these individual PLR values through probability-weighted summation. It differs from most studies that rely on interference-averaging methods. The numerical results indicate that the proposed evaluation method enhances PLR accuracy by 10 dB compared to the benchmark.

Millimeter wave (mmWave) has emerged as a key technology for next-generation communications to address spectrum scarcity in traditional low-frequency wireless systems. However, its dynamic channel, high propagation losses and blocking susceptibility impose higher demands on resource allocation in complex interference environments, especially in factory scenarios. Efficient resource allocation in mmWave systems relies on accurately identifying and modeling interference, but current prevalent research remains constrained by idealized channel state information (CSI) assumptions and statistical modeling approaches that focus on stable CSI and consistent interference and noise. These conventional methods are inadequate for transient systems with instantaneous channel variations. To overcome these challenges, this paper proposes an interference identification model based on directional beams, which integrates the cluster scattering characteristics of mmWave signals and formulates the received power as the sum of the directional beam gain-weighted multipath powers. Using intelligent algorithms, we train this model to precisely identify interference and match arbitrary input resource relationships to achieve accurate signal-to-interference-plus-noise ratio (SINR) prediction for supporting the subsequent resource allocation. Numerical results demonstrate that the proposed algorithm improves the prediction accuracy by 4.7% − 35.1% compared to the benchmark scheme.

Edge computing (EC), positioned near end devices, holds significant potential for delivering low-latency, energy-efficient, and secure services. This makes it a crucial component of the Internet of Things (IoT). However, the increasing number of IoT devices and emerging services place tremendous pressure on edge servers (ESs). To better handle dynamically arriving heterogeneous tasks, ESs and IoT devices with idle resources can collaborate in processing tasks. Considering the selfishness and heterogeneity of IoT devices and ESs, we propose an incentive-driven multilevel task allocation framework. Specifically, we categorize IoT devices into task IoT devices (TDs), which generate tasks, and auxiliary IoT devices (ADs), which have idle resources. We use a bargaining game to determine the initial offloading decision and the payment fee for each TD, as well as a double auction to incentivize ADs to participate in task processing. Additionally, we develop a priority-based intercell task scheduling algorithm to address the uneven distribution of user tasks across different cells. Finally, we theoretically analyze the performance of the proposed framework. Simulation results demonstrate that our proposed framework outperforms benchmark methods.

With the rapid growth of global traffic and the construction of large-scale low-orbit satellites, the hybrid network of multitier LEO satellite has become the future trend, which also brings challenges to satellite routing. In this article, we propose a flexible satellite cross-tier routing method under the control of gateway, considering on-board processing ability and satellite congestion to realize low lantency routing. First, we model the multitier satellite constellations as marked Poission point process (MPPP), in which each tier follows Poission point process (PPP) distribution with marked different satellite queueing length. Then, the analytical expressions of routing outage probability, end-to-end delay are derived, considering search radius, packet arrival rate, routing distance and intertier distance. Finally, the search range expansion approach is proposed to solve the problem of traffic congestion, and the tradeoff between routing success probability and search range deflection angle is obtained. Numerical results show that the cross-tier routing mechanism can significantly reduce the routing outage probability under high load and reduce the end-to-end delay under medium load, respectively. In addition, the search range expansion approach can significantly reduce the routing outage probability without influencing the sum delay significantly. This work is expected to be instructive to the future sixth generation (6G) network.

Mobile edge computing mitigates the shortcomings of cloud computing caused by unpredictable wide-area network latency and serves as a critical enabling technology for the Industrial Internet of Things (IIoT). Unlike cloud computing, mobile edge networks offer limited and distributed computing resources. As a result, collaborative edge computing emerges as a promising technology that enhances edge networks' service capabilities by integrating computational resources across edge nodes. This paper investigates the task scheduling problem in collaborative edge computing for IIoT, aiming to optimize task processing performance under long-term cost constraints. We propose an online task scheduling algorithm to cope with the spatiotemporal non-uniformity of user request distribution in distributed edge networks. For the spatial non-uniformity of user requests across different factories, we introduce a graph model to guide optimal task scheduling decisions. For the time-varying nature of user request distribution and long-term cost constraints, we apply Lyapunov optimization to decompose the long-term optimization problem into a series of real-time subproblems that do not require prior knowledge of future system states. Given the NP-hard nature of the subproblems, we design a heuristic-based hierarchical optimization approach incorporating enhanced discrete particle swarm and harmonic search algorithms. Finally, an imitation learning-based approach is devised to further accelerate the algorithm's operation, building upon the initial two algorithms. Comprehensive theoretical analysis and experimental evaluation demonstrate the effectiveness of the proposed schemes.

In sixth-generation (6G) networks, the dense deployment of femtocells will result in significant co-channel interference. However, current studies encounter difficulties in obtaining precise interference information, which poses a challenge in improving the performance of the resource allocation (RA) strategy. This paper proposes an intelligent scheme aimed at achieving energy-efficient RA in uplink scenarios with unknown interference. Firstly, a novel interference-inference-based RA (IIBRA) framework is proposed to support this scheme. In the framework, the interference relationship between users is precisely modeled by processing the historical operation data of the network. Based on the modeled interference relationship, accurate performance feedback to the RA algorithm is provided. Secondly, a joint double deep Q-network and optimization RA (DORA) algorithm is developed, which decomposes the joint allocation problem into two parts: resource block assignment and power allocation. The two parts continuously interact throughout the allocation process, leading to improved solutions. Thirdly, a new metric called effective energy efficiency (EEE) is provided, which is defined as the product of energy efficiency and average user satisfaction with quality of service (QoS). EEE is used to help train the neural networks, resulting in a superior level of user QoS satisfaction. Numerical results demonstrate that the DORA algorithm achieves a clear enhancement in interference efficiency, surpassing well-known existing algorithms with a maximum improvement of over 50%. Additionally, it achieves a maximum EEE improvement exceeding 25%.

The studies of human clothing for digital avatars have predominantly relied on synthetic datasets. While easy to collect, synthetic data often fall short in realism and fail to capture authentic clothing dynamics. Addressing this gap, we introduce 4D-DRESS, the first real-world 4D dataset advancing human clothing research with its high-quality 4D textured scans and garment meshes. 4D-DRESS captures 64 outfits in 520 human motion sequences, amounting to 78k textured scans. Creating a real-world clothing dataset is challenging, particularly in annotating and segmenting the extensive and complex 4D human scans. To address this, we develop a semi-automatic 4D human parsing pipeline. We efficiently combine a human-in-the-loop process with automation to accurately label 4D scans in diverse garments and body movements. Leveraging precise annotations and high-quality garment meshes, we establish several benchmarks for clothing simulation and reconstruction. 4D-DRESS offers realistic and challenging data that complements synthetic sources, paving the way for advancements in research of lifelike human clothing.

Mobile edge computing (MEC) is a promising computing paradigm that offers users proximity and instant computing services for various applications, and it has become an essential component of the Internet of Things (IoT). However, as compute-intensive services continue to emerge and the number of IoT devices explodes, MEC servers are confronted with resource limitations. In this work, we investigate a task-offloading framework for device-assisted edge computing, which allows MEC servers to assign certain tasks to auxiliary IoT devices (ADs) for processing. To facilitate efficient collaboration among task IoT devices (TDs), the MEC server, and ADs, we propose an incentive-driven pricing and task allocation scheme. Initially, the MEC server employs the Vickrey auction mechanism to recruit ADs. Subsequently, based on the Stackelberg game, we analyze the interactions between TDs and the MEC server. Finally, we establish the optimal service pricing and task allocation strategy, guided by the Stackelberg model and priority settings. Simulation results show that the proposed scheme dramatically improves the utility of the MEC server while safeguarding the interests of TDs and ADs, achieving a triple-win scenario.

The proliferation of connected devices in wireless systems result in severe intercell interference (ICI). To mitigate ICI, an accurate interference model of link-granularity is highly beneficial. The data generated by wireless devices during networks operation can contribute to mining the interference relationship if properly utilized. Existing frameworks of data-driven interference modeling require data collected from the entire network. Such data are unobtainable in a large network due to the communication constraints of a single network node. This paper proposes an uplink interference modeling algorithm that takes as input area-limited wireless big data instead of global data. With interference modeling formulated as a supervised learning task, the proposed algorithm can precisely model the interference relationship between an interested user equipment (UE) and any of its primary interfering users. Simulation shows that under high interference scenario the proposed algorithm achieves the same signal to interference plus noise ratio (SINR) prediction accuracy with significant reduction in training complexity compared to baseline algorithms.

The introduction of edge computing provides a broad application scenario for the Internet of Vehicles. Service programs that were not able to be handled timely by On-Board Unit (OBU) can now be placed on Road Side Unit (RSU) to meet users' requirements of End-to-End (E2E) latency and reliability. However, based on the microservice architecture, services are decomposed of multiple microservices, and the complex dependencies between microservices pose new challenges to their placement. To tackle this problem, we first model the dependencies as a directed acyclic graph (DAG), and the long-term interference-aware placement model is then established to depict the load balance between RSUs and network. After that, we formulate it as an integer linear programming (ILP) problem with the aim to achieve a tradeoff between node load cost and transmission cost while reducing the E2E latencies. Considering the local features of DAG topology, an iterative two-phase heuristic microservice placement algorithm is then proposed. Finally, a simulation environment based on real-world electric taxis trajectory data is constructed, and intensive experiments with several baseline algorithms are conducted to verify the superiority of our proposed algorithm.

With the development of the Internet of Things (IoT), certain IoT devices have the capability to not only accomplish their own tasks but also simultaneously assist other resource-constrained devices. Therefore, this article considers a device-assisted mobile edge computing system that leverages auxiliary IoT devices to alleviate the computational burden on the edge computing server and enhance the overall system performance. In this study, computationally intensive tasks are decomposed into multiple partitions, and each task partition can be processed in parallel on an IoT device or the edge server. The objective of this research is to develop an efficient online algorithm that addresses the joint optimization of task partitioning (TP) and parallel scheduling (PS) under time-varying system states, posing challenges to conventional numerical optimization methods. To address these challenges, a framework called online task partitioning action and parallel scheduling policy generation (OTPPS) is proposed, which is based on deep reinforcement learning (DRL). Specifically, the framework leverages a deep neural network (DNN) to learn the optimal partitioning action for each task by mapping input states. Furthermore, it is demonstrated that the remaining PS problem exhibits NP-hard complexity when considering a specific TP action. To address this subproblem, a fair and delay-minimized task scheduling (FDMTS) algorithm is designed. Extensive evaluation results demonstrate that OTPPS achieves near-optimal average delay performance and consistently high-fairness levels in various environmental states compared to other baseline schemes.

Beam hopping (BH)-enhanced satellite-enabled Internet of Things (S-IoT) is a significant complement to terrestrial Internet of Things (IoT), and is also a key component of the nonterrestrial network (NTN)-enabled IoT. For BH low-Earth orbit (LEO) satellite IoT, efficient resource management is crucial for improving system performance. The joint allocation of multidimensional resources, such as time, frequency, and power, needs to be investigated urgently, with multiple purposes of maximizing the long-term throughput, minimizing the average delay of real time (RT) services and assuring the fairness. Involving both discrete and continuous variables, the multidimensional resources allocation problem is formulated as a multiobjective mixed integer programming problem. To address this problem, we transform it into two subproblems. First, the power optimization (PO) subproblem is approximated as a convex optimization problem and further solved. Subsequently, the beam scheduling subproblem is modeled as a Markov decision process. Furthermore, an action masking multiobjective double deep Q network (AMM-DDQN) algorithm is proposed based on Chebyshev scaling and action masking strategy. The simulation results demonstrate the convergence of the proposed AMM-DDQN algorithm, which outperforms the baseline methods in terms of multiple performances. Specifically, compared with the greedy with distance limit strategy, TopKDQN without PO method, TopKDQN method, genetic algorithm, and random method, the average delay of RT services of the proposed algorithm is reduced by 22.51%, 10.82%, 4.42%, 34.41%, and 52.13%, respectively, achieving QoS guarantees in BH LEO S-IoT.

This article addresses the problem of identifying disconnected agents in multiagent systems via external estimators. Specifically, we employ external estimators with an appropriately designed decision rule to identify the disconnectedness (i.e., the status of being disconnected) between two arbitrarily chosen agents in formation-control multiagent systems. The design of the decision rule is inspired by the unit-root testing problem of autoregressive time series. To make the best possible decision, a best-effort procedure is also proposed. Then, by introducing the concept of connected components (or just components) in graph theory, and using the methods of consensus analysis and time-series analysis, we develop an analytical framework to show the theoretical performance of the designed decision rule. A particularly important result shown by our analysis is that the miss probability of the decision rule can converge to 0 as the number of data samples increases. Finally, simulation results validate the performance of the decision rule and the best-effort procedure, showing that they can perform well even in small samples.

Reconfigurable intelligent surface (RIS) is regarded as a promising technology to potentially enhance communications and localization capabilities. In this paper, we investigate a challenging received signal strength (RSS) based localization problem utilizing RIS. In particular, we consider a mixed line-of-sight and non-line-of-sight (LOS/NLOS) scenario with multiple sources and sensors as well as one RIS. Firstly, we obtain a closed-form Cramér-Rao lower bound (CRLB) expression and formulate a joint optimization problem to minimize the CRLB. Due to the non-convex objective function and coupled relationship between variables, it is difficult to solve directly. To overcome such issues, a novel two-stage alternating localization and passive beamforming (PBF) scheme is proposed, where the optimization problems corresponding to two stages, namely the joint localization and NLOS identification (JLNI) stage and the PBF optimization (PBFO) stage are alternately addressed. Specifically, for the JLNI stage, we adopt alternating optimization, parametric sparse Bayesian dictionary learning and block coordinate descent approaches to jointly estimate the locations of sources and LOS/NLOS path condition. Subsequently, for the PBFO stage, we optimize the PBF vector by exploiting semi-definite relaxation, difference-of-convex programming and successive convex approximation approaches. Finally, compared with the state-of-the-art methods, numerical simulations demonstrate the superiority and effectiveness of the proposed scheme in terms of CRLB, localization error and NLOS identification accuracy.

Edge computing servers have been widely deployed in recent years to address the requirements of diverse tasks that are sensitive to delays and computationally intensive. However, due to their independent nature and uneven distribution of service requests, certain clusters may be relatively idle, while others may be overloaded. This situation can result in increased latency for certain tasks, and it prevents the full utilization of resources in the edge clusters. To mitigate this problem, we design and implement a prototype testbed for task offloading, aimed at achieving computing and network convergence. This testbed facilitates collaboration among multiple edge computing clusters. We construct multiple clusters using Intel NUC mini computers and incorporate key enabling technologies into the system. We assess the testbed's performance by employing multiple video processing services that require low latency and high computational capacity. In scenarios with uneven service requests, load balancing can be achieved across the edge computing clusters, resulting in reduced response latency for user tasks.

The Cell-Free Massive Multiple-Input Multiple-Output (CF-MIMO) system is a promising technology for beyond-fifth-generation (B-5G) networks. It involves deploying multiple access points (APs) with multiple antennas to serve groups of users (UEs) cooperatively. In this paper, we introduce two algorithms that utilize big data technology for interference identification and signal-to-interference-plus-noise ratio (SINR) prediction. These algorithms effectively identify user-level interference information and provide support for resource allocation. They outperform traditional machine learning methods in terms of accuracy, time efficiency, and computation complexity by a significant margin. To establish the theoretical foundation, we derive the closed form of the average SINR based on large-scale fading coefficients (LSFCs). Our results demonstrate that our algorithms significantly enhance prediction accuracy by 50%-75% and achieve an impressive 8-to 80-fold improvement in training efficiency compared to the benchmark scheme.

Satellite constellation is envisioned as an important approach to enhancing the capability of existing networks. Technologies such as Network Function Virtualization (NFV) and Service Function Chain (SFC) have been proposed to make satellites much more tolerant to different kinds of service requests. Owing to Software-Defined Networks (SDN), satellite constellations can be managed in a more flexible manner. However, due to the high variability of constellation and multi-types of Virtual Network Functions (VNFs), it becomes a major challenge to select appropriate instances of VNFs to concatenate for routing when orchestrating resources to map SFC requests. In this paper, we investigate SFC Mapping Problem (SFC-MP) in a dynamically changing logical segmented network to provide stable communication service. We formulate the problem as a Binary Integer Programming (BIP) model. In addition, we propose a new Continuous Logical Segmented Network Resource Aware Routing (LSNRAR-Continuous) algorithm for SFC requests routing to achieve network load balancing and reduce the impact of VNF migration on services. Simulation results show that the algorithm can effectively solve the SFC-MP problem, and the proposed algorithm has higher performance in terms of average delay, mapping cost and service stability compared with existing literature algorithms.

The fifth-generation (5G) wireless network is expected to support emerging applications requiring ultra high reliability and low latency, such as self-driving cars, factory automation (industry 4.0), and smart grid, known as ultra-reliable and low-latency communications (URLLC). Uplink grant-free (GF) transmission is considered as a promising technology for supporting the rigorous requirements of URLLC by saving the time of requesting/waiting for the scheduling grant and supporting the K-repetition transmission. Besides, the intercell interference (ICI) in uplink multi-cell GF transmission is another critical issue to be solved. In this paper, we propose an interference-aware based radio resource configuration framework of URLLC uplink GF transmission which means that we can configure the radio resources by utilizing the available interference information to mitigate the impact of severe ICI on the transmission performance in URLLC. Numerical results show that, the proposed scheme can greatly improve the total transmission reliability and has higher scalability and robustness compared to prior art solutions under the condition of satisfying the transmission delay requirement and resource constraint.

The severe inter-cell interference (ICI) problem in ultra-dense networks seriously restricts the capacity of the wireless network. The major bottleneck of this problem is the inability to obtain accurate interference information. However, interference information is hidden in data generated in wireless network. Motivated by this, this paper proposes a novel neural-network-based uplink interference identification algorithm to accommodate interference model. We design neural network based on interference model, use data generated in operating wireless network to mine inter-user signal-to-interference ratio information in wireless network, and realize accurate prediction of signal-to-interference-plus-noise ratio (SINR) without extra radio resource consumption. The simulation results show that the proposed algorithm could achieve the same level of prediction accuracy as the baseline algorithms with the training time two orders of magnitude lower, which is suitable for practical applications.

Abstract Unmanned aerial vehicles (UAVs), widely used due to their low cost and versatility, pose security and privacy threats, which calls for their reliable recognition at low altitudes. However, strong ground clutter and multipath effects severely interfere with the weak radar echoes reflected off the micro‐UAVs, resulting in severe degradation of recognition reliability. Based on channel modelling and UAV recognisability analysis, a time‐frequency transform‐aided contrastive learning model is proposed to suppress the severe ground clutter and reliably recognise low‐altitude UAVs. In the proposed framework, a time‐frequency transform unit is first applied to suppress the multipath‐induced ambiguity effect and ease the semantic feature extraction via Zhao‐Atlas‐Marks transform and morphological operation. Thereafter, a contrastive‐learning‐based feature extraction and fusion unit is established to suppress non‐target clutter interference and extract recognisable semantic UAV features. Finally, a gated recurrent unit‐based classifier is designed for UAV recognition. Sufficient experiments are carried out on both real and simulated data sets, and the comparative results verify that the proposed model outperforms the mainstream algorithms and improves the detection accuracy by more than 5% under severe ground clutter interference.

Energy efficiency (EE) is acknowledged as a key performance indicator for 5G networks. This paper mainly studies the problem of energy efficient power allocation in 5G Ultra-dense network (UDN). The existing power allocation algorithms mainly focus on the downlink, and most of them are based on analytic algorithms, which has high computational complexity and is difficult to meet the needs of large-scale deployment in UDN. In order to reduce the complexity, this paper proposes an uplink power allocation algorithm based on multi-agent reinforcement learning (MARL). Each user acts as an agent and all the users interact with the communication environment simultaneously. In the MARL framework of the proposed algorithm, we add a performance estimator to help train Q-network. Simulation results show the proposed algorithm performs efficiently in term of energy efficiency as well as maintaining a high network throughput at the same time. The complexity of the proposed algorithm is proved to be reduced by at least two magnitudes compared with the analytic algorithms.

For the orthogonal frequency division multiplexing-based orthogonal time-frequency-space (OFDM-based OTFS) systems, this paper studies the pilot optimization problem under the framework of distributed compressed sensing (DCS) and complex exponential basic extension model (CE-BEM). In order to reduce the inter-subcarrier interference (ICI) caused by the doubly selection (DS) channel and improve the accuracy of sparse channel estimation based on DCS, we propose pilot structure design and pilot pattern optimization schemes, respectively. First, we insert multiple sets of pilot clusters in the frequency domain OFDM symbols, where each set of pilot clusters contains an effective pilot and a guard pilot, and the data on both sides of the effective pilot is set equal to mitigate adjacent ICI. Then, through mutual coherence property, the optimization problem of effective pilot patterns in co-sparse symbols is transformed into a set of optimization problems of pilot interval, and a pilot pattern design algorithm based on pilot intervals is proposed. Finally, simulation results verify the effectiveness of the pilot structure design scheme, and the proposed algorithm not only has low computational complexity but also has superior system performance.

Due to the characteristics of being license-free, the ISM (Industrial, Scientific, Medical) bands are frequently utilized by wireless communication systems. However, the ubiquitous and unmanaged IEEE 802.11 systems deployed in the ISM bands may bring non-negligible interference to emergency communications. This paper considers suppressing the transmission of 802.11 systems in 2. 4GHz ISM band for protecting the public safety in emergency scenarios. To this end, two kinds of suppression frames that comply with the 802.11 protocol are analyzed, which respectively borrow the ideas of virtual carrier-sense attack and spoofing. The validity of each of the frames is then verified both qualitatively and quantitatively by the designed experiments with multiple commercial off-the-shelf (COTS) 802.11 devices. Based on which we propose an integrated suppression method that is effective for all tested devices. Further experiments and analysis show that the presented method outperforms the state-of-the-art suppression methods in terms of energy consumption and applicability.

Spectrum prediction has recently gained a lot of attention due to its extensive applications in cognitive radio networks. However, most of the related research assumed that the spectrum occupancy pattern is time-invariant, which limits the performance of proposed prediction methods for the high burst frequency bands, e.g. the ISM (Industrial, Scientific, Medical) bands. In order to improve the prediction accuracy for them, this paper first analyzes the characteristics of the collected real WiFi data in 2.4GHz ISM band, and shows the burstiness of the band from multiple aspects. Based on the analysis, we then propose a MultiLayer Perceptron based Reinforcement Learning (RLMLP) method which could adaptively select the corresponding predicting action according to the state to which any piece of data belongs. The state space of the method consists of multiple data categories that are determined by the results of feature partitioning, while the action space is composed of multiple MLPs with the same mapping structure. Finally, numerical results on the collected data show that the proposed RLMLP method is significantly better than the state-of-the-art algorithms in terms of the prediction performance.

With the rapid development of 5G technology, there is an increasing demand of high-definition (HD) video service, so that efficient content transmission is expected to guaranteed the quality of experience of users. However, traditional terrestrial networks can hardly support this kind of service due to the limited coverage and capability especially in scene of remote area or peak hours of hotspots. Under the support of High Throughput Satellite, satellite can serve as a supplement in hybrid satellite-terrestrial networks (HSTN) to provide various of services. Specifically, aggregation in packet level for collaborative transmission between satellite and terrestrial networks is in direction of development which should be reconsidered. In this paper, a classic SDN-aware HSTN architecture is adopted to capture content information of the system and make strategy dynamically for efficient distribution of content in finer scale. Key technologies, including tag method, path selection strategy and reordering scheme, are proposed to achieve collaborative transmission of HD videos. Finally, complete implementation of a prototype, a Hardware In the Loop (HIL) platform with the SITL module of OPNET, is built to illustrate the feasibility and effectiveness of the proposed solutions. Numerical results show that collaborative transmission in HSTN can effectively realize link aggregation, which has great significance for complex conditions in future networks.

The ultradense network (UDN) has been identified as a promising technology to address the challenge of the ever increasing demands on data rates or massive accesses, especially for Internet of Things (IoT)-oriented applications. However, the severe co-channel interference (CCI) generated by densely deployed femtocells in UDN poses a critical issue. The conflict graph is widely recognized as an effective representation of the underlying interference constraints in the network and a powerful tool for interference management. Different from most prior studies that construct conflict graphs based on accurate geographical distance information, which is usually hard to obtain in reality, an accurate and practical machine-learning-based conflict graph construction approach is proposed in this article. Based on the constructed graph, the throughput maximization problem, which is NP-hard, is decoupled into a user clustering subproblem and a subchannel allocation subproblem. The former is solved by proposing a low complexity user clustering algorithm with modified balanced Mink-Cut, which identifies low-interference entities (i.e., clusters) for spectrum reuse; and the latter is solved by presenting a subchannel allocation algorithm with accumulative intercluster interference considered, which could further reduce the interference caused by spectrum reuse. Moreover, to further improve the spectrum efficiency, a supplementary allocation algorithm is deployed to allocate the remaining subchannels. The simulation results show that the proposed approach improves the aggregate throughput by up to 186.68%, compared with the other existing methods.

We address the problem of learning hidden graph structure from spatiotemporal signals which are prevalent in distributed sensor networks. Based on a space-time representation model that takes into account correlated properties in dynamic evolution, we formulate the graph learning problem as a regularized multi-convex optimization problem. A correlation-aware and differential smoothness-based graph learning method (CADS) is proposed, which simultaneously estimates the time correlation of each vertex and refines the graph under the differential smoothness prior. The proposed method promotes such smoothness property in each learning step, leading to an improvement of learning accuracy. Experiments on synthetic and real-world datasets demonstrate the effectiveness of the proposed CADS which outperforms the state-of-the-art graph learning methods in classification and prediction tasks.

Received signal strength (RSS) measurement based source localization is highly dependent on the propagation model. However, such propagation model is not easy to be captured in the practical applications. In this paper, we address the multiple sources localization (MSL) problem while jointly estimating parametric propagation model. Specifically, we model the localization problem as being parameterized by the unknown source locations and propagation parameters. Then, the localization problem is reformulated as a joint parametric sparsifying dictionary learning (PSDL) and sparse signal recovery (SSR) problem. Finally, the problem is solved under the framework of sparse Bayesian learning with parametric dictionary approximation. We compare the proposed method with the state-of-the-art MSL algorithms as well as Cramér-Rao lower bound (CRLB). Numerical simulations highlight the effectiveness of the proposed method.

Graph learning often boils down to discovering the hidden structure of data that is characterized by a graph. Most of the previous works mainly focus on static data processing. However, the distributed sensor network gives rise to space- time data which exhibits spatiotemporal correlation and evolves smoothly over time. In this paper, we address the problem of learning graphs from space-time sensing data. Based on a dynamic model that takes into account both the spatial and temporal correlated property in temporal evolution, we propose a spatiotemporal smoothness-based graph learning method (GLSS), which novelly introduces the spatiotemporal smoothness to the field of space-time data analysis. By simultaneously recovering data and refining graphs under the spatiotemporal smoothness prior, the graph learning accuracy can be efficiently improved. Experiments on synthetic data and real-world data in weather sensor networks demonstrate that joint space-time analysis in proposed GLSS can bring benefits to graph learning and outperforms current the state-of-the-art methods.

With emerging requirement of local low-latency services, Mobile Edge Computing (MEC) is a promising solution to tackle the challenge between urgent demands for computation capability and limited battery energy of mobile devices. Moreover, the sharing property of applications costs waste as for the processing of redundant data, which derives an imperative need for the collaboration among users. In this paper, by leveraging these features, we design a D2D-assisted MEC system for energy efficiency of devices with the consideration of task delay. For sake of energy minimization, a strategy that jointly optimizes resource allocation and tasks offloading assignment is proposed. Further, a low-complexity algorithm is developed to decompose the original problem into two subproblems and get the sub-optimal solution efficiently. Simulation results present the efficient and effective performance of the proposed algorithm with different application parameters. Particularly, it is shown that our proposed algorithm gets 48.41%~90.58% and 37.33%~96.63% improvement of energy consumption than those of non-collaboratively offloading scheme and randomly offloading scheme, respectively.

Mobile edge computing (MEC) is one of the key technologies for fifth generation networks and beyond, which brings computation resources in proximity to end users. While enabling computing capability at the network edge, it also introduces extra energy consumption to the network operation. Moreover, the nonuniform traffic distribution of mobile network makes the utilization of MEC platforms unbalanced. In this paper, we propose an online optimization strategy of MEC server (MECS) computation task offloading with sleep control scheme to minimize the long term energy consumption of the MECS network. First, the energy optimization problem under delay constraint is formulated which considers both the radio and computation resources. Then, a Lyapunov-based approach is proposed to convert the long term optimization problem to a per-slot optimization problem which only requires information of current time slot. An online offloading algorithm is proposed to make decisions in each time slot. Finally, the system performance is evaluated and the impacts of several key parameters are analyzed. Simulation results demonstrate that our proposed strategy can significantly reduce the long term average energy consumption of the mobile edge network by 30% to 90% under different workload scenarios, while keeping a relatively low system delay compared with the schemes without MEC cooperation and sleep control.

Cognitive radio (CR) has received wide attention for enhancing the spectrum utilization. Spectrum prediction can be fully utilized in both time and frequency domains for cognitive access. In this paper, Long Short-Term Memory (LSTM) networks method is adopted for spectrum prediction. Based on prediction of the power of future time slots, the method can help to achieve spectrum utilization flexibility by calculating throughput of shared channels. A new spectrum access strategy, which integrates optimal spectrum sensing interval in time domain and channel selection based on the presented LSTM networks method in frequency domain, is proposed. In particular, for multiple channels of the shared spectrum, the optimal sensing interval of each channel is calculated, which is then adopted as the reference output length of the LSTM networks method, with predicted results, a feedback which consists of a preferred channel list will be conducted for spectrum access. With both real-life and generated data, the proposed LSTM networks method is verified, which outperforms commonly used Neural Network (NN) and Hidden Markov Model (HMM) methods. Numerical results also show that the proposed spectrum access strategy is capable of increasing throughput of the cognitive system and reducing energy consumption of spectrum sensing significantly.

In this paper, a power allocation scheme based on a stackelberg game model is proposed to coordinate complicated interference in heterogeneous network. Firstly, the power allocation problem is modeled as a stackelberg game where base stations (BS) are treated as competitive players. Then a two-stage pricing-based power allocation scheme is proposed, where macro-BS and micro-BS cooperate with each other in order to provide optimal power allocation strategy. Theoretical analysis and simulation results both validate that the proposed scheme not only makes improvement in spectral and energy efficiency, but also reduces computational complexity, especially in dense deployment scenario.

The main requirement of the computation offloading service is the low service delay, which would correspond to a high Quality of Service (QoS). Recently, many works show that placing virtual resources (e.g., computing resource) in the Mobile Edge Network (MEN) to form a Mobile Edge Computing (MEC) system contributes to a lower service delay. However, due to the limited virtual resource in the MEN and the constraints of the wireless channel condition, only part of users can be served with low enough service delay. Moreover, considering the independent virtual machine (VM) environment on the MEC server in MEN for each user, efficient virtual resources management is needed. In this paper, we propose two computation offloading strategies combined with the virtual resources management to minimize the average service delay, where the virtual resources consists of the computing resources and the storage resources. One of the proposed strategies guarantees the fairness of users while the other one not. Then the optimal deployments of VMs with different strategies are obtained through the simulations. We also find and calculate the optimal proportion of these two kinds of virtual resource when there is only a limited budget for them.

Cognitive satellite terrestrial networks have received widespread attention recently for improving the spectrum utilization. In this paper, a hybrid interweave-underlay spectrum access (HIUSA) scheme based on spectrum sensing in 5GHz license-exempt spectrum is proposed, which eliminates the performance degradation brought by inaccurate parameters estimation of the interference link in a large extent, and enhances the throughput of the cognitive system substantially. While analyzing relevant details, we also focus on the resource allocation (RA) problem in this scenario, the RA problem takes the maximum throughput of the cognitive satellite communications (SatCom) as target, and subjects to the requirements of cognitive terminals. Then, the convex RA problem is solved by a simplified iteration algorithm. Extensive simulation results are given to demonstrate the performance and effectiveness of the proposed HIUSA scheme as well as the RA approach, by contrasting with the legacy system as well as the common method.

Caching at the user devices is a key technology to alleviate backhaul load and improve users' quality of experience in mobile edge networks. However, due to the concern of privacy and limited battery life, users are not willing to share their resources. In this study, the authors jointly design the caching strategy and incentive scheme to encourage the users to share their storage resources and improve the social welfare of the cellular network. First, the user equipments (UEs) are classified into different types according to their preference to share cache resources. Then, based on contract theory, an optimisation problem with necessary constraints is formulated aiming at maximising the base station (BS)'s utility. The reward the BS pays for a UE is based on the total amount of contents it shares with other UEs, which is related to the caching policy of UEs. A heuristic caching strategy is proposed and the optimal contract is obtained. Finally, the system performance of the proposed solution is analysed, simulation results show that the incentive scheme can improve the willingness of users to share contents, and the proposed caching strategy contributes more to the social welfare compared with two baseline caching schemes: fair caching and random caching.

Time-frequency analysis is one of essential signal processing tool for wireless sensor signal in Internet of Things (IoT), but its traditional processing approaches, such as short time-frequency transformation (STFT) and discrete wavelet transformation (DWT), are challenged by the limitation of capability to self-learn from unknown environments and adjust parameters adaptively. To address this problem, we propose to build up the deep learning network to learn time-frequency analysis to instead of traditional STFT and DWT approaches. With using typical neural network layers to remodel STFT and DWT operations, the proposed models consider the efficiency on both training and processing procedures and show their parameter adaptability and capability of deep feature extraction from sensor signals. Moreover, we demonstrate how to integrate learning time-frequency analysis networks into practical IoT applications, signal detection in noisy environment, and classifying of various modulated wireless sensor signal, by which their performance are further evaluated in terms of computation complexity and efficiency.

Base station (BS) sleeping operation in transient process has been widely analyzed in current studies to save cellular network energy consumption. In this paper, we propose a hysteretic BS sleeping strategy in 5G cellular network. The BS adjusts its transmitting power to adapt to the traffic load in active state, and frequently goes to sleep state and keeps sleeping until N requests assembled. When the BS wakes up or shuts off, it will experience a state transition delay, which means the BS actions somehow lag behind the BS decisions. This paper explored the impact of state transition delay on the power consumption and traffic delay performance, and discussed the tradeoff between power-saving and traffic delay requirements. Numerical results show that the longer transition delay is, the worse system performance the BS is suffered. And the BS sleeping operation is energy-efficient only under a short transition delay.

To meet the increasing demand for passengers in high- speed train (HST) system, it is critical to develop the understanding of properties in HST propagation environment. This paper derives a new channel model for HST by conducting a measurement campaign in a commercial HST network at 1.905 GHz in China from Beijing to Tianjin. A median average filtering (MAF) algorithm is proposed to remove the effect of multipath on the analysis in large-scale parameters. Meanwhile, spatial autocorrelation and parameters of shadow fading are researched associated with the existing topology of HST network. Furthermore, the performance of the proposed method is evaluated and compared with local mean filtering algorithm that followed Lee's law by proceeding both goodness-of-fit (GoF) and Kolmogorov- Smirnov (KS) tests. The results indicate that the proposed method can precisely estimate the channel model parameters and provide a better fitting to the measured data. Thus, the channel model developed in this paper can be useful as a guide to characterize the propagation channel in HST environment.

The emerging 5G wireless networks will pose extreme requirements such as high throughput and low latency. Caching as a promising technology can effectively decrease latency and provide customized services based on group users behaviour (GUB). In this paper, we carry out the energy efficiency analysis in the cache-enabled hyper cellular networks (HCNs), where the macro cells and small cells (SCs) are deployed heterogeneously with the control and user plane (C/U) split. Benefiting from the assistance of macro cells, a novel access scheme is proposed according to both user interest and fairness of service, where the SCs can turn into semi- sleep mode. Expressions of coverage probability, throughput and energy efficiency (EE) are derived analytically as the functions of key parameters, including the cache ability, search radius and backhaul limitation. Numerical results show that the proposed scheme in HCNs can increase the network coverage probability by more than 200% compared with the single- tier networks. The network EE can be improved by 54% than the nearest access scheme, with larger research radius and higher SC cache capacity under lower traffic load. Our performance study provides insights into the efficient use of cache in the 5G software defined networking (SDN).

Fog computing based radio access network is a promising paradigm for the fifth generation wireless communication system to provide high spectral and energy efficiency. With the help of the new designed fog computing based access points (F-APs), the user-centric objectives can be achieved through the adaptive technique and will relieve the load of fronthaul and alleviate the burden of base band unit pool. In this paper, we derive the coverage probability and ergodic rate for both F-AP users and device-to-device users by taking into account the different nodes locations, cache sizes as well as user access modes. Particularly, the stochastic geometry tool is used to derive expressions for above performance metrics. Simulation results validate the accuracy of our analysis and we obtain interesting tradeoffs that depend on the effect of the cache size, user node density, and the quality of service constrains on the different performance metrics.

A multi-carrier one-way relay network is considered, in which a source wishes to send information to a destination via a full-duplex amplify-and-forward relay. We perform power allocation across different subcarriers for the source and the relay, as well as subcarrier pairing at the relay, so as to maximize the achievable sum rate subject to individual power budget constraint at each transmit node, and therefore formulate the joint power allocation and subcarrier pairing optimization problem. Due to the interdependency in the power allocation between self-interference subcarrier and outgoing subcarrier at the relay node, we propose a suboptimal scheme to trade the performance for computational complexity. Then dual decomposition technique is employed for power allocation, while the subcarrier pairing problem is solved by Hungarian algorithm. Simulation results show that the proposed resource allocation scheme can significantly improve system performance.

Fractional frequency reuse (FFR) is an efficient management technique to eliminate inter-cell interference (ICI) in multi-cell orthogonal frequency division multiple access (OFDMA) networks through inter-cell coordination. Generally, the derivations of throughput and coverage probability are treated as separate problems or investigated in different ways. In this paper, we derive average cell throughput and coverage probability expression for both round robin (RR) and maximum SINR (MSINR) scheduling strategies with different subcarrier allocation schemes from the same starting-point, the cumulative distribution function (CDF) of the instantaneous SINR . Results of static and dynamic subcarrier allocation schemes are compared to verify that latter is more reasonable because it takes both throughput and fairness into consideration. Analytical and simulation results also show that average cell throughput increases and coverage probability decreases with the distance threshold. Based on this, we investigate the optimal distance threshold to attain as good balances between throughput and coverage with different number of users in a cell. In terms of base station (BS) power control, we demonstrate that there exists an optimal power to satisfy coverage probability and obtain maximum throughput no matter what scheduling strategy is applied.

Inter-Cell Interference (ICI) is always a key problem in Fractional Frequency Reuse (FFR) system to be focused on, which should be well resolved to pursue higher throughput and better power efficiency. In this paper, we investigate throughput and power efficiency of RR scheduling in FFR system by both closed-form expression and Monte Carlo trials method. We improve a previous throughput model by applying variable subcarrier distribution scheme and upgrading expression for the Cumulative Distribution Function (CDF) of SINR. Then we propose a new closed-form expression of average cell throughput. The fairness performance of this model is better than that using fixed subcarrier distribution scheme. Meanwhile, an optimal radius threshold is selected so as to achieve best throughput performance. Then we manage to explore the relationship between cell power efficiency and transmit power based on the optimal radius threshold. From both analytical and simulation results, it is shown that power efficiency is monotonically decreasing with transmit power. Hence operational power is introduced into power efficiency as energy consumption for base station. After that, the highest power efficiency can be reached by setting a proper and reasonable transmit power.

With the worldwide evolution of 4G generation and revolution in the information and communications technology(ICT) field to meet the exponential increase of mobile data traffic in the 2020 era, the hybrid satellite and terrestrial network based on the soft defined features is proposed from a perspective of 5G. In this paper, an end-to-end architecture of hybrid satellite and terrestrial network under the control and user Plane (C/U) split concept is studied and the performances are analysed based on stochastic geometry. The relationship between spectral efficiency (SE) and energy efficiency (EE) is investigated, taking consideration of overhead costs, transmission and circuit power, backhaul of gateway (GW), and density of small cells. Numerical results show that, by optimizing the key parameters, the hybrid satellite and terrestrial network can achieve nearly 90% EE gain with only 3% SE loss in relative dense networks, and achieve both higher EE and SE gain (20% and 5% respectively) in sparse networks toward the future 5G green communication networks.

This study investigates the cross‐tier base station (BS) cooperation in non‐uniform heterogeneous networks where the distribution of pico BSs (PBSs) is modelled as Neyman–Scott cluster process. The authors propose an edge aware cross‐tier cooperation scheme to improve the performance of edge hotspot users that have weaker signal‐to‐interference‐plus‐noise ratio (SINR). Taking consideration of various user behaviours, non‐hotspot users are only served by the nearest macro BS whilst the hotspot users with better SINR are only served by their serving PBSs. The edge hotspot users who suffer from high cross‐tier interference operate in the cooperation mode. Stochastic geometry is utilised to derive the SINR and energy efficiency performance of the proposed scheme, which is compared with other classical schemes such as full cooperation (FC) and traditional non‐cooperation scheme. Numerical results show that compared with the FC scheme, the proposed scheme can maximise the energy efficiency of the network by an optimal cooperation threshold, when SINR coverage is larger than a threshold. The authors also find that user behaviour have little effect on the tradeoff between SINR Coverage and energy efficiency, unless spatial aggregation coefficient is very small.

In cloud radio access networks (C-RANs), a substantial amount of data must be exchanged in both backhaul and fronthaul links, which causes high power consumption and poor quality of service (QoS) experience for real-time services. To solve this problem, a cluster content caching structure is proposed in this paper, which takes full advantages of distributed caching and centralized signal processing. In particular, redundant traffic on the backhaul can be reduced because the cluster content cache provides a part of required content objects for remote radio heads (RRHs) connected to a common edge cloud. Tractable expressions for both effective capacity and energy efficiency performance are derived, which show that the proposed structure can improve QoS guarantees with a lower cost of local storage. Furthermore, to fully explore the potential of the proposed cluster content caching structure, the joint design of resource allocation and RRH association is optimized, and two distributed algorithms are accordingly proposed. Simulation results verify the accuracy of the analytical results and show the performance gains achieved by cluster content caching in C-RANs.

A harvest-use-store power splitting (PS) relaying strategy with distributed beamforming is proposed for wireless-powered multi-relay cooperative networks in this paper. Different from the conventional battery-free PS relaying strategy, harvested energy is prioritized to power information relaying while the remainder is accumulated and stored for future usage with the help of a battery in the proposed strategy, which supports an efficient utilization of harvested energy. However, PS affects throughput at subsequent time slots due to the battery operations including the charging and discharging. To this end, PS and battery operations are coupled with distributed beamforming. A throughput optimization problem to incorporate these coupled operations is formulated though it is intractable. To address the intractability of the optimization, a layered optimization method is proposed to achieve the optimal joint PS and battery operation design with non-causal channel state information (CSI), in which the PS and the battery operation can be analyzed in a decomposed manner. Then, a general case with causal CSI is considered, where the proposed layered optimization method is extended by utilizing the statistical properties of CSI. To reach a better tradeoff between performance and complexity, a greedy method that requires no information about subsequent time slots is proposed. Simulation results reveal the upper and lower bound on performance of the proposed strategy, which are reached by the layered optimization method with non-causal CSI and the greedy method, respectively. Moreover, the proposed strategy outperforms the conventional PS-based relaying without energy accumulation and time switching-based relaying strategy.

Relay power control for two-way (TW) full-duplex (FD) relay network is studied in this letter. In the prior literature, the relay is assumed to always use its full transmit power in a TW FD relay network. However, high transmit power will increase loopback self-interference at the relay node and thus make the incoming link to the relay become the bottleneck for the end-to-end performance. Therefore, it is suboptimal to always utilize the full power capability of the relay. Thus, we propose three relay power control schemes, which can, respectively, maximize 1) the data rate of an individual end node, 2) the minimum data rate of the two end nodes, and 3) the sum data rate of the two end nodes. Numerical results show that, compared to using full relay power, the proposed relay power control schemes can improve system performance while reducing relay power consumption.

The cloud radio access network (C-RAN) is an emerging network architecture that holds the promise of coping with the explosive growth of mobile wireless data. In this paper, by considering the stochastic traffic arrivals and time-varying channel conditions, we address the stochastic optimization of joint remote radio head (RRH) activation and linear beamforming to maintain delay performance and minimize average network power consumption in downlink slotted C-RAN. We first formulate the joint optimization as a group sparse beamforming problem. Based on Lyapunov optimization technique, the stochastic optimization problem is then transformed into a queue-aware joint RRH activation and beamforming problem, which can be greedily solved at each slot. Finally, a low-complexity stationary algorithm with guaranteed convergence and closed-form expressions is proposed. The proposed algorithm can be implemented in a parallel manner, thus it is highly scalable to a large-sized C-RAN. Extensive numerical simulations validate the effectiveness of the proposed algorithm.

An optimal resource allocation scheme for orthogonal frequency division multiplexing (OFDM) based multiuser two-way full duplex (FD) relaying is discussed in this paper. Compared with traditional half duplex (HD) relaying, FD mode can double data rate under perfect interference cancellation, which, however can not be achieved under realistic conditions. Our goal is to maximize the throughput of the whole system by allocating available power and subcarriers under residual self-interference. We formulate a nonlinear optimization problem under individual power constraints. An optimal solution is obtained by using Lagrange dual decomposition method. In addition, a suboptimal solution which reduces the computational complexity significantly is also provided in this paper. Numerical results indicate advantage of the optimal resource allocation scheme proposed in this paper.

This paper studies the physical layer security in cognitive relay network (CRN) with multiple antennas in the presence of multiple eavesdroppers. Under spectrum sharing scenario and orthogonal space-time block code (OSTBC) transmission, we derive both the exact and asymptotic expressions of secrecy outage probability over Rayleigh fading channels and give the reliability-security tradeoff analysis. The results which have been verified by Monte Carlo simulation show that the loss of the secrecy outage performance caused by an increase of eavesdroppers number can be totally overcome by multiple antenna diversity. It's illustrated that increasing the number of antennas can also improve both reliability and security of the system. Besides, the asymptotic analysis indicates the secrecy diversity order is only determined by number of antennas and is independent with number of eavesdroppers. The secrecy array gain is relevant with both number of antennas and eavesdroppers. In other words, the existence of eavesdroppers will degrade the secrecy outage performance but will not affect the diversity order of the system.

Considering that full-duplex relaying (FDR) can achieve higher spectral efficiency than traditional half-duplex relaying (HDR), a spectrum sharing protocol based on FDR is proposed in this paper. We investigate a two-phase FDR spectrum sharing protocol in cognitive two-way relay networks. Analytical expressions for the outage probabilities of the primary and secondary systems under the proposed protocol are derived in a closed form. Monte-Carlo simulations are carried out to confirm the analytical expressions. Results show that the performance of our two-way FDR spectrum sharing protocol depends on the residual loop interference (LI) at the relay node. When the residual LI is small, the proposed FDR spectrum sharing protocol can significantly improve the outage performance. Furthermore, if the residual LI is small enough, the two-way FDR spectrum sharing scheme can outperform its HDR counterpart, both for the primary system and the secondary system.

In this paper, the resource management problem in geographically distributed cloud systems is considered. The Follow Me Cloud concept which enables service migration across federated data centers (DCs) is adopted. Therefore, there are two types of service requests to the DC, i.e., new requests (NRs) initiated in the local service area and migration requests (MRs) generated when mobile users move across service areas. A novel resource management scheme is proposed to help the resource manager decide whether to accept the service requests (NRs or MRs) or not and determine how much resources should be allocated to each service (if accepted). The optimization objective is to maximize the average system reward and keep the rejection probability of service requests under a certain threshold. Numerical results indicate that the proposed scheme can significantly improve the overall system utility as well as the user experience compared with other resource management schemes.

Nowadays, it has become feasible to use mobile nodes as contributing entities in computing systems. In this paper, we consider a computational grid in which the mobile devices can share their idle resources to realize parallel processing. The overall computing task can be arbitrarily partitioned into multiple subtasks to be distributed to mobile resource providers (RPs). In this process, the computation load scheduling problem is highlighted. Based on the optimization objective, i.e., minimizing the task makespan, a buyer-seller model in which the task sponsor can inspire the SPs to share their computing resources by paying certain profits, is proposed. The Stackelberg Pricing Game (SPG) is employed to obtain the optimal price and shared resource amount of each SP. Finally, we evaluate the performance of the proposed algorithm by system simulation and the results indicate that the SPG-based load scheduling algorithm can significantly improve the time gain in mobile grid systems.

Cloud-based mobile services are interactive in nature. Due to the strong correlation between uplink (UL) requests and downlink (DL) responses, it is irrational to optimize the UL and DL resource control problems separately and independently. In this paper, a novel traffic model for interactive mobile cloud services (IMCSs) is constructed, based on which a joint UL-DL scheduling and power allocation strategy is developed. The objective is to minimize the roundtrip delay of causally related UL and DL data groups subject to the average UL transmission power constraint. The algorithm can operate without knowledge of the traffic arrival rates and be implemented in a distributed way so that the transmission overheads between the mobile terminals and the cloud server is reduced.

Future wireless network will address the explosive increase demand of high-data-rate video services as well as massive-access machine type communication (MTC) requests, so that increasing number of small cells are conceived to be densely deployed in hot spots, resulting in an Ultra-dense Network (UDN). As a main issue for the future network, UDN is a step further towards a low-cost, self-configuring and self-optimizing network, while also leading to high-frequent measurement, intolerable handover failure (HOF), as well as huge power consumption in both the terminal and access network. Thus, mobility enhancement in ultra-dense scenario has become a critical problem for the next generation wireless systems. To solve this problem, the split of control plane and user plane (C/U) has become one of the most promising way, as it allows more flexibility and better service control schemes. Inspired by this, a set of macro assisted small cell enhancement schemes is proposed contributing to a novel Data-only Carrier (DoC) system in our previous work. In this paper, for improving the handover (HO) performance, new mobility-enhanced schemes are designed and analyzed in detail in DoC network, taking into consideration of mobility, flexibility and various typical handover scenarios. Simulations are conducted by a system-level platform to illustrate the fundamental relationship between key handover parameters and mobility performance. Numerical results show that the gain of system HOF rises by 53.6% via optimizing and reconfiguring the handover parameters in DoC network. In addition, the DoC network has an excellent performance gain in UDN with 82% HO improvement and 44.34% energy efficiency promotion compared with the current LTE network, which may be a promising mobility enhancement strategy for future 5G networks.

In this paper, we present performance analysis for underlay cognitive decode-and-forward relay networks with the Nth best relay selection scheme over Nakagami-m fading channels. Both the maximum tolerated interference power constraint and the maximum transmit power limit are considered. Specifically, exact and asymptotic closed-form expressions are derived for the outage probability of the secondary system with the Nth best relay selection scheme. The selection probability of the Nth best relay under limited feedback is discussed. In addition, we also obtain the closed-form expression for the ergodic capacity of the secondary system with a single relay. These expressions facilitate in effectively evaluating the network performance in key operation parameters and in optimizing system parameters. The theoretical derivations are extensively validated through Monte Carlo simulations. Both theoretical and simulation results show that the fading severity of the secondary transmission links has more impact on the outage performance and the capacity than that of the interference links does. Through asymptotic analysis, we show that the diversity order for the Nth best relay selection scheme is min(m1, m3) × (M - N) + m3, where M denotes the number of cognitive relays, and m1and m3represent the fading severity parameters of the first-hop transmission link and the second-hop transmission link, respectively.

To decrease the training overhead and improve the channel estimation accuracy in uplink cloud radio access networks (C-RANs), a superimposed-segment training design is proposed. The core idea of the proposal is that each mobile station superimposes a periodic training sequence on the data signal, and each remote radio head prepends a separate pilot to the received signal before forwarding it to the centralized base band unit pool. Moreover, a complex-exponential basis-expansion-model based channel estimation algorithm to maximize a posteriori probability is developed. Simulation results show that the proposed channel estimation algorithm can effectively decrease the estimation mean square error and increase the average effective signal-to-noise ratio (AESNR) in C-RANs.

In this paper, the channel estimation in uplink multiple access relay networks (MARNs) with analog network coding protocol has been researched. We apply the superimposed training (ST) scheme where each relay puts a separate training sequence on the top of the received one before forwarding to destination, and design a maximum likelihood based channel estimation algorithm for the composite source-relay-destination and individual relay-destination links. The optimal training sequences as well as the superimposed training power are also derived in closed forms. To make our study more complete, the channel estimation in the time-selective fading environment is further considered, and a correlation-based channel estimation (CBCE) algorithm is developed by taking advantage of time-domain channel autocorrelation nature. Simulation results show that the presented ST scheme can effectively improve the performance of multi-user detection in MARNs, and the proposed CBCE algorithm significantly outperforms the existing channel estimation methods.

This paper studies optimal resource allocation for multiple network-coded two-way relay in orthogonal frequency division multiplexing systems. All the two-way relay nodes adopt amplify-and-forward and operate with analog network coding protocol. A joint optimization problem considering power allocation, relay selection, and subcarrier pairing to maximize the sum capacity under individual power constraints at each transmitter or total network power constraint is first formulated. By applying dual method, we provide a unified optimization framework to solve this problem. With this framework, we further propose three low-complexity suboptimal algorithms. The complexity of the proposed optimal resource allocation ORA algorithm and three suboptimal algorithms are analyzed, and it is shown that the complexity of ORA is only a polynomial function of the number of subcarriers and relay nodes under both individual and total power constraints. Simulation results demonstrate that the proposed ORA scheme yields substantial performance improvement over a baseline scheme, and suboptimal algorithms can achieve a trade-off between performance and complexity. The results also indicate that with the same total network transmit power, the performance of ORA under total power constraint can outperform that under individual power constraints. Copyright © 2012 John Wiley & Sons, Ltd.

Spectrum sharing for cognitive two-way relaying is considered in this paper. A secondary relay is used to assist two-way communications between two primary users, and as a return, the secondary relay is allowed to transmit its own secondary signal by using some of the licensed primary spectrum. Three different spectrum sharing strategies are studied in this paper. In the baseline superposition coding (SC) strategy, the relay superimposes its secondary signal on the relayed primary signals in the same phase, and in the SC strategy with secondary interference cancellation (SC-SIC), the interference from the superimposed secondary signal on the primary signals can be removed; whereas in the time division (TD) strategy, the relay uses two distinct phases to transmit the relayed primary signals and its own secondary signal. Therefore, relay power or transmission time is treated as the shared resource and needs to be allocated between primary and secondary transmissions in the three strategies. We develop resource allocation results which can minimize outage probability of the secondary signal, and meanwhile, can satisfy data rate targets of the two primary users. Our results show that, although the SC-SIC strategy requires the least shared resource to achieve the data rate target for primary users, the TD strategy can provide the best performance for secondary transmission because it can completely avoid mutual interference between primary and secondary signals.

In this paper, we derive an effective SINR mapping algorithm based on Mutual Information (MI) Effective SINR Metric (ESM) model for 256QAM modulation system. Since recently 256QAM modulation is proposed in 3GPP LTE-A Rel.12 and IEEE 802.11ac standard, the design of Link-to-System (L2S) interface for 256QAM needs to be considered. Based on the Log Likelihood Ratio (LLR) receiver model, we derive the LLR probability density function (PDF) of each bit in the 256QAM modulation constellation, and approximate them as mixture Gaussian distributions. Then based on the MI ESM model definition, we compute the MI function of 256QAM by Monte Carlo integration, which can be used in the L2S interface of LTE-A or other 256QAM modulation based system. Numerical results demonstrate the accuracy of this model.

Cognitive two-way relaying is studied in this paper. A secondary relay is used to assist bidirectional communication between a pair of primary users. As a return, the secondary relay is allowed to transmit its own secondary signal on the licensed primary spectrum. For this purpose, superposition coding is employed at the relay to superimpose the secondary signal on the primary signals. Three typical cognitive two-way relaying strategies are considered in this paper, namely, amplify-andforward (AF), XOR- based decode-and-forward (DF-XOR) and superposition based DF (DF-SUP). Outage probabilities of the two primary users under these three strategies are derived for Rayleigh fading channels. Their performances are compared with direct transmission and another recently proposed cognitive two-way relaying strategy which enables interference cancelation of the secondary signal at the primary users. Our results show that a major portion of relay power has to be allocated for relaying primary signals because the superimposed secondary signal always plays as an interference to the primary signals. Finally, we propose several potential solutions to suppress this interference to enhance the performance of cognitive two-way relaying.

In this paper, we study a cognitive two-way relay network in which orthogonal frequency division multiplexing (OFDM) technique is adopted within the secondary system and a pair of secondary source nodes communicate with each other through a relay node by using amplify-and-forward two-way relaying strategy. We propose an optimal power allocation scheme to maximize the smaller data rate of the secondary users while satisfying both individual node power and aggregation interference constraints. We decompose the optimization problem into two subproblems and solve them by using dual decomposition approach. Furthermore, we propose a distributed power allocation algorithm. Finally, numerical simulations and comparisons are presented to illustrate the performance of the proposed scheme.

This paper analyzes a spectrum access scheme based on region division for Device-to-Device (D2D) communication underlaying cellular networks with outage constraint for cellular communication. The D2D pairs will access the spectrum by sharing the cellular uplink (UL) frequency resources in the networks. By utilizing stochastic geometry, D2D accessing the frequency spectrum can be modeled as the probability that the cellular user (CeUE) SINR is below an appropriate threshold. And the constraint of the probability appears as a transcendental equality, so we figure out the solution with the help of Lambert W function and obtain the closed-form solution of the region division in the whole cell when the cellular location are determined. Then in the simulation, we analyze the relationship between system capacity and key parameters including the CeUE location, the D2D density and D2D output power in detail. The results show that the proposed scheme can make the D2D pairs access the frequency spectrum in the networks effectively.

In underlay cognitive radio networks, imperfect channel knowledge will have an adverse effect on the performance of both the primary users (PU) and the secondary users (SU) owing to the interference power constraint of PU. This paper investigates the performance of a cognitive relay network (CRN) with imperfect channel state information (CSI) of the interference links over Nakagami-m fading channels. Interference probability is defined to characterize the interference caused by SU to PU due to CSI imperfection. Closed-form expressions for both the interference probability of the primary user and the outage probability of the secondary system are derived and validated by simulations. It is proved that the interference probability of the primary user is always 0.5 under the condition of imperfect CSI when no power control mechanism is adopted. The effects of CSI imperfection, channel fading severity, interference probability of PU and transmit power of PU on the outage performance of the secondary system are also analyzed.

This study investigates the security of the two‐way relaying system with untrusty relay nodes. Cooperative jamming schemes are considered for bi‐directional secrecy communications. The transmit power of each source node is divided into two parts corresponding to the user and jamming signals, respectively. Two different assumptions of the jamming signals are considered. When the jamming signals are a priori known at the two source nodes, closed‐form power allocation expressions at two source nodes are derived. Under the assumption of unknown jamming signals, it is proven that the cooperative jamming is useless for the system secrecy capacity, because that all the power should be allocated to the user signals at each source node. Relay selection is also investigated based on the analysis of cooperative jamming. Simulation results are presented to compare the system secrecy capacities under the two jamming signal assumptions.

This study comprehensively investigates the performance of the downlink massive multiple‐input multiple‐output (MIMO) system with channel state information (CSI) delay, when the base station serves multiple user terminals (UTs) taking advantage of maximum ratio transmission precoding. Through the characteristic analysis of the received signal‐to‐interference‐plus‐noise ratio at UT, the tight lower bound of average area spectrum efficiency (SE) and its asymptotic bound with the infinite number of UTs are deduced, respectively. Based on the asymptotic bound and the realistic power consumption model consisting of both radiated power and circuit power, the trade‐off between SE and energy efficiency (EE) is developed, and the optimal EE with respect to SE is attained concisely. Moreover, the approximate expressions of both outage probability and bit error ratio (BER) are derived when the massive MIMO system works at its interference limited region. All theoretical results coincide to numerical results, and they show that deploying more transmission antennas will be helpful to improve SE, EE and reliability simultaneously; SE will be enhanced; however, the reliability, including both outage probability and BER, will be worsened by multiplexing more UTs; enlarging CSI delay can extensively deteriorate SE, EE and reliability.

Large-scale user behavior can be used as the guidance for deployment, configuration, and service control in heterogeneous cellular networks (HCNs). However, in wireless networks, large-scale user behavior (in terms of traffic fluctuation in spatial domain) follows inhomogeneous distribution, which brings enormous challenges to energy-efficient design of HCNs. In this paper, the heterogeneity of large-scale user behavior is quantitatively characterized and exploited to study the energy efficiency (EE) in HCNs. An optimization problem is formulated for energy-efficient two-tier deployment and configuration, where the base station (BS) density, BS transmit power, BS static power, and quality of service are taken into account. We present closed-form formulas that establish the quantitative relationship between large-scale user behavior and energy-efficient HCN configuration. These results can be used to determine BS density and BS transmit power with the objective of achieving optimal EE. Furthermore, we present three energy-efficient control strategies of micro BSs, including micro BS sleep control, coverage expansion control, and coverage shrinking control. Simulation results validate our theoretical analysis and demonstrate that the proposed control strategies can potentially lead to significant power savings.

Wireless network coding can significantly improve the spectrum efficiency for relaying transmission when receivers can acquire accurate channel state information (CSI). In this paper, the channel estimation problem for two-way relaying channels is considered where two sources exchange information through an amplify-and-forward relay employing analog network coding protocol. By taking advantage of the apriori information of wireless channels to further improve channel estimation accuracy, the maximum a posteriori (MAP) based estimation schemes are developed to estimate the composite source-source channel coefficients and the amplitude of individual source-relay channels with apriori knowledge of channel distribution information (CDI). Variations of MAP estimation algorithms are also developed for systems under practical constraints where channel CDI needs to be estimated. In particular, scale MAP estimator as well as a long term estimation algorithm is developed to effectively control the negative impact of CDI estimation error on MAP estimation performance. The simulation results show that the MAP based estimation strategies consistently outperform maximum likelihood estimation methods in the measure of mean square error, thus establishes the advantage of presented MAP based schemes.

A resource allocation scheme involving several Device-to-Device (D2D) multicast groups underlaying OFDMA-based systems is proposed in this paper. In order to guarantee Quality of service (QoS) of cellular users (CeUEs), we define the signal-to-interference-pulse noise ratio (SINR) threshold value for CeUEs. Meanwhile, the minimum throughput of a single D2D multicast group is predetermined to maintain fairness of each D2D multicast group. Since the subcarrier assignment and power allocation are a joint optimization problem with complex calculation, the proposed scheme is divided into two steps. First, subcarriers are allocated under the premise of ensuring the minimum throughput of the D2D multicast groups and the QoS of CeUEs. Then by applying an approximation form of Shannon capacity, the power allocation problem can be solved by convex optimization. Simulation results show that the proposed scheme improves sum-throughput significantly as well as fairness. Besides, the sum-throughput increases with the increasing number of D2D multicast groups.

Cognitive relay networks have been studied for the advantages of improving the throughput of secondary users. Relay location and power allocation are the key issues in cognitive relay networks, which impact on the system performance. In this paper, we analyze the problem of optimal relay location and power allocation in cognitive relay networks. Firstly, we deduce an ergodic capacity formula for the secondary users reuse the resource of one primary user in Rayleigh-fading channels, and the formula is used in the terms of high signal-to-noise ratio (SNR) and high interference-to-noise ratio (INR). Then, the expressions for optimal relay location and power allocation are derived from the deduced formula when the distances among primary users and secondary users are known. At last, an ergodic algorithm for finding the results is given. The simulation proves the proposed ergodic capacity formula is correct. The ergodic algorithm is also verified by simulation, and the optimal relay location and power can be also determined.

This paper analyzes the optimal power and density allocation for D2D (Device-to-Device) communication in heterogeneous networks on multi-bands with target of maximizing D2D achievable transmission capacity. The heterogeneous networks contain one or several cellular systems, and D2D communication shares uplink resources with them. By utilizing stochastic geometry, the problem is formed as sum capacity optimization for D2D network with constraints that guarantee outage probabilities of both cellular and D2D transmissions. The original problem is non- convex but we find the D2D transmission capacity has a remarkable property: it is sectional continuous with limited discontinuous point in the feasible region of power and density allocation and the maximum capacity is reached on the critical point. Based on this, we propose a algorithm as follows: first we figure out all of critical points as a candidate set and then obtain the optimal solution from them. The numerical results demonstrate the effectiveness of the algorithm and it shows that optimal parameters of D2D transmission is affected by outage constraints as well as the interference from cellular systems.

In this paper, we investigate the problem of utilizing the Kalman Filter to reconstruct signals with sparse frequency content under a streaming CS framework. We develop a Gaussian Markov model of the sparse streaming signal under the Analog-to-Information Converter (AIC) hardware structure and propose an adaptive Kalman Filter for the reconstruction. Different from existing CS schemes for streaming signals, we exploit the correlations between the signals of two consecutive observation windows to model the process in the state transition form so that the Kalman Filter can be incorporated to obtain the convergent estimation of the input streaming signal. Simulation experiments show the feasibility of the proposed model and demonstrate the superior performance of the proposed algorithms.

This paper analyzes the optimal density and power allocation for D2D (Device-to-Device) communication in heterogeneous networks on multi-bands with target of maximizing D2D transmission capacity. The heterogeneous networks contain one or several cellular systems, and D2D communication shares uplink resources with them. By utilizing stochastic geometry, it is formed as a sum capacity optimization problem for D2D network with constraints that guarantee outage probabilities of both cellular and D2D transmissions.Since the original problem is non-convex, we divide the proof into two steps: first we prove the power allocation problem is convex when the D2D density is fixed, which can be solved by lagrangian method; then we prove that the optimal D2D density exists in a semi- closed interval.We propose a linear searching algorithm based on the former conclusions:with discretizing the interval of D2D density, a series of solutions can be obtained by solving the optimization problem of each D2D density; hence the global optimal capacity can be selected from them.The simulation results demonstrate the effectiveness of the proposed algorithm and it also shows that optimal parameters of D2D transmission is affected by outage constraints as well as the interference from cellular systems.

Cooperative spectrum sharing is an effective way to improve energy and spectrum efficiency of wireless communication network. In this paper, we consider a power constrained cooperative spectrum sharing network and model it as a labor-consumption market. The secondary users (SUs) offer labor, i.e., power consumed for relaying the primary user's (PU's) traffic. In order to encourage SUs to work, PU admits SUs' consumption, i.e., the licensed band accessed by SUs for their own traffics. We formulate the problem as an auction in a labor-consumption market repeatedly played with multiple SUs for power and time trading in cooperative spectrum sharing. Based on this model, our results show that the performances of the PU and the network are greatly improved by cooperative spectrum sharing. Moreover, the selection of SUs depends on not only their channel conditions but also their transmission needs.

The security of the two-way relaying system with an eavesdropper is investigated in this paper. A cooperative jamming and power allocation scheme is proposed to enhance the system secrecy capacity. Both user and pre-defined jamming signals are transmitted by each source node simultaneously. The optimum power allocation between the user and jamming signals at each source node is derived. Our analytical results suggest that the proposed cooperative jamming scheme improves on the system secrecy capacity, especially when the channel gains of the two source-relay links are of large difference. Simulation results in close agreement with analytical results clearly demonstrate the advantage of the proposed cooperative jamming scheme.

This paper proposes the problem that the direct communication between two D2D UEs is impossible since the outage probability of D2D communication goes beyond the threshold defined by system. The problem is solved by applying relay to Device-to-Device (D2D) communication, which is defined as D2D communication with relay mode. In this communication mode, relay is selected from idle Cellular User Equipments (CeUEs), and both of two hops in it are D2D communication. In this paper, we provide the criteria of employing this communication mode. First we derive out the interference constrained precondition for applying the mode of D2D communication with relay based on outage probabilities analysis, and then the criterion of employing D2D communication with relay mode is proposed by comparing the sum-capacity of this mode with that of cellular communication mode on the basis of the optimal relay selection. By simulating, we compare the occurrence probabilities of the modes of D2D communication, cellular communication and D2D communication with relay. The numerical results also reveal the D2D communication with relay mode can improve the average sum-capacity in contrast with cellular communication mode based on the proposed criteria.

Power allocation for orthogonal frequency division multiplexing (OFDM) based two-way relay link in cognitive relay networks is discussed in this paper. Two secondary source nodes exchange their information through a secondary relay node by using amplify-and-forward two-way relaying strategy. The goal of power allocation is to maximize the sum data rate of the secondary system subject to the constraint that the aggregation interference of the secondary system on the primary system does not exceed the given threshold. In addition, individual node power constraint is applied for both secondary source nodes and the secondary relay node. We solve the optimization problem by using dual decomposition approach, and further propose a distributed power allocation algorithm. Numerical results demonstrate the advantage of the proposed algorithm over uniform power allocation. Besides, power-constrained as well as interference-constrained regions are shown in our numerical experiments.

The security of the three-phase two-way relaying system with an eavesdropper is investigated in this paper. A cooperative jamming and power allocation scheme is proposed to enhance the system secrecy capacity. When a source node transmits user signals to the relay node, the other source node interferes the relay node with pre-defined jamming signals simultaneously. Optimum power allocation between the user and jamming signals at each source node is analyzed. Our analytical results suggest that the proposed cooperative jamming scheme improves on the system secrecy capacity, especially when the channel gains of the two source-relay links are of large difference. Simulation results in close agreement with analytical results clearly demonstrate the advantage of the proposed cooperative jamming scheme.

In this paper, we investigate a two-way relay networks consisted of two sources, multiple cooperative relays, and an eavesdropper. To guarantee the secure communication, a null space beamforming strategy is applied, where the relay beamforming vector is design to lie in the null space of the equivalent channel from two sources to the eavesdropper. Aiming to minimize the total transmit power under individual secrecy rate constraint at two sources, an alternating iteration method is proposed to calculate the relay beamforming vector as well as sources' transmit power. For relay beamforming vector optimization subproblem, two different approaches, semi-definite programming (SDP) relaxation and sequential quadratic programming (SQP) method, are proposed. Subproblem with two sources' transmit power optimization is formulated as a single variable problem and solved by Newton method with line search effectively. Through the numerical simulations, we verify the effectiveness of proposed algorithm. Moreover, with computational complexity analysis, we show that the SQP method has lower complexity than SDP, and further verify it in terms of executing time.

In this paper, a network coding broadcast (NC-BC) scheme is proposed to improve the spectral efficiency for multiple-input and multiple-output (MIMO) transmissions. Particularly by network coding the base station broadcast message with each user message respectively, NC-BC can save the radio resource allocated for base station broadcasting, which is necessary in conventional time division-based scheme. Moreover, the iterative precoding design for NC-BC is studied for approaching the optimal performance, and the sub-optimal precoding design with low complexity is also provided. The simulation results show that the proposed NC-BC scheme with precoding optimization can further improve the system transmission performance.

This study concerns the approximate distribution of the random variable log 2 ( A + χ 2 ) and its applications in the performance analysis of communication systems where A is 0 or 1 and χ 2 a chi‐square distributed random variable. The authors prove that log 2 ( A + χ 2 ) is approximately Gaussian distributed and derive the expressions of the mean and variance of the approximate distribution. The approximate Gaussian distribution provides a new way to simplify the derivation of performance metrics and obtain analytical results. Then the authors utilise the approximate results in two applications, which are the approximation of the Gaussian Q ‐function and capacity analysis, respectively. For one thing, the approximate distribution can be explored to deduce a new approximate equivalent expression of the Q ‐function on the basis of which an accurate approximation of the Gaussian Q ‐function can be developed. For another, the approximate Gaussian distribution provides an intuitive approach to analyse the channel capacity of Rayleigh‐fading multiple antenna systems. The approximate statistical distributions of the channel capacities of orthogonal space‐time block codes, single‐input multiple‐output, multiple‐input single‐output, transmit antenna selection with maximal‐ratio combining and multiple‐input multiple‐output systems are presented. The applicability of the approximate distribution can be demonstrated through simulation results in both applications.

The secrecy capacity of relay communications is investigated in this paper, where an eavesdropper is present. Distributed precoding through multiple relay nodes can be used to enhance the received signal power at the destination node and to mitigate the signal leakage to the eavesdropper, simultaneously. Due to individual power constraints at relay nodes, the distributed precoding scalar at each relay node is equivalent to a distributed precoding angle. An iterative algorithm is proposed to find the suboptimum distributed precoding angles at all the relay nodes, where the channel state information (CSI) sharing overhead among the relay nodes can also be substantially reduced. Each relay node receives the equivalent CSI from its preceding relay node, computes its distributed precoding angle, and updates the equivalent CSI for the next relay node. Compared with the simple decode-and-forward relaying protocol with random distributed precoding, the proposed iterative distributed precoding algorithm is able to further improve on the secrecy capacity of the multirelay wiretap system with an acceptable CSI sharing overhead.

ABSTRACT Outage performance is analyzed for opportunistic decode‐and‐forward cooperative networks employing orthogonal space–time block codes. The closed‐form expressions of diversity order and the end‐to‐end outage probability at high signal‐to‐noise ratio regime are derived for arbitrary relay number (K) and antenna configuration (N antennas at the source and each relay, ND antennas at the destination) under independent but not necessarily identical Rayleigh fading channels. The analysis is carried out in terms of the availability of the direct link between the source and the destination. It is demonstrated that the diversity order is min{N, ND} ⋅ KN if the direct link is blocked, and if the direct link is available, the diversity order becomes min{N, ND} ⋅ KN + NND. Simulation and numerical results verify the analysis well. Copyright © 2011 John Wiley & Sons, Ltd.

Joint scheduling and resource allocation in uplink orthogonal frequency division multiplexing (OFDM) systems is complicated, and even gets intractable with large subcarrier and user number. This paper investigates the resource allocation for OFDM-based multi-user multiple-access relay channels (MARC) with network coding. We formulate a joint optimization problem considering source pairing, subcarrier assignment, subcarrier pairing and power allocation to maximize the sum-rate under per-user power constraint. The problem is addressed in polynomial time by optimizing three separate subproblems, and afterwards three low-complexity suboptimal algorithms are further proposed. The simulation results demonstrate performance gain of the proposed algorithms versus per-node transmit power and source nodes number, respectively.

The widespread requirement of multimedia application, especially Video-on-Demand (VoD), has lead to rapidly rising energy consumption. User behavior brings a great effect on the energy consumption of traffic transmissions. In wireless networks user behavior in terms of user request frequency follows power-law distribution, which indicates that some media streams are requested more frequently than the others. There-fore, exploiting multicast transmission technique for multimedia can significantly reduce the transmission power consumption. However, due to user requests occurs at different moment, in multicast transmission a subsequent user will miss the pervious part of the media stream that has been already transmitted for the early-arriving user. In order to guarantee the quality of service (QoS), the transmitter can deliver the missing fraction of the media stream through initiating separate patching stream. In this paper, we propose an energy efficient multicast scheme with patching stream which enable the transmitter to deliver both patching stream through unicast transmission and shared stream through multicast transmission with dynamic bandwidth allocation. Closed-form formula for power consumption of this scheme is established, in which the impact of the time window length, the user requests distribution are considered. We also derive a tight upper bound on the minimum power consumption under the optimal time window length. Compared to the traditional unicast transmission power consumption which grows like O(eλ), power consumption in the proposed scheme grows like O(e√λ), where λ represents the user request rate. Simulation results validate the theoretical analysis and demonstrate that our scheme can lead to 73% and 20% power deduction compared with the traditional unicast transmission scheme and traditional patching multicast transmission scheme.

Spectrum sharing between primary and secondary systems in cognitive two-way relay networks is discussed in this paper. A two-phase spectrum sharing protocol is proposed, in which a secondary (cognitive) user acts as the relay to assist the bidirectional primary transmission. Analog network coding (ANC) is employed for two-way relaying between the two primary users, and spectrum sharing is achieved by superimposing the secondary signal on the network-coded primary signals at the secondary relay. We analytically derive the outage probability of the primary users under our proposed two-phase protocol, and identify the spectrum sharing regions within which the spectrum sharing protocol can achieve higher (or at least equal) outage performance for the primary users than direct transmission without spectrum sharing. Results show that our proposed two-phase spectrum sharing protocol can outperform another recently proposed three-phase protocol which is based on decode-and-forward (DF) network coding operation.

This paper analyzes the optimal D2D user allocation over multi-bands in the heterogeneous networks. The heterogeneous networks contain one or several cellular systems and D2D communication shares uplink resource with them. By allocating D2D users on different bands, it can reduce the interference between D2D and cellular systems and improve D2D transmission capacity at the same time. Through utilizing stochastic geometry, the problem is formed as sum D2D transmission capacity on each band with constraints that guarantee outage probilities of both cellular and D2D transmission. The primal problem is first proved to be convex and then solved by constructing Lagrange function and KKT conditions. The optimal D2D user densities over multi-bands are derived and we propose a D2D scheduling algorithm base on this conclusion for the dynamic D2D access process. Simulation results show the superiority of optimal user allocation over average allocation method.

This paper analyzes the underlay and overlay mode selection of Device-to-Device (D2D) communication in the LTE-Advanced single-cell scenario. The two cases that the cell contains relay node or not are considered, and the study focuses on the location relationship between cellular UE and D2D UE. Our evaluation shows that whether D2D communication can reuse the cellular uplink resource or not is affected by the system parameters. Specifically the underlay mode is preferred when the cellular user is closer to the BS or relay node than the D2D user. The simulations show that the introduction of relay node enables D2D pairs to have more chances to share the resources with cellular user in the underlay mode.

Conventional study of green communication mainly focuses on the transmission power adjustment to minimize the total power consumption while guaranteeing a target system capacity. However, for the energy efficient design the dynamic transmission mode is an effective way to reduce total transmission power in multiuser networks. In this paper, an energy efficient traffic transmission scheme based on user convergence behavior (UCB) is proposed which characterizes the phenomenon of similar/convergent users' traffic requests during a certain timewindow. First a system model is built to study the relations of user convergence, length of time-window and transmission power consumption. Specifically in each time-window the transmitter analyzes the similarity of users' traffic requests and the similar traffics will be transmitted by multicast mode while the other traffics will be transmitted using unicast mode. To analyze the performance of our scheme, we establish a simple stochastic model in which locations and density of users, wireless channel conditions and transmitting mode are considered. Analytical results, such as power reduction ratio and energy efficiency (EE) of the proposed scheme, are developed, from which the quantitative relationship between UCB and the energy conservation can be obtained. Simulation results validate the theoretical analysis and demonstrate that our scheme can potentially lead to 35% power consumption deduction compared with the conventional transmission scheme.

Distributed antenna systems (DAS) are deployed not only for enhancing coverage, but also for reducing the transmission power consumption, which have emerged as the promising candidate for energy-efficient wireless communications. In this paper, orthogonal and co-channel resource allocation schemes considering energy efficiency in single-cell DAS are analyzed. For orthogonal resource allocation scheme, the interference is avoided by sacrificing the available resources. While for the co-channel resource scheme, the spectrum efficiency improves under the expense of increasing the interference. The close-form expressions of spectrum and energy efficiency of these two schemes are derived, by which the impact of transmission power on spectrum and energy efficiency are theoretically compared. Both the theoretical analysis and simulation results indicate that increasing transmission power beyond a reasonable level will seriously impair energy efficiency. Furthermore, the DAS with co-channel resource allocation scheme is recommended to utilize in the green communication systems.

In this paper, we propose admission control and power optimization algorithms for Device-to-Device (D2D) communication which share uplink resources with cellular system in underlay mode. In the presence of quality of service (QoS) protection (both for D2D and cellular users) and transmit power limit, we propose a set-based admission control (SAC) algorithm in which some novel strategies of sets adjustment are presented to handle the violations of constraints. By using SAC, we get a set which contains admitted D2D links (DLs) as many as possible, and other DLs are rejected, but the D2D system capacity is not optimal. Then, we propose a distributed power optimization (DPO) algorithm to maximize the D2D system capacity after implementation of SAC. In DPO, QoS protection is also provided, each DL uses gradient descent method to update its transmit power, and DLs only need to exchange “price” messages which indicate the effect of interference. Through the numerical results, we demonstrate the feasibility and satisfying performance of proposed algorithms compared to traditional algorithms.

In this paper, the early-termination fixed-complexity sphere detector (ET-FSD) that is a channel-adaptive version of FSD, is developed to exploit scale effects for the multiple-antenna system which has to detect signals of multiple users under the constraint of sum complexity (e.g., the base-station systems always encounter the run-time limit of signal detection of all the users). In order to apply the concept of scale effects in microeconomics to the study of ET-FSD, the corresponding mathematic model primarily based on the large deviation principle is established. The key evidence that tells the existence of scale effects in ET-FSD is presented instead of the complete proof due to the space limitation. We also argue that within multiple-user systems the scale effects can be utilized to realize ET-FSD that has both the optimal performance in the point view of diversity order and the polynomial time unit complexity in the worst-case sense (one can think of unit complexity as the complexity per user in multiple-user scenario). Finally, we provide the numerical results to support the theoretical analysis.

In this paper, physical-layer network coding with spatial modulation in two-way relaying channels is studied. Two multi-antenna source nodes exchange information via a denoise-and-forward (DNF) relay node, and space shift keying modulation is employed in both source nodes and relay. The error performance in terms of average symbol error probability is evaluated. To further enhance the transmission quality, the denoise mapping operator is concerned to be optimized, and a graph-based approach is adopted to make the problem more tractable. Effective sub-optimal algorithm based on dichotomizing method is presented to reduce the solving complexity. Simulation results in terms of symbol error rate and throughput show that the DNF protocol with optimized mapper outperforms that with random or no mapper.

Geometry-based optimal power control was proposed in [14] to transform the power-control problem to a new geometrical problem on the position relationship between a line and some points. This scheme provides a novel visual perspective and lowers the complexity of optimization. We generalize this scheme to a larger class of power-control optimization problems so as to maximize the network utility with multiple average and peak power constraints in wireless networks. To facilitate the handling of the geometrical model, we define a subset of geometrical models with specified characteristics, called a regular geometrical model, and derive the type of power-control problems eligible for the regular geometrical model. For such a type of problems, two strategies are proposed for the construction of the regular geometrical model. Utilizing geometrical properties, we propose a novel geometry-based optimization scheme for the general power-control problem. Its computational complexity is significantly lower than the conventional algorithms. We also provide a further discussion on irregular geometrical model cases. Finally, we provide two examples of deploying the proposed geometry-based power-control scheme.

Carrier aggregation (CA) has been proposed within 3GPP to aggregate multiple component carriers (CCs) in LTE-Advanced system to achieve higher peak data rate. In this paper, we propose CA between FDD and TDD carriers in order to utilize FDD and TDD spectrums more efficiently. By comparing the differences in control channel between LTE FDD and TDD specifications, three problems in the case of CA between FDD and TDD carriers are identified, and we then propose the respective solutions and analyze their pros and cons. It is shown that CA between FDD and TDD carriers can provide system flexibility and performance benefits for the operators which own both FDD and TDD spectrums.

This paper investigates optimal resource allocation in orthogonal frequency division multiplexing (OFDM) based multiple two-way relay systems operating with analog network coding (ANC) protocol. We formulate a joint optimization problem considering power allocation, relay selection and subcarrier paring to maximize the sum capacity under individual power constraints on each node. By applying dual method, an unified optimization framework is provided and the problem is solved efficiently. Based on this framework, we further propose three suboptimal algorithms. The complexity of optimal algorithm (ORA) and three suboptimal algorithms are evaluated, and the analysis results show that the complexity of ORA is only a polynomial function of the number of subcarriers and relay nodes. Simulation results demonstrate that the proposed ORA scheme yields substantial performance improvement over baseline scheme, and suboptimal algorithms can achieve a trade off between performance and complexity.

An improved high-spectral-efficiency coding-rotated modulation (CRM)-iterative demodulation/decoding (ID) scheme in the orthogonal frequency division multiplexing (OFDM) system is proposed. For the rotated QAM, it unveils the optimum rotation matrix depending on the modulation order, the code rate and the receiver scheme (ID or non-ID). The suboptimal solution of the rotation angle is proposed, and a novel two-dimensional time/frequency component interleaver is also put forward to make the best use of the modulation diversity, time diversity and frequency diversity. Besides, code-matched four-dimensional QAM rotation matrices and the corresponding time/frequency component interleaver are proposed to improve the error performance furthermore. The analysis of extrinsic information transfer chart (EXIT) chart is also given to explain the convergence characteristic. Simulation results have turned out that this new scheme can significantly outperform the conventional BICM scheme.

Cognitive radio (CR) allows unlicensed users to access the licensed spectrum opportunistically (i.e., when the spectrum is left unused by the licensed users) to enhance the spectrum utilization efficiency. In this paper, the problem of allocating resources (channels and transmission power) in multihop CR networks is modeled as a multicommodity flow problem with the dynamic link capacity resulting from dynamic resource allocation, which is in sharp contrast with existing flow-control approaches that assume fixed link capacity. Based on queue-balancing network flow control that is ideally suited for handling dynamically changing spectrum availability in CR networks, we propose a distributed scheme (installed and operational in each node) for optimal resource allocation without exchanging spectrum dynamics information between remote nodes. Considering the power masks, each node makes resource-allocation decisions based on current or past local information from neighboring nodes to satisfy the throughput requirement of each flow. Parameters of these proposed schemes are configured to maintain the network stability. The performance of the proposed scheme for both asynchronous and synchronous scenarios is analyzed comparatively. Both cases of sufficient and insufficient network capacity are considered.

There has been a growing interest in analog network coding, which can improve system throughput and spectrum efficiency significantly in wireless systems. Two-way relay scenario is considered in this paper, where the base station (BS) and the relay are both equipped with multiple antennas, and each of K user equipments (UEs) in the cell has a single antenna. An advanced multi-user scheduling scheme is proposed for the analog network coded two-way relay channel, where UEs and BS exchange information via the relay node during two time slots. Because each UE with single antenna has poor transmission and reception capability, the scheduling scheme is carefully designed to decrease multi-user interference and optimize beamforming gain from BS to relay. Analytical results of sum rate and outage probability have been developed to demonstrate that the multi-user diversity gain can be achieved by the proposed scheme. Meanwhile, the user fairness of the proposed scheme is on the same order as that of round robin (RR), and the computation complexity only increases linearly with the number of users in the serving cell. Monte-Carlo simulation is conducted to exhibit the performance gains from the proposed scheduling scheme. Results show that the proposed channel correlation based user selection scheme outperforms existing traditional scheduling schemes significantly, even when the cellular user payload is low.

ABSTRACT We consider the problem of optimal power allocation and optimal user selection in a layered multicast transmission over quasi‐static Rayleigh fading channels. A scheme based on superposition coding is proposed in which basic multicast streams and enhanced multicast streams are superimposed and transmitted by a base station, while users with worse channel conditions can only decode basic multicast streams, and users with better channel conditions can decode both basic and enhanced multicast streams. In this paper, subject to fixed user selection ratios, the optimal power allocation for each stream that maximizes average throughput is investigated, and the impact of power allocation on average outage probability is discussed. Finally, subject to fixed transmit power and power allocation, the optimal user selection ratio for enhanced multicast streams is also studied. Numerical results show that the optimized layered multicast scheme outperforms the conventional multicast scheme in terms of average throughput. Copyright © 2010 John Wiley & Sons, Ltd.

We consider a multi-pair two-way relay (TWR) network where the multi-antenna users of each pair exchange information via a multi-antenna relay. The interesting challenge is how to deal with the inter- user interference and explore the potential of multiple antennas concurrently. Beamforming methods in previous works are based on the criteria of zero forcing (ZF) and minimum mean square error (MMSE) to mitigate the inter-user interference. However, since the user already knows its own information, it is unnecessary to mitigate the intra-pair interference at the relay. In this paper, we propose a coordinated eigen beamforming (CEB) scheme, which maximizes the effective channel gain of each user in the sub-space nulling the inter-pair interference. The CEB scheme is implemented with an iterative optimization algorithm with limited iterations. Additionally, the power loading scheme is adopted after convergence to guarantee fairness among users. Simulation results indicate our scheme achieves near full diversity order within the sub-space, outperforming pervious works.

In this paper, we consider a two-way asymmetric relaying channel with unmatched traffics from two sources. Aiming at maximizing the sum rate under a minimum rate constraint, we address the optimization problem (in terms of time and power allocation) for two decode-and-forward (DF) strategies, namely, the decode-and-forward with joint modulation (DF-JM) and the decode-and-forward with network-superposition coding (DF-NSC). Closed-form solutions under different relay settings are presented. Numerical results are provided to illustrate the performance gains due to the optimal resource allocation, as well as the achievable rate gaps between two different DF strategies.

In 3GPP LTE-Advanced networks deployed with type I relay nodes (RNs), resource partition is required to support in-band relaying. This paper focuses on how to partition system resources in order to attain improved fairness and efficiency. We first formulate the generalized proportional fair (GPF) resource allocation problem to provide fairness for all users served by the evolved node B (eNB) and its subordinate RNs. Assuming traditional proportional fair scheduling is executed independently at the eNB and each RN to achieve local fairness, we propose the proportional fair resource partition algorithm to tackle the GPF problem and ensure global fairness. Through system level simulations, the proposed algorithm is evaluated and compared with both non-relaying and relaying systems with the fixed resource partition approach. Simulation results demonstrate that the proposed algorithm can achieve a good trade-off between system throughput and fairness performance.

In this paper, a novel scheme of multiple-input multiple-output (MIMO) detector is proposed for base-station (BS) system that has to detect signals of multiple users, which is capable of exploiting the scale effects and thus named as the scale effects oriented MIMO detector. The scale effects is the feature that, the unit complexity of MIMO detector decreases as the number of users increases under certain condition while maintaining the full diversity. Through theoretic analysis of error probability, diversity order and complexity, as well as works of computer simulation, we demonstrate that the proposed MIMO detector has the scale effects.

In this paper a framework of analyzing the secrecy capacity of Raleigh fading multi-antenna system in presence of multiple eavesdroppers is presented. The multi-antenna system we concern adopts the transmit antenna selection with maximal-ratio combining (TAS/MRC) diversity scheme. We propose to make use of the closed-form approximations to analyze the secrecy capacity. The simulations validate the analytical results derived by the proposed framework.

To address the problems of high sampling rates, shadow fading and additive noise from the receiver, in this paper, a distributed compressed sampling (DCS) and centralized reconstruction approach which utilize the spatial diversity against fading channels is proposed. Unlike traditional centralized reconstruction, in this paper, we centralized recover the spectrums by exploiting the block-sparsity which is rather prevalent in multi-band signals. In DCS, first each CR samples the signals with a sub-Nyquist sampling rate independently, then the sampled data are uploaded to the fusion center (FC), finally FC reconstructs these data simultaneously. To exploit the block-sparsity, two new centralized recovery algorithms simultaneous block orthogonal matching pursuit (S-BOMP) and simultaneous binary tree based block orthogonal matching pursuit (S-BTBOMP) are developed. Simulation results show they outperform existing simultaneous recovery algorithms which don't take block-sparsity into consideration.

Due to the dense and self-deployment of home eNodeBs (HeNBs) in femtocells, serious inter-cell interference may arise without good coordination. To deal with it, a distributed interference coordination scheme for femtocells networks with carrier aggregation (CA) is proposed in this paper. Firstly, each femtocell operates on all the component carriers (CCs) of the network and gathers the information needed via local measurements. Then, based on the measurements, decisions of maintaining or releasing the component carrier are individually made by each femtocell on each component carrier. Simulation results validate the effectiveness of our proposed scheme in term of the signal to interference and noise ratio (SINR) and throughput.

To obtain better cooperative diversity on relay networks. A joint network and channel coding (JNCC) scheme based on turbo codes and corresponding iterative decoding strategy are proposed for uplink multiple-access relay channel (MARC) systems. The proposed scheme is considered by using different processing ways for different users and turbo network coding for the relay where only the extra redundancy is forwarded by the relay, designing iterative decoding strategy at destination to achieve the improvement of bit error rate (BER) performance. By doing this, a better error correction capability is embedded to the proposed JNCC scheme providing a better help to the destination when decoding different users original messages. Simulation results demonstrate that the proposed scheme substantially improves the BER performance to the referenced schemes in AWGN and Rayleigh fading channels respectively.

A new unequal-error-protected space-time block code (UEP-STBC) is designed in this paper for multimedia transmission systems deployed with multiple antennas. Traditionally, a space-time code is designed to support a single information stream aiming to achieve a point on the fundamental rate versus diversity tradeoff curve, while this proposed class of codes has the capability of transmitting different performed symbols from different layers within the same codeword. The UEP-STBC, whose symbols belong to different orthogonal layers without interference, is fit for the systems using scalable video coding (SVC) as the source coding. The design covers the cases of arbitrary number of transmit antennas. The simulation results demonstrate the performance advantage and coverage enhancement of the proposed codes in multimedia transmission over conventional codes.

This paper presents a novel Distributed Streaming Compressive Spectrum Sensing (DSCSS) algorithm for wide-band spectrum sensing under decentralized cognitive radio network (CRN) scenario. In contrary to traditional compressive sensing (CS) that only focuses on fixed-length signal's compressive sampling and reconstruction, DSCSS follows streaming CS framework, where Analog-to-Information Converter (AIC) is utilized to perform streaming signal acquisition below Nyquist sampling rate at individual cognitive radios (CR). Since the sparsity of wide-band spectrum is unavailable in practical situation, DSCSS alternatively estimates the sparsity and the true support set of the spectrum, and the estimated support set is marked and exchanged to the other CRs as a priori information, which are merged and utilized to obtain cooperative sensing gain. This process repeats to acquire performance promotion progressively until robust spectrum sensing results are achieved. Moreover, the low computational complexity makes DSCSS more suitable for on-line applications. Various simulations and comparisons are performed to show the efficiency of the proposed approach, the effectiveness of which is testified.

In this paper, the theoretical insight into Gaussian approximation of channel capacity for several classes of Rayleighfading multiple-antenna systems is presented. In particular, a theorem, which has not been developed by the former studies of Gaussian approximation, is introduced to these systems. Then guided by this theorem, a new approach of determining the approximate mean and variance for Gaussian approximation is proposed, which is simpler and more intuitive than the existed approach. The simulation results show the availability of such new approach.

In traditional compressive sampling approach, it's always assumed the sparsity of a signal is known. However, we always can't get this in Cognitive Radio (CR) network. This makes a great barrier to the practical usage of compressive sampling. This paper develops an Adaptive Compressive Sampling (ACS) approach for wideband signals. It doesn't need the sparsity as a priori knowledge. Also, once the sparsity changes, it can adaptively change the proper sampling rate through comparing the different results recovered by different sampling rates. When there is no difference between the results recovered by two different sampling rates, the smaller sampling rate of these two is the proper sampling rate to recover the original information of the signal exactly. Moreover, ACS can provide the unoccupied spectrum holes to Secondary Users (SU) in CR for dynamic spectrum access.

In this paper, we investigate a cooperative system consisting of one source-destination pair equipped with single antenna and L relays equipped with M antennas as wireless access points. We propose a new relay selection scheme for this system based on partial relay selection, where the best relay is selected according to the instantaneous and one-hop channel state information (CSI). We use maximal ratio combining (MRC) and maximal ratio transmitting (MRT) at relays to obtain the maximal achievable received signal-to-noise ratio (SNR). Close-form expressions for the outage probability and symbol error rate (SER) are derived. High SNR analysis is tightly approximated to explicitly characterize the diversity order and array gain. Monte Carlo simulations verify our analytical results. Results show that the diversity order increases with the antenna numbers at the selected relay according to M. For partial relay selection, two available relays are enough to get the array gain, and impacts of relay locations are also discussed in this paper.

Femtocell is a promising cost-effective technology to provide the hotspot coverage especially in buildings. Due to the high density of femtocells in urban environment, the need to reuse the scarce spectrum results in co-channel interference. In this paper, we propose a graph-based distributed scheme to manage radio resources efficiently among femtocells, achieving a good tradeoff between system throughput and user fairness. After the interference graph is generated, each femtocell first uses certain number of resources randomly. Then, femtocells may apply for more resources with the given probability. Our simulation results demonstrate the effectiveness of the proposed scheme in terms of throughput and fairness.

Joint processing algorithm of detection and decoding for linear block coded multiple-input multiple- output (MIMO) system is investigated in this paper. Iterative detection and decoding (IDD) algorithm, which is considered as the optimal approach for convolutional coded MIMO system, yet is not processing efficient enough for linear block coded MIMO system under given computational complexity. In this case, although list-type detection and list- type decoding are separately used to generate a list of candidates (hard information), only the associated soft information is calculated and passed. Motivated by the joint ML principle and list-type process, we propose a much simpler and more efficient method, named list detection and decoding (LDD) algorithm. LDD exploits the common nature of list-type process in IDD to generate a list of candidates (hard information) for decoding- and-decision instead of iterative processing in IDD. We show that LDD can achieve near-optimal performance while enabling a performance-complexity tradeoff with different list size. Furthermore, the fixed complexity is suitable for hardware implementation. Simulation results show that LDD outperforms IDD while having a lower decoding complexity.

In this paper, a novel non-saturation analytical model for enhanced distributed channel access (EDCA) in IEEE 802.11e wireless local area network (WLAN) is proposed. Unlike previous work focused on saturation conditions, this model uses Markov and M/M/1/K theories to predict MAC delay, service time, throughput and loss. Moreover, the EDCA technique resets the default contention window (CW) of stations statically after each successful transmission. The static behavior which can not adapt to the network state results in bad performance. Consequently, we introduce an enhancement scheme based on quality of experience (QoE) perceived by users to adjust CW adaptively. Instead of solely relying on technical parameters such as loss and delay, our scheme is based on QoE which contains the parameters inherently. Simulations validate this model and demonstrate better performance of our scheme compared with traditional EDCA regarding QoS parameters and user satisfaction.

Many research results show that in real world, networks are neither regular nor random but ones with the feature of scale-free characteristic. Applying this feature in telephone network, traffic behavior has been proved to have significant relationship with the user network. However, in a particular scenario, objective existence of user network cannot be changed and each user can only be occupied in one call, so the traffic behavior under this scenario is determined, which means no improvement strategies can be proposed. Based on this point, base station network is proposed: its relation can be changed by adding some new base stations; what's more, base station can support many calls simultaneously, then the limitation factor is subject to the number of capacity at each base station node, which can also be controlled. In this situation, some configurations can be proposed to improve the system performance. In this paper, we establish the base station network with weighted scale-free property. Through comparing with fully-connected base station network which was widely used in the previous model, we research on the effects of network relation on traffic behavior. Then a channel capacity distribution strategy is proposed to improve the system performance, which also verifies the advantage of base station network establishment.

This paper focuses on how to associate users with serving nodes in order to achieve improved fairness and efficiency for the cellular networks enhanced with multiple relay nodes (RNs). We first formulate the generalized proportional fair (GPF) problem with the aim of providing fairness for all users served by the evolved node B (eNB) and its subordinate RNs. Routing is incorporated into the GPF problem as part of the resource allocation strategy. Assuming traditional proportional fair (PF) scheduling algorithm is executed independently at the eNB and each RN, we propose efficient PF-based routing algorithm aiming at optimizing the GPF objective, which also takes into account the impact of relay link resource allocation. Through system-level simulations, the proposed algorithm is evaluated and compared with both non-relaying and relaying systems with benchmark routing algorithms. Simulation results demonstrate that the proposed algorithm can achieve better system throughput and fairness performance.

In this paper, considering a relay assisted hybrid overlay/underlay cognitive radio system with peak interference power constraints for protecting the primary system, the upper bound of outage probability of secondary system with power limit is derived. The results show that the outage performance of secondary system improves with the increase of maximum tolerated interference power before a specific threshold, but it keeps unchanged after the threshold. The results also show that more relays can provide higher diversity gain to get better outage performance in this kind of cognitive radio system. It is also indicated that the outage performance of secondary system is affected by the activity behavior of primary network, and relay cooperation can decrease this kind of affection.

The convergence of non-cooperative distributed power control in Gaussian interference channel is analysed in this study. Firstly, the existing distributed power control schemes are categorised as two types: gradient projection type and non-linear type, according to the iterative steps. A unified mathematical formulation is then provided for each type. The objective is extended from rate maximisation, which has been studied a lot in iterative water-filling game, to more general form of utility maximisation. Based on it, a set of sufficient conditions are derived for each type of the schemes, guaranteeing the uniqueness of the fixed point and the global convergence in a totally asynchronous manner. These convergence requirements can be interpreted as different degree of separation, according to the concrete form of utility function. To get insight into the derived convergence conditions, some numerical results are presented in the end.

In this study, the authors propose an incremental opportunistic decode-and-forward (ODF) cooperation scheme employing orthogonal space–time block codes (OSTBC) under Rayleigh fading channels. Different from existing research, the authors use ODF and OSTBC together to maximise the diversity gain, while incremental relaying is implemented to improve transmission efficiency. Besides, a more practical system model is introduced where multiple geographically isolated nodes are equipped with multiple antennas and the large scale fading is taken into consideration. The exact expression of end-to-end outage probability is derived in the whole signal-to-noise ratio (SNR) region for arbitrary relay number, antenna configuration and incremental relaying trigger value. Through asymptotic analysis, the authors also obtain the closed-form expression of outage probability in high SNR region and derive the expression of diversity order. The results show that the proposed scheme outperforms traditional direct transmission and fixed ODF in arbitrary SNR region. Meanwhile, the outage probability and diversity order depend directly on the relay number, antenna configuration and incremental relaying trigger value. The analytical results can be utilised to facilitate network planning and optimisation. Simulation results are presented to verify the authors analysis.

Network coding can deliver multiple data streams simultaneously and make full use of broadcast nature of wireless channels. The authors propose two diversity-enabled network-coding (NC) schemes to optimise wireless uplink scheduling. The existing scheduling protocols normally have to allow the users with relatively low channel gains to transmit, and it can maintain fairness but reduce congregated throughput. The main idea of the proposed scheme is to always schedule users with the best channel condition, while the use of NC encourages the scheduled users to help others which have not been served previously. Delay and capacity performance for different network coded scheduling schemes are analysed. Round-robin and pure opportunistic scheduling are evaluated for performance comparison. In order to show the effectiveness of the proposed schemes, NC schedulers are applied to a time division duplexing code division multiple access wireless cellular networks. System-level simulation was carried out based on the third generation partnership project specifications. Per-sector average throughput and cumulative distribution function of user average throughput are adopted as the performance metrics. Analytical and simulation results show that the proposed NC schedulers can achieve a better tradeoff between fairness and throughput than those without NC.

Carrier aggregation (CA) is one of the promising techniques for the further advancements of the third-generation (3G) long-term evolution (LTE) system, referred to as LTE-Advanced. When CA is applied, a well-designed carrier scheduling (CS) scheme is essential to the LTE-Advanced system. Joint user scheduling (JUS) and separated random user scheduling (SRUS) are two straightforward CS schemes. JUS is optimal in performance but with very high complexity, whereas SRUS is contrary. Consequently, the authors propose a novel CS scheme, termed as ‘separated burst-level scheduling’ (SBLS). In SBLS, the connected component carrier (CC) of one user can be changed in burst level, whereas in SRUS, it is fixed. Meanwhile, SBLS limits the users to receive from only one of the CCs simultaneously, which is the same as that in SRUS. In this way, SBLS is expected to achieve higher resource utilisation than SRUS but with acceptable complexity increase. There are two factors that are important to the performance of SBLS, namely the dispatching granularity and the dispatching policy. The authors' analysis is verified by system-level simulations. The simulation results also show that the resultant performance gain of SBLS over SRUS is notable and increasing dispatching granularity will quickly deteriorate the performance of SBLS.

The theoretical analysis on quality-of-service (QoS) performances is required to provide the guides for the developments of the next-generation wireless networks. As a good analysis tool, the probabilistic network calculus with moment generating functions (MGFs) recently can be used for delay and backlog performance measures in wireless networks. Different from the existed studies which mostly focused on the single-hop networks with single-user under a two state Markov channel model, this study develops an analytical framework for wireless multi-hop relaying networks under the finite-state Markov channel by using probabilistic network calculus with MGFs. By using the concatenation character of network calculus, the authors regard a two-hop wireless relaying channel as a single server equivalently, which consisting of two dynamic servers in series. When the single-user model is straightforwardly extended and applied in multi-user scenarios, the state space of service process is increased exponentially with the number of users, which is only applicable in case of very small user number. Then, in order to avoid the limitation of user number, the authors propose to reflect the multi-user effects by using the equivalent data rate of the modified service process, whose transition and stationary probabilities are kept unchanged with those in single-user scenarios. Next, delay and backlog bounds of multi-hop wireless relaying networks are derived with the proposed analytical framework. Simulation results show that analytical bounds match simulation results, whose accuracy depends on the required violation probability. The effectiveness of the relaying techniques in improving the performances is also demonstrated.

We consider two end users which have asymmetric traffic requirements in terms of both data rate and outage probability. They exchange information in Rayleigh flat-fading channels, and a half-duplex relay node is employed to assist the bidirectional communication between them, using the analog network coding (ANC) protocol. The provision of power levels for each node is investigated so as to minimize the total energy consumed to satisfy the asymmetric traffic requirements. By comparing energy consumptions between ANC strategy and direct transmission strategy, the relay operating region is also identified in which relay-assisted transmission can yield higher energy efficiency than direct transmission. It also indicates that the relay node is best positioned at the middle point of the two end nodes for any asymmetric traffic requirements from the perspective of energy consumption minimization.

We propose a new framework of joint spectrum allocation and power control to utilize open spectrum bands in cognitive radio networks (CRNs) by considering both interference temperature constraints and spectrum dynamics. We first address a simpler problem for the case of a single flow. A TDM-based power-control strategy is adopted to achieve maximum end-to-end throughput by choosing an appropriate multihop route and spectrum combination for each single flow. Then, the simpler solution is extended to the multiflow case in which interflow interference and cumulative interference temperature must be considered. Considering the overhead of switching route and spectrum, the optimal waiting time before making a switch is derived. Our in-depth simulation study has shown that the proposed algorithms utilize spectrum more efficiently than other existing algorithms.

In this paper, we study the design of network coding for the multiple two-way relaying channels where multiple pairs of sources wish to exchange information with their partners. All nodes are equipped with multiple antennas, and we focus on a particular scenario where the sources have less antennas than the relay. For such a case, the application of existing protocols developed for the scenario with a single pair has to rely on the time sharing approach, which will result in some loss of reliability and throughput. In this paper, we develop a new network coding transmission protocol which can be viewed as a combination of traditional beamforming and the recently developed approaches of signal alignment. By using such a protocol, all M pairs of source nodes can accomplish information exchanging within two time slots. We have developed analytical results, such as outage probability and diversity-multiplexing tradeoff, which demonstrate that the proposed transmission protocol can achieve a larger multiplexing gain than the time sharing approach. Furthermore, the proposed network coding scheme is extended to the special case where source nodes only have a single antenna. Simulation results have been provided to demonstrate the performance of the proposed network coding schemes.

In this paper, we study a special case of multi-way relaying channel, to which traditional beamforming cannot achieve the best performance due to insufficient antennas. A new transmission protocol is proposed by aligning the messages from the same pair with the help of relay precoding. As a result, inter-pair interference can be avoided and intra-pair interference can be coped with by using network coding. Then analytic results, such as the ergodic sum rate and the outage probability, are developed for the proposed protocol. The numerical results are also provided to demonstrate the performance of our proposed scheme. To improve the diversity gain of the proposed scheme, an optimal scheme is also presented.

We consider a two-way relay system where two sources exchange information with the assistance of multiple, non-cooperative, relay nodes. Specifically, we propose a capacity upper bound for the two-way relay channel and derive the achievable regions for different relay strategies, such as the amplify-and-forward (AF), the decode-and-forward (DF) and the compress-and-forward (CF). Furthermore, the upper bound and the achievable regions for the additive white Gaussian noise channel are presented. Numerical results are provided to illustrate how the capacity varies with respect to the number of relay nodes, the distance between the relays and the sources, and the transmission powers.

Considering a cooperative multicast system where 2 sources transmit data to 2 users with the help of 1 relay (2-1-2), the performance of a network coded cooperative (NCC)transmission scheme is evaluated. Due to the use of network coding, more than one source node can be served simultaneously by one cooperative transmission. As a result, the time resource consumed by the cooperative transmission is reduced and the spectral efficiency is significantly increased. In this paper, to facilitate performance evaluation, three information-theoretic metrics, i.e., ergodic capacity, outage probability and diversity gain are studied. Both analytical and numerical results show that the NCC scheme can significantly improve ergodic capacity, while achieving almost the same outage probability and the same diversity gain as the conventional scheme.

In multiuser cognitive radio (CR) network, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs. Due to lack of cooperation among different nodes in the network, channel uncertainty is considered. In a worst case philosophy, a closed-form worst-case expression is derived, with which the uncertainty optimization problem is transformed into a certain one. Second-order cone programming approximation (SOCPA) method is proposed as a robust algorithm. Typical network models are approximated to second-order cone programming problems and solved by interior-point method. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel models by simulation.

In cognitive radio networks, the statistical duty cycles (traffic loads) of primary channels have a decisive effect on the throughput and link maintenance of secondary users (SUs). It is very difficult and time-consuming for the SUs to distinguish between primary channels in terms of duty cycles. This paper proposes a multi-user cooperation scheme where SUs share status information about the primary channels and the corresponding cooperation information processing scheme based on Bayesian inference to differentiate the primary channels in terms of statistical duty cycles within a short period of time. The cooperation information processing scheme helps the SUs quickly make accurate estimates of the statistical duty cycles of primary channels and theire uncertainties. Specifically, with the aid and information from its cooperating neighbors, a SU will continuously update the likelihood function and the priori distribution for each primary channel. Analytical and simulation results show that the proposed multi-user cooperation scheme, which is based on a Bayesian updating rule, can significantly save a SU's time in channel detection and selection, and therefore greatly improve its data transmission time and throughput.

The convergence of non-cooperative distributed power control in Gaussian interference channel is analyzed in this paper. Firstly, the existing distributed power control schemes are categorized as two types: gradient projection type and non-linear type, according to the iterative steps. A unified mathematical formulation is then provided for each type. The objective is extended from rate maximization, which has been studied a lot in iterative water-filling game, to more general form of utility function. Based on it, a set of sufficient conditions are derived for each type of the schemes, guaranteeing the uniqueness of the fixed point and the global convergence in a totally asynchronous manner. These convergence requirements can be interpreted as different degree of separation, according to the concrete form of utility function. To get insight into the derived convergence conditions, some numerical results are presented in the end.

Interference coordination is the key to reduce intercell interference in a TD-LTE system. Because of implementation complexity, partial and soft frequency reuse schemes are hardly suitable to TD-LTE systems. The decode-and-forward relay scheme, which may generate some additional interference, is presented to extend coverage and improve performance of TD-LTE systems. To mitigate the relay related interference, a directional relay topology is proposed in this paper. The radio resource is reused between the isolated RSs to improve the spectrum efficiency. The joint interference coordination and directional relay can suppress most inter-cell and inter-relay interferences and improve the capacity. The signal to interference plus noise ratio (SINR) distributions and throughput for the traditional non-relay scenario and the proposed directional relay scenario are derived. The analysis and simulation results show the effectiveness of the proposal scheme.

In multiuser cognitive radio (CR) network, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs, which is nonconvex problem. Iterative dual subgradient (IDuSuG) algorithm is proposed to solve such problems. It iteratively performs BF and PC to optimize the sum rate, among which minimum mean square error (MMSE) or virtual power-weighed projection (VIP2) is used to design beamformers and subgradient method optimizes the PC. VIP2algorithm is devised for the case of the interference caused by MMSE beamformer over the threshold. Channel uncertainty is considered and robust algorithm is provided by modifying updates in iterative process. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel model by simulation.

An outage probability analysis model is presented to evaluate performances and show key factors impacting on performances for the heterogeneous relaying scheme utilized to complete the hierarchical convergence of multiple radio access networks (RANs). The diversity gains related to the multiple access schemes and power constraints are analyzed. Our analytical and simulation results show that the outage probability mainly depends on the number of cooperative relay nodes, multiple access scheme, normalized power, and radio channel characteristics. Meanwhile, the power constraint for relay nodes does not have much impact on the outage performance especially when the broadcast/multicast radio channel condition is good enough.

In this paper, we study the outage performance of decode-and-forward (DF) opportunistic communication systems with the Nth best relay selection scheme under independent but not necessarily identical Rayleigh fading channels. In traditional opportunistic cooperation, only the best relay helps forward the source's messages to the destination. However, in practical systems, the best relay may be unavailable due to scheduling and overload problems. In this case, another suboptimal but available relay may be selected to participate in cooperation. Without loss of generality, we analyze the performance when the Nth best relay is selected to cooperate and take the availability of the direct link between the source and the destination into consideration. In particular, we derive the exact expression of outage probability for arbitrary signal-to-noise (SNR), then we obtain the closed-form expression in high SNR region. Through asymptotic analysis, the diversity order which reflects the effect of the direct link is obtained and it is linearly related with the number of relays and the selection criterion N. Simulation results are presented to verify the analysis.

In the planning of cellular networks, link budget calculation is the first step to get the maximum allowable cell radius that guarantees a target signal to interference plus noise ratio (SINR) with a certain level of outage probability at the cell border. The interference margin as one of key inputs for link budget is used to compensate for co-channel interference. In this paper, a mathematical analysis for interference margin as a function of system load is proposed in orthogonal frequency division multiple access (OFDMA) cellular networks. The analysis is derived from OFDMA features based on a general expression of exponential effective SINR mapping (EESM). The proposed approach can be easily applied to the evaluation of interference from neighboring cells, and help to improve the accuracy of the link budget calculation in OFDMA systems. All the theoretical analysis given in this paper have been proved by Monte Carlo simulations.

The Physical Downlink Control Channel (PDCCH) is used to signal dynamic resource assignment information in the Long Term Evolution (LTE) system. In the presence of numerous active users, the system performance is likely to be hindered by shortage of control channel resource. In this paper, several simple algorithms are brought forward for making efficient PDCCH resource allocation. We first propose a minimum aggregation level algorithm (Min-AL) to maximize the total number of scheduled users by exploiting multi-user diversity gain, followed by algorithms with the purpose of improving the blocking performance of cell-edge area through co-channel interference avoidance (CCI-A) and priority boosting (PB). Simulation results have shown that the Min-AL algorithm achieves the best system performance at the expense of cell-edge performance, while both CCI-A and PB algorithms are effective in reaching a compromise between system and cell-edge performance.

This paper considers the network coded relay protocol utilized in the cellular systems. The time division multiple access (TDMA) based opportunistic network coded cooperation(TDMA-ONCC) scheme, whose central idea is to perform the opportunistic network coded cooperation based on the observed instantaneous channel qualities of source-to-relay and relay-to-destination links, is researched. Performances in terms of ergodic capacity and outage probability are derived for both TDMA-ONCC and the single relay based opportunistic selecting Decode-and-Forward (SR-OSDF) schemes. The tight closed form expressions for the outage probability are derived. Numerical results show that the proposed expressions for both the ergodic capacity and the outage probability are close to the theoretical analysis results. The results show that the TDMA-ONCC scheme significantly outperforms the SR-OSDF scheme due to the network coded cooperation gain.

In this paper, we investigate the outage performance of decode-and-forward (DF) based opportunistic cooperative communications with channel estimation errors at the receivers under Rayleigh fading channels, in which the effect of the direct link has been explicitly evaluated. To be specific, the exact expression of outage probability has been derived for arbitrary values of signal-to-noise ratio (SNR) when pilot power is fixed. Through asymptotic analysis, the closed-form expressions of outage probability in the high SNR region and the diversity order are obtained. The analysis shows that the channel estimation errors due to limited pilot power impose a significant impact on the outage performance, leading to the diversity order be 0 even when the direct link is available. Although deploying more relays can mitigate the estimation errors effectively, the performance limit caused by the estimation errors becomes more obvious as SNR grows. For specific pilot power configuration and relay deployment, the outage probability remains unchanged even if data power approaches to infinity. Furthermore, simulation results are presented to verify our analysis.

In time division-high speed packet access plus (TDHSPA+) system, multiple input multiple output (MIMO) technique is adopted to improve spectrum efficiency and transmission reliability. However, most current literature are focused on the large spacing antenna setup, which is impractical for user equipment (UE) because of the size limitation. Therefore, dual polarization antenna scheme is introduced in the system to provide multiplexing gain and/or diversity gain. In this paper, we derive the dual polarization channel model for performance evaluation. Furthermore, the performance of dual polarization scheme under different MIMO architectures is presented and analyzed. It is shown that polarization scheme can achieve similar average throughput and successful transmission ratio compared with spatial separation scheme in various scenarios.

Wireless cooperative relay is an efficient way in obtaining diversity in distributed manner, and it can also be used as a way in extending the cell coverage in cellular systems. In this paper, assuming receiver channel state information (CSI) only, the ergodic and outage capacity analysis are presented for amplify-and-forward (AF) multiple-input multiple-output(MIMO) relay channels deploying orthogonal space-time block codes (OSTBCs). Under flat Rayleigh fading environment, we derive closed-form analytical expressions for the calculation of the ergodic capacity and outage capacity for both the OSTBC transmission with and without the direct link. Numerical results show that all the derived analytical expressions are very tight and are valid for evaluations of the ergodic and outage capacity under various antenna configurations. The results also show how the number of transmit antennas and receives antennas affect the overall channel capacity under fading channel environments.

In the next generation wireless systems, it's quite likely that a large number of user terminals are not able to transmit and/or receive over the entire system bandwidth, as much wider system bandwidth, e.g., 100 MHz, is expected to be employed in the future. As a new and challenging problem, user terminal bandwidth limitation is considered in this paper, and multiuser resource allocation for orthogonal frequency division multiplexing (OFDM) downlink with terminal bandwidth limitation is discussed. The optimal multiuser resource allocation strategy is first presented; however, due to the prohibitive computational expense of the optimal strategy, two suboptimal resource allocation strategies with significantly reduced complexity are proposed as well. The performance of the two suboptimal strategies is given via simulations, and is discussed for various scenarios.

Although the established capacity results for the classic three-node relay channel rely on the assumption of fullduplex relay nodes, it's practically difficult for radio transceivers to support simultaneous signal transmission and reception. Timedivision half-duplex relay strategies have thus been proposed to address this limitation. Amplify-and-forward (AF) and decode-and-forward (DF) are two well-known half-duplex relay strategies in the literature. Later, DF approach was extended by the so-called variable-rate two-phase relay strategy, in which the transmission rates for both phases are not necessarily the same. More recently, a novel half-duplex relay strategy based on the information theoretical concepts of broadcast channel (BC) and multiple access channel (MAC) models is proposed. In this approach, the source broadcasts distinct data flows to the destination and the relay respectively during the first phase, and in the second phase the relay forwards the received information whereas the source sends another data flow to the destination. In this paper, we will first develop optimal resource allocation, in terms of power and time, for these half- duplex relay strategies, and then compare their performance under various link conditions.

According to the number of successful decoded relay nodes with good destination-to-relay and relay-to-destination link qualities, a simple adaptive relay selection algorithm and its corresponding protocol is presented to achieve a good diversity and multiplexing gains. When the antenna number of the destination is less than the number of successful decoded relay nodes, the opportunistic relay selection scheme is utilized for achieving the diversity gain. Otherwise, the multiplexing selection scheme is adopted to achieve the multiplexing gain. We analyze the outage probability performance, and the asymptotic expression in terms of the outage probability for the proposal is derived. The diversity-multiplexing tradeoff (DMT) and ergodic capacity for the proposed algorithm are also evaluated. Compared with the individual opportunistic relay selection scheme and multiplexing selection scheme, the proposed adaptive relay selection algorithm can provide better capacity and lower outage probability.

The conventional cooperative protocols have to face some problems in practical broadcast and multicast systems because feedback channel is unavailable. An adaptive cooperative relay protocol, which can be adopted in future broadcast systems, is proposed in this paper. The outage probability performance of this protocol is analyzed over Nakagami-m fading channel, and the asymptotic expression of outage probability for proposed protocol is derived. It is compared with the conventional Decode-and-Forward and Amplify-and-Forward protocols. A combination of numerical simulation and theoretical analysis, including the optimal numbers of relays and the impact on the system performance are further analyzed for different channel states. According to these results, the advantages and characteristics of this protocol are confirmed.

Cooperative base station for downlink multiple-input–multiple-output (MIMO) system is known as a critical radio technology for worldwide interoperability for microwave access (WiMAX) communications. This study proposes to use zero-forcing beamforming for cooperative base stations in a downlink multicell MIMO system. It is well known that beamforming requires perfect knowledge of channel state information (CSI) at the transmitter, and in practice the perfect CSI may not be available because of channel estimation errors. In this study, using approximate capacity loss analysis the authors are able to analyse the effect of channel estimation errors on system capacity in a cooperative base station system with zero-forcing beamforming. A power allocation policy is proposed to reduce the capacity loss under per base station power constraints. Numerical results show that the approximate capacity loss is very close to the real capacity loss, which can be reduced with the help of the power allocation policy.

Multihop relaying is one of the promising techniques in future generation wireless networks. The adaptive modulation and coding (AMC) mechanisms can be applied in order to increase the spectral efficiency of wireless multihop networks. However, most of these mechanisms concentrate on the physical layer without taking the queuing effects at the data link layer into account, whose performances are overestimated. Therefore the cross-layer analytical framework is presented in analysing the quality-of-service (QoS) performances of the decode-and-forward (DF) relaying wireless networks, where the AMC is employed at the physical layer under the conditions of unsaturated traffic and finite-length queue at the data link layer. Considering the characteristics of DF relaying protocol at the physical layer, the authors first propose modelling a two-hop DF relaying wireless channel with AMC as an equivalent Finite State Markov Chain (FSMC) in queuing analysis. Then, the performances in terms of queuing delay, packet loss rate and average throughput are derived. The numerical results show that the proposed analytical method can be efficiently applied for studying the issues including the relay deployment and the cross-layer design in the multihop relaying networks.

In multi-input-multi-output relay systems with amplify-and-forward protocols, the source-relay and the relay-destination links can be treated as two groups of spatial channels. In this letter, an adaptive spatial channel mapping matrix is presented to be used between the two groups. A unified framework of the spatial channel mapping matrix design is presented, which includes various relay protocols. The spatial channel matrix is designed to reduce the relaying noise power or the local noise in the destination node. Simulation results demonstrate the advantage of the adaptive spatial channel mapping on the system reliability and capacity with different relay protocols.

In wireless sensor networks, several relay nodes can be used to support multiple transmission links between source and destination nodes simultaneously to achieve higher spectral efficiency. A channel state information sharing scheme among multiple relay nodes is presented in this letter, where only one angle per source-destination pair is sent from one relay node to another. Then, to enhance received signal powers, a distributed multiuser precoding scheme is presented to be used at each relay node with the angles sent by another relay node. Simulation results demonstrate that the proposed distributed precoding scheme enhances the capacity performance with slight overhead.

In this letter, a power-control scheme for maximum sum-rate is proposed for the fading multiple access channels by considering the presence of primary users. Both the average transmit-power constraints and the peak interference-temperature constraints are considered. The interference caused by cognitive users must be under a pre-specified threshold for protecting primary users. The power-control optimization is considered as a novel geometrical problem which investigates the relationship of positions of a line and a few points. At most two users transmit simultaneously for optimality and the corresponding conditions are provided for both cases. Based on the analysis, the optimal power control is given for each specific fading state. For lowering computational complexity, the power-control optimization problem is divided into two categories according to different tight constraints. Simulation results are provided for the optimal power-control performance.

Abstract Due to the TDMA (time division multiple access)/time division duplex (TDD) specialization in the uplink (UL) of code division multiplex access (CDMA) systems, some advanced techniques, such as smart antenna (SA) and multi‐user detection (MUD), are utilized conveniently in time division‐synchronous code division multiplex access (TD‐SCDMA) systems. These advanced techniques have great impacts on the capacity and radio resource management (RRM) schemes. In this paper, the UL capacity and load models specified for TD‐SCDMA systems are proposed, in which the impacts from SA and MUD techniques are considered, and the UL load can be estimated based on the total received power in the base station. According to the proposed theoretical capacity and load evaluation models, the call admission control (CAC) strategies suitable for TD‐SCDMA systems are presented. Since there are two kinds of SA schemes (i.e., tracking beam antenna (TBA) and switched beam antenna (SBA)) utilized in TD‐SCDMA systems, the efficient CAC algorithms suitable for these two SA schemes are designed and evaluated, which are based on principles of the interference increase estimation. All simulation results show that the proposed CAC strategies can work efficiently and improve performances of TD‐SCDMA systems dramatically. Copyright © 2009 John Wiley & Sons, Ltd.

Abstract This paper proposes a novel protocol based on cooperative relaying between users. The protocol takes advantage of the fact that data traffic is bursty and silent periods exist between data bursts. Rather than wasting these idle time slots, users can take advantage of them to perform cooperative relaying, obviating the need for dedicated system resources for relaying, hence using the spectrum more efficiently. The benefit of this user cooperation for the higher network layers is analyzed. The system was modeled in terms of the maximum stability region and the maximum stable throughput. Our results show that our proposed protocol provides significant performance gains compared to conventional time‐division multiple‐access (TDMA) systems, as well as cooperative relaying protocols, namely selection relaying and incremental relaying. Copyright © 2009 John Wiley & Sons, Ltd.

Considering a wireless relay network composed of a source, several relays and a destination, a linear block network coding (LBNC) scheme is proposed to combat the lossy nature of wireless channel. The relays not only replicate the messages received but also perform network coding according to a linear block generator matrix. A special case of LBNC, parity-check network coding (PCNC) scheme is firstly theoretically analyzed and the explicit Average Outage Probability (AOP) and Block Outage Probability (BOP) are derived. For comparison, advanced relay cooperation (ARC), where relays only replicate and forward messages without coding them, is also presented and analyzed. Numerical results show that PCNC performs better than ARC when SNR is high and the s - r link is in good condition. For general LBNC scheme, it is very complicated to calculate the precise outage probability due to the difference of generator matrices, and we turn to simulation to evaluate the outage performance. The result shows that the performance of (M + C, M) LBNC can be estimated by ([M/C] + 1, [M/C]) and ([M/C] + 1, [M/C]) PCNC.

In this paper, capacity performance analysis is presented for multiple-input multiple-output (MIMO) relay channels with transmit antenna selection and maximal-ratio combining receive (TAS/MRC) in amplify-and-forward (AF) relay networks operating over flat Rayleigh fading channels. Assuming that the source and destination are equipped with Ns and Nj antennas, respectively, and communicate with each other with the help of a single-antenna relay, we derive the cumulative distribution function (CDF), probability density function (PDF) and moment generation function (MGF) for the system end-to-end SNR. Based on these, we then present closed-form analytical expressions for the calculation of the ergodic capacity and outage capacity for the AF MIMO relay channels with TAS/MRC. Numerical results show that all the derived analytical expressions are very tight and are valid for evaluations of the ergodic and outage capacity under various antenna configurations. The results also show how the number of transmit antennas and receives antennas affect the overall channel capacity under fading channel environments.

Considering a wireless relay network composed of a source, several relays and a destination where the source transmits data packets to the destination through both direct and relay paths, a multi-timeslots network coding (MTNC) scheme is proposed to combat the lossy nature of wireless channel where the relay nodes with satisfying relay-destination (r - d) channel state firstly perform network coding on the successfully decoded data packets received from the source at previous timeslots and then forward the coded version to the destination. We focus on three metrics - Ergodic capacity, outage probability and symbol error rate to evaluate the performance of MTNC scheme and the replication-based relay (RR) scheme where a "best" relay node is selected out to replicate and forward the data packet. Precise closed form expression of ergodic capacity, tight estimated closed form expression of outage probability (OP) and symbol error rate (SER) are derived for both schemes, and also numerical results are shown to prove the gain of network coding. However, with increasing of the relay number, the improvement of outage probability and SER is limited.

QR decomposition (QRD) based relay protocols can achieve both the distributed array gain and the intra-node array gain in multi-relay systems. Because the QRD is not unique if column permutation is utilized, the traditional QRD based relay protocol can be further improved. Row permutation of the forward channel and column permutation of the backward channel are proposed in this paper. Exhaustive and iterative search algorithms are presented to solve the permutation optimization problem. The iterative search algorithm with modified QRD is a good trade-off between capacity performance and complexity.

Cognitive radio makes it possible for an unlicensed user to access a licensed spectrum opportunistically on the basis of non-interfering. This paper addresses the problem of joint route selection and resource allocation in OFDMA-based multihop cognitive radio networks, in the objective of optimizing different types of end-to-end performance. Aiming to solve it optimally, we first show that this problem of optimal resource allocation can be formulated as a convex optimization problem and identify its necessary and sufficient conditions. Based on this conclusion, we propose an iterative algorithm that can be implemented in a distributed manner. This algorithm applies Lagrangian duality theory and the Frank-Wolfe method. The scheme thus converges to a globally optimal solution. We present numerical results from using the algorithm to provide insight into the optimal cross-layer design, e.g., the relationship between bottleneck throughput and hops, and the effect of interference temperature constraints.

In this paper, a novel observe-and-forward (OF) cooperative scheme is proposed for relay-enhanced wireless cooperative systems. In this scheme, the codewords transmitted from the source are regenerated by the decoder at the relay and forwarded without re-encoding or interleaving. The decoding processes for different streams of a transmitted codeword can be parallel, which greatly reduces the relaying latency and the complexity of the relay. Furthermore, classical Viterbi algorithm (VA) decoding is adopted at the destination while a Turbo decoding is necessary in decoded-and-forward with coded cooperation (DF-CC) scheme. Union bounds on error performances and the achievable rates are analyzed for the OF scheme. Both the analysis and simulation show that the proposed OF scheme works as well as the classical DF scheme and even better than the DF-CC scheme in some scenarios. The features of the proposed OF scheme are smaller relaying latency and lower complexity, which facilitate the application of this relaying scheme.

In this paper, we investigate resource allocation for decode-and-forward (DF) opportunistic cooperative networks, where the availability of the direct link between the source and the destination has been taken into consideration. In addition to separate power allocation and location optimization, we also consider joint resource allocation to minimize the outage probability. Under Rayleigh fading channels, the closed-form solution is derived for both separate and joint resource optimizations. Numerical results show that the proposed optimized systems outperform the unoptimized ones, and the minimum outage probability can be achieved by joint power-location optimization.

Selection cooperation has been proposed as a promising way of realizing cooperative diversity for its simplicity and good performance. In this paper, a framework to analyze the multiuser diversity and selection diversity in multiple-relay networks is presented. Based on this framework, we derive closed-form asymptotic expressions of outage probability and symbol error rate (SER) for both amplify-and-forward (AF) and decode-and-forward (DF) based multiple-relay networks. Both the theoretical analysis and simulations show that a multiuser diversity order of K and a selection diversity order of M + 1 can be achieved simultaneously for both AF and DF protocols (where K is the number of accessing users and M is the number of available relays). These show that the multiuser diversity can be readily combined with the selection diversity in multiple-relay networks.

This paper considers subcarrier allocation for the multihop orthogonal frequency division multiple-access (OFDMA) broadcast networks consisting of one source, multiple destinations, and one amplify-and-forward (AF) relay. In this paper, proportional fair (PF) based subcarrier allocation is discussed to get a tradeoff between the system transmission rate and fairness. First, the problem is formulated as an optimization problem with prohibitive complexity. Second, by analyzing the optimal solution for the subcarrier allocation problem without PF constraint, two suboptimal schemes are proposed. The simulation results indicate that with the same fairness performance, the proposed schemes achieve considerable capacity gain compared with the conventional PF scheduling method which is extended simply from the single-hop system.

A robust joint multiuser scheduling and precoding design is proposed for uplink multiuser MIMO systems with imperfect channel state information (CSI). The effect of the antenna correlations is involved in the channel model. The multiuser scheduling and the precoding that avail the total mean square error (TMSE) minimization criteria under individual power constraint are firstly deduced and the combination of the two parts is designed in the following. The proposed design is compared with the robust precoding with random scheduling scheme and the non-robust scheme. The simulation results show that the joint design helps achieving larger system throughput and the robust algorithm mitigates the performance loss due to the imperfect CSI.

Inner cell interference (INCI) is avoided in common multicell orthogonal frequency division multiplex access (OFDMA) systems but inter cell interference (ICI) still exist. The system throughput is severely degraded by ICI, especially at cell edge. Several schemes have been proposed to handle this problem by coordinating the way to allocate spectrum resource to each cell. Since the allocation of spectrum has effects on ICI mitigation and the spectral efficiency, a wise strategy to consider those two factors is required. In this paper, the power division reuse partitioning scheme with successive interference cancellation (PDICS) for OFDMA uplink transmission is discussed. PDICS balances ICI mitigation and spectral efficiency by appropriate frequency allocation and power distribution. To improve frequency efficiency, the frequency reuse factor is chosen as 0.5, so INCI exists. To minimize INCI, successive interference cancellation is suggested. The simulation results show that PDICS has better performance of throughput and symbol error rate (SER) than the conventional schemes.

We propose a forwarding scheme by superposition coding for wireless relaying, in which a relay will not forward a message to a destination if the destination has successfully decoded the message directly from a source. In our scheme, flag signal and data signal are superimposed and transmitted by the source, and according to whether the flag signal has been successfully decoded by the relay, the relay can determine whether to forward the data signal to the destination. Numerical results show that our scheme can outperform classical decode-and-forward cooperation scheme in terms of spectral efficiency and outage probability.

A hybrid system of cellular mode and the peer-to-peer (P2P) mode is considered in this paper, where the cellular uplink resource is reused by the P2P transmission. In the objective of overall system throughput maximization, we addresses the problem of distributed power control of P2P transmission in the hybrid system model. Some preliminary results of the problem are presented first to investigate the optimal solution of the problem. Based on these results, by applying the game theory approach, that is, potential game, an asynchronously distributed power control scheme is devised. The associated properties of the proposed scheme are analyzed, including the global convergence, the conditional optimality and the Lyapunov stability. In the end, simulation is conducted to study the performance of the proposed scheme, which shows satisfying results.

A hybrid system of cellular mode and device-to-device (D2D) mode is considered in this paper, where the cellular uplink resource is reused by the D2D transmission. In order to maximize the overall system performance, the mutual interference between cellular and D2D sub-systems has to be addressed. Here, two mechanisms are proposed to solve the problem: One is mitigating the interference from cellular transmission to D2D communication by an interference tracing approach. The other one is aiming to reduce the interference from D2D transmission to cellular communication by a tolerable interference broadcasting approach. Both mechanisms can work independently or jointly to synergy the transmission in the hybrid system for the efficient resource utilization. In the end, simulation is conducted to study the performance of the proposed schemes, which shows satisfying results.

In cognitive radio (CR) networks, the ability to capture a frequency slot for transmission in a vacant channel has a significant impact on the spectrum efficiency and quality of service (QoS) of a CR user. Important factors include spectrum handoff, transmission rate and delay. This paper proposes a framework for sensing and selecting channels that have the highest probability of appearing idle while reducing the corresponding sensing time. In contrast to previous work, we consider the practical issues encountered by a CR user in a wireless environment, such as discontinuous target frequency bands and limited spectrum sensing ability. We examine the spectrum sensing scheme in terms of packet loss ratio (PLR). The simulation results show that the proposed spectrum sensing strategy can decrease the probability of packet losses in the discontinuous spectrum environment and improve spectrum efficiency.

This paper presents a resource allocation framework for the transmission of heterogeneous services in two-hop orthogonal frequency division multiplexing (OFDM) cooperative relay systems. An optimal adaptive power and subcarrier allocation scheme is proposed to maximize the system throughput while satisfying the quality of service (QoS) requirements of both the real-time (RT) and nonreal-time (NRT) service for point-to-point transmission, and a sub-optimal fast search algorithm is proposed for practical implementation. Then, the idea is extended to point-to-multipoint transmission of heterogeneous services. Optimal solution is provided, and a fastest-power-descending based power and subcarrier allocation algorithm is proposed. Simulation results show that the proposed schemes improve the spectral efficiency while guaranteeing the QoS of each user.

In cognitive radio networks, the limitation of control channel bandwidth is a challenge of cooperative spectrum sensing when the number of cognitive users becomes very large. Cluster- based architecture is applied for cooperative sensing to avoid the congestion on control channel and reduce the sensing delay. In this paper, we propose a cluster-based cooperative spectrum sensing scheme to improve the efficiency of the network. The number of clusters effects both the system efficiency and detection performance significantly. By balancing the tradeoff between the communication overhead and sensing reliability, we can obtain the optimal number of clusters, which can minimize the cooperation overhead without any performance loss of reliability. Moreover, a clustering strategy is proposed based on a given number of clusters and simulation results show the superiority of the proposed strategy.

This paper proposes a novel semi-dynamic inter-cell interference coordination (ICIC) scheme for multi-cell OFDMA systems. The objective of the novel scheme is to strike a balance between ICI minimization and frequency reuse factor (FRF) maximization. Firstly, we divide cell-edge users into non-overlapping user groups based on users' geometry, and classify each group's available bandwidth, which includes both orthogonal resource and non-orthogonal resource, into several ranks according to traffic load in neighboring groups. Then, different allocation strategies are applied correspondingly to different ranks of resource. The novel scheme achieves variant complexity and overhead according to traffic load. Simulation results show that the novel scheme can significantly enhance the cell edge throughput and reduce blocking probability, especially for networks with heavy-loaded spots in cell-edge area.

In this paper, we consider the optimal resource allocation problem for dual-hop systems with a source-destination pair and multiple decode-and-forward (DF) relays. Orthogonal frequency division multiplexing (OFDM) is adopted in both hops. To maximize the system capacity, we formulate a mixed binary integer programming problem to optimally allocate the subchannels and transmit power for both the source and the relay nodes. Because of the prohibitive complexity, a greedy heuristic algorithm is proposed to decompose the original problem into solvable subproblems. Simulation results demonstrate that the proposed algorithm has a near-optimal performance.

Due to similarity between cooperative systems and traditional multi-input-multi-output (MIMO) systems, precoding techniques can be introduced into MIMO relay systems. In this paper, a practical distributed precoding scheme with limited feedback scheme is proposed in the MIMO relay system, where the zero-forcing (ZF) relaying protocol is proposed to be used in the relay node so that the information of relaying channel and noise can be compressed into two positive real coefficients. Precoding is proposed to be operated through two continuous transmitted vectors of the source node, which is termed as distributed spatial-temporal precoding (DSTP). Power allocation is combined with the proposed DSTP for higher spectrum efficiency. DSTP outperforms the direct transmission and the simple ZF relaying protocol. Analysis and numerical results demonstrate that DSTP with suitable receiver performs very close to the capacity low bound of the ZF relaying system.

The incremental relaying (IR) protocol outperforms simple amplify-and-forward and decode-and-forward protocols due to usage of feedback. Based on the IR protocol, a novel protocol termed as fractional incremental relaying (FIR) is firstly presented in this paper to achieve higher spectral efficiency. When a packet of data needs to be transmitted by the relay node, symbols are transmitted a few at a time as needed instead of the entire packet. Then, analysis result shows that the proposed protocol makes more efficient use of channel freedom degrees than the traditional IR protocol does. Finally, numerical results under independent Rayleigh fading demonstrate the advantage of the proposed FIR protocol.

In this paper, we investigate the linear processing at either base station or relay station in cellular network with a non-regenerative MIMO relay assisting. The purpose of linear processing is to equalize the two-hop fading channel in order to support multiuser transmission in downlink and uplink. Under the transmit power constraint at each station, the closed-form expressions of the suboptimal MMSE processing matrix in downlink and the optimal MMSE processing matrix in uplink are derived when the linear processing is performed at either base station or relay station. Simulation results demonstrate that the proposed MMSE strategies significantly outperform the corresponding ZF strategies in terms of BER.

In this paper, we investigate the performance of heterogeneous networks with multi-antenna cooperative relays. Specifically, threshold-based maximum ratio combining (MRC) and selection combining (SC) schemes are adopted for decoding at the relays and the end-to-end (E2E) error rate performance is analyzed by assuming a Nakagami channel model. Numerical results show that the deployment of multi-antennas can reduce the number of required relay nodes, and thus significantly reduce the system cost. On the other hand, the selection of optimal decoding threshold depends on the number of relay nodes, number of antennas, as well as the average SNR value at the receiver. It is also demonstrated that when the BER requirement is not high, the SC relaying scheme is sufficient to provide satisfactory performance, such that the complexity of relays can be effectively reduced.

Performance analysis is presented for multiple-input multiple-output (MIMO) relay channels with transmit antenna selection and maximal-ratio combining receive (TAS/MRC) in two-hop amplify-and-forward (AF) relay networks operating over flat Rayleigh fading channels, where the source and destination are equipped with Ns and Nj antennas, respectively, and communicate with each other with the help of a single-antenna relay. We derive closed form expressions for the cumulative distribution function (CDF) and probability density function (PDF) of the overall system SNR, based on which we present exact symbol error rate (SER) and outage performance analysis. The theoretical analysis is validated by Monte Carlo simulations, which show an exact match between them. Our analysis shows that full spatial diversity order, which corresponds to the minimum number of antennas at the source and destination, i.e., min{Ns,Nd}, can be achieved for the two-hop AF MIMO relay channel with TAS/MRC.

This paper investigates the spatial resource allocation algorithms for the uplink Virtual-MIMO (Multiple Input and Multiple Output) systems, where K client users (each with one or multiple antennas) are served by one multiple-antenna BS (Base Station). To fully exploit the spatial multi-user diversity gain, the finding of the optimal spatial co-channel users is discussed, which is formulated as a mixed binary integer programming problem. Based on the property of hermitian matrix, simulated annealing is used to recursively find the suboptimal spatial co-channel user group. By simulation results, our proposed strategy has almost the same system throughput performance as the optimal greedy algorithm, and can maintain lower computation complexity.

The MAC-layer sensing, as a key component of spectrum sensing in cognitive radio, concerns the sensing mechanism design to determine when to sense and access which channel. An important issue of MAC-layer sensing is to find an available channel with a minimized searching delay for the cognitive transmission without any harmful interference. In this paper, we focus on this issue and propose adaptive searching scheme and cluster-based searching scheme to reduce the searching time when channel conditions are various and the cooperative sensing is applied. Moreover, the optimization of these two schemes are also developed in this paper. By adaptive selecting the searching parameters according to the current environment, the average consumed time of channel searching can be minimized, while the searching quality is also satisfied. The simulation results verify the confidence of proposed schemes and show a better searching performance when combining these two schemes.

In this paper, we investigated the end-to-end throughput of a chain in Cognitive Radio Networks (CRNs). We found that, the end-to-end throughput is dependant on both the primary usage patterns and the transmission scheduling scheme being used. In addition, to increase the end-to-end throughput of a Cognitive Radio (CR) chain, the scheduling scheme should be adjusted according to the primary usage patterns of the CR links in the chain. In the paper, firstly, we proposed an algorithm to approximate the achievable end-to-end throughput considering the primary usage patterns by abstraction and iteration. Then, a novel layered packets transmission scheduling scheme was proposed in attempt to realize the approximated end-to-end throughput. Finally, extensive simulations were conducted and results showed that, using proposed transmission scheduling scheme, the achievable end-to-end throughput of a CR chain is increased by considering the primary usage patterns and the final end-to-end throughput is close to the approximation.

A two-hop relaying system where a source communicates with its destination through multiple relay nodes is studied for capacity maximization. Amplify-and-forward (AF) relaying is adopted for its simplicity. Taking the independent channel transfer function of different subcarriers and links into consideration, we formulate a resource allocation optimization problem for joint subcarrier assignment, subcarrier matching and power allocation of the two-hop transmission. A heuristic suboptimal algorithm which decomposes the joint problem is proposed. First, equal power allocation is assumed in a partial- update manner to help assigning subcarriers to each relay for matching; then optimal power allocation is achieved by joint waterfilling of source and relays under separate power constraints to further increase system capacity. Numerical results show that the proposed algorithm has a near-optimal performance.

Cognitive radio makes it possible for an unlicensed user to access a licensed spectrum opportunistically on the basis of non-interfering. This paper addresses the problem of resource allocation for multiaccess channel (MAC) of OFDMA-based cognitive radio networks, taking into account of the interference temperature constraints. The objective is to maximize the system utility, which is used to quantify different quality-of-service (QoS) requirements of different users. Firstly, a theoretical framework is provided, where necessary and sufficient conditions for optimal subcarrier assignment and power allocation are presented under certain constraints. Then, an effective algorithm is devised for more practical conditions based on Lagrangian duality theory, where subgradient/ellipsoid method is applied for Lagrangian multipliers iteration. With polynomial time complexities, the proposed resource allocation algorithm is proved to achieve optimal system performance by numerical results.

In fast moving environment, the inter-carrier interference (ICI) due to Doppler spread will degrade the performance of OFDM system severely. Using Jakes' model for the Doppler power spectrum and linear model for time-varying channel during an OFDM symbol interval, the analytical closed- form expression of ICI power, signal-to-interference ratio (SIR) and signal-to-interference-plus-noise ratio (SINR) are given without assumption on the statistical characteristic of ICI. Moreover, the effect on bit error probability (BEP) performance by the number of concerned interfering subcarriers is analyzed, which helps to choose the number of concerned interfering subcarriers according to the Doppler spread to greatly reduce the complexity of ICI mitigation method with little performance penalty. The simulation results show that the ICI analysis and SIR expression are efficient, and the concerned number of interfering subcarriers should be more with the increase of Doppler spread when ICI mitigation is adopted.

This paper analyzes the problem of multi-service transmission in multiuser cooperative networks. The objective is to maximize the best effort (BE) service utility while guaranteing the rate constraint of QoS service. In this paper, we first deduce the optimal power ratio of the source obtained power to total power. Based on this deduction result, the optimal solution of multi-service transmission is investigated. To further reduce the algorithm complexity, a suboptimal resource allocation algorithm is also proposed. Simulation results are provided to evaluate the utility and outage performance of these two algorithms when different value of power ratio is chosen.

In this paper, the Cramer-Rao lower bound (CRLB) for spatial correlation matrices is derived based on a rigorous model of the doubly selective fading channel for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Adopting an orthogonal pilot pattern for multiple transmitting antennas and assuming independent samples along the time, the sample auto-correlation matrix of the channel response is complex Wishart distributed. Then, the maximum likelihood estimator (MLE) and the analytic expression of CRLB are derived by assuming that temporal and frequency correlations are known. Furthermore, lower bounds of total mean squared error (TMSE) and average mean squared error (AvgMSE) are deduced from CRLB for asymptotically infinite and finite signal-to-noise ratios (SNR's), respectively. According to the lower bound of AvgMSE, the amount of samples and the order of frequency selectivity show dominant impact on the accuracy of estimation. Besides, the number of pilot tones, SNR and normalized maximum Doppler spread together influence the effective order frequency selectivity. Numerical simulations demonstrate the analytic results.

In cognitive radio networks, the unlicensed users can utilize the unoccupied licensed spectrum opportunistically. In this paper, we propose a joint power and end-to-end rate control algorithm considering restricting the interference to licensed users. By duality theory, the optimal resource allocation solution is given for the unlicensed users while satisfying the interference temperature limits. An asynchronous algorithm is proposed to be implemented in practical networks. Finally, we give a discussion to the proposed algorithm's performance on fairness. Numerical results show that the proposed algorithm can limit the interference to licensed user under a predefined threshold while maintaining a satisfied data rate fairly.

In this letter, a novel maximum Doppler spread estimation algorithm is presented for OFDM systems with the comb-type pilot pattern in doubly selective fading channels. First, the least-squared estimated channel frequency responses on pilot tones are used to generate two auto-correlation matrices with different lags. Then, according to these two matrices, a Doppler dependent parameter is measured. Based on a time-varying multipath channel model, the parameter is expanded and then transformed into a nonlinear high-order polynomial equation, from which the maximum Doppler spread is readily solved by using the Newton's method. The delay-subspace is utilized to reduce the noise that biases the estimator. Besides, the subspace tracking algorithm is adopted as well to automatically update the delay-subspace. Simulation results demonstrate that the proposed algorithm converges for a wide range of SNRs and Dopplers.

In multiuser cooperative relay networks, cooperative diversity can be obtained with the help of relays, while multiuser diversity is an inherent diversity in multiuser systems. In this letter, the performance analysis of multiuser diversity in cooperative multirelay networks is presented. Both the case of all relay participating and the case of relay selection are considered. We first derive asymptotic expressions of outage probability and symbol error probability for amplify-and-forward (AF) and decode-and-forward (DF) protocols with joint multiuser and cooperative diversity. Then, the theoretical analysis are validated by Monte Carlo simulations. Both the theoretical analysis and simulations show that a multiuser diversity order of K and a cooperative diversity order of M+ 1 can be achieved simultaneously for both AF and DF protocols (where K is the number of accessing users and M is the number of available relays). These demonstrate that the multiuser diversity can be readily combined with the cooperative diversity in multiuser cooperative relay networks.

This paper investigates a simple and effective power allocation method to maximize the Effective Configuration Duration(ECD) in wireless sensor networks, which aims to minimize the signaling overhead needed to perform relay nodes selection, Cooperative Set update and power allocation, resulting in obvious power saving and lifetime extension. Compared with traditional allocation schemes, this method jointly considers the residual energy of sensors and the mean of channel power gains, thus limits the feedback burden and increases the topology stability. Two classical power allocation methods are evaluated for comparison, and numerical results show that the proposed scheme can significantly extend ECD over a wide range of parameter values.

Cognitive radio makes it possible for an unlicensed user to access a spectrum opportunistically. This paper addresses the problem of power control in cognitive radio networks, to maximize the system utility in the presence of interference temperature constraint. Penalty function is applied in the problem formulation to take into account the transmit power budget and interference temperature constraints, which is solved efficiently by geometric programming. In the proposed distributed power control scheme, users exchange "price" messages which indicate the negative effect of interference at the receivers. Given this set of prices, each transmitter updates power levels on multiple channels using gradient descent method. It is proved that the proposed algorithm converges to the global optimum when operated in an totally asynchronous manner. The performance of the proposed scheme is investigated by numerical results in the end.

In this paper, a novel maximum Doppler spread estimation algorithm is presented for OFDM systems with the comb-type pilot pattern. The least squared estimated channel frequency responses (CFR's) on pilot tones are used to generate the auto-correlation matrices with/without a known lag, from which the time correlation function can be measured. The maximum Doppler spread is acquired by inverting the time correlation function. Since the noise term will bias the estimator, the estimated CFR's are projected onto the delay subspace of the channel to reduce the bias term as well as the computation complexity. Furthermore, the subspace tracking algorithm is adopted to automatically update the delay subspace. Simulation results demonstrate the proposed algorithm can quickly converge to the true values for a wide range of SNR's and Doppler spreads in Rayleigh fading channels.

With mobile WiMAX being widely deployed, providing a feasible solution for location service in mobile WiMAX is imperative and significant. In this paper, we propose a novel mobile WiMAX positioning scheme, which includes four steps: downlink preamble fast detection (DPFD), positioning algorithm selection mechanism based on the number of detected preambles, media access control (MAC) message signaling, and location calculation. In the first step, neighbor information carried by MOBNBR-ADV is introduced to decrease the neighbor BSs' preamble detection time. Meanwhile, Uplink Ranging Assistant Downlink-Time Difference of Arrival (URAD-TDoA)/uplink ranging assistant-cell ID (URA-CelllD) are proposed in selection mechanism for two/one preambles detected. Furthermore, new messages and detail message signaling for positioning are designed in MAC layer. By simulations, we show that the proposed positioning scheme can be a promising candidate for location service in mobile WiMAX systems.

Hybrid automatic repeat request (HARQ) protocol typically operates in multi-process stop-and-wait (SAW) mode to fully utilize channel capacity. A prior packet, due to retransmission(s), may arrive at the receiving side later than the packets that follow it but use other HARQ processes, thus leading to out-of-order reception. Medium access control (MAC) layer is responsible for packet reordering operations so as to offer in- sequence delivery to upper layer. An arriving packet should be temporarily stored in the reordering buffer, if there is at least one prior packet that has not arrived yet. Nevertheless, protocol stalling may occur if a packet is discarded at the transmitter due to excessive failed retransmissions, or if a negative acknowledgement (NACK) signal is inversed as an acknowledgement (ACK). A timer-based mechanism is suggested by 3GPP to handle protocol stalling. In this paper, we propose an adaptive timer- based stalling avoidance mechanism as the enhancement to the current 3GPP specifications. In our proposal, the duration of the timer is set or updated through dynamic monitoring on the status of each HARQ process. We show with illustrative examples and simulations that the proposed mechanism reduces considerably extra packet delay incurred during reordering operations.

We consider a two-hop relaying network in which orthogonal frequency division multiplexing (OFDM) is employed for the source-to-destination, the source-to-relay and the relay- to-destination links. Amplify-and-forward (AF) and decode-and- forward (DF) policies are both discussed with or without two-hop diversity, respectively, for the relaying network with a sum-power constraint. An unified approach is used for optimal power allocation in the four different relaying scenarios. First, equivalent channel gains are developed for any given subcarrier pair in each scenario, and then optimal power allocation can be obtained by applying the classic water-filling method. Moreover, we provide the proof to the optimality of sorted subcarrier pairing for AF and DF relaying without diversity, which, combined with optimal power allocation, can offer further performance gain.

In this paper, influence of spatial correlation on codebook-based precoding technology is analyzed. Optimum pre- coder distribution under spatial correlated channel is achieved at first, which is no longer isotropical on the unitary matrix (vector) set. Selection probability of the matrix (vector) in codebook is not uniform too. Then, a novel codebook design is presented for spatial correlated channel, which is termed as nonuniform codebook. Codebook is designed as function of spatial correlation characteristic of channel and presents a nonuniform quantization of unitary vector set. Smaller quantization error and higher spectral efficiency can be achieved by proposed codebook design than that of traditional fixed uniform codebook design, with the cost of slight feedback overhead increasing.

In the multiuser spatial multiplexing multiple-input multiple-output (MIMO) system, the joint transmitter-receiver (Tx-Rx) design is investigated to minimize the weighted sum power under the post-processing signal-to-interference-and-noise rate (post-SINR) constraints for all subchannels. Firstly, we show that the uplink-downlink duality is equivalent to the Lagrangian duality in the optimization problems. Then, an iterative algorithm for the joint Tx-Rx design is proposed according to the above result. Simulation results show that the algorithm can not only satisfy the post-SINR constraints, but also easily adjust the power distribution among the users by changing the weights accordingly. So that the transmitting power to the edge users in a cell can be decreased effectively to alleviate the adjacent cell interference without performance penalty.

In order to achieve the improved diversity over the original coded cooperation in fast fading channel, the novel cooperation strategy with hierarchical modulation is proposed in this paper, where users send both their own as well as their partners' parity bits with hierarchical error protection during the cooperation frame. Only the frame-level synchronization is necessary when using the proposed strategy, which facilitates the implementation on the uplink. The bounds for the block-error rate (BLER) of the proposed strategy are analyzed and the simulation results given.

In current wireless system performance evaluation, separate link and system level simulators are needed due to less computation complexity. The link-to-system (L2S) interface method to interconnect two simulators is essential and need careful definition. Exponential effective signal-to-interference-and-noise ratio mapping (EESM) is a typical L2S interface method suitable for evaluation of orthogonal frequency division multiplexing systems. When itpsilas used in simulation, all the sub-carriers for one user have to use the same modulation and coding scheme. In this paper, two modified L2S interface EESM methods are presented based on the idea that a high-level modulation symbol could be equivalently converted to several low-level modulation symbols with different reliability. As a result, usage of EESM can be extended to the situation that sub-carriers for one user use different modulation schemes.

Network coding is seen as a promising technique to improve network throughput. In this paper, network coding in cooperative relay networks and user cooperative networks is investigated and an optimized power allocation scheme is provided. By comparing with traditional relay forwarding in a simple two-user scenario, network coding shows a better system performance with a lower hardware cost and higher spectral efficiency, and this scenario can be extended to general multi-user environment without much cost.

In this paper a novel Weighted Proportional Fair (WPF) scheduling algorithm is proposed. Traditional Proportional Fair (PF) algorithm cannot exploit the inherent near-far diversity given by pathloss and cannot achieve maximum best-effort service utility under multicell scenario. WPF overcomes this deficiency. The weight value and weight factor are introduced to WPF which enable WPF utilizing near-far diversity to reduce the inter-cell interference. All the asymptotic analysis and numerical results show when weight factor chooses a small value, WPF scheduling can enhance both the best-effort service utility performance and throughput performance compared to PF scheduling in multicell network.

In this paper, a parametric channel estimation algorithm applicable to uplinks of orthogonal frequency division multiple access (OFDMA) systems whose subcarriers are pseudo-randomly allocated is proposed. By exploiting pilot hopping, estimation of signal parameters via rotational invariance technique (ESPRIT) is employed to estimate the path delays of the sparse multipath fading channel. From the delay information, a channel interpolator utilizing global pilots, which can be irregular distributed, is derived to estimate the channel state information on the desired tones. Moreover, a simple method of estimating the time correlation of the channel taps is introduced and integrated in the proposed algorithm. Simulation results demonstrate that the proposed algorithm outperforms the local linear channel interpolator within a wide range of SNRpsilas and Dopplerpsilas.

An energy efficient cooperative MIMO selection scheme is proposed for uniform load distribution in cluster based wireless sensor networks. The intrinsic data flow direction in multi hop cluster based sensor networks causes uneven load distribution in the network. The transit clusters and the clusters near the base station carry more network traffic than the other clusters. Cooperative MIMO can artistically reduce the per bit energy consumption, Space-Time Block Codes are designed to achieve maximum diversity for a given number of transmit and receive antennas with very simple decoding algorithm. In radio fading channel, STBC require less transmission energy than SISO technique for the same Bit Error Rate and can be employed practically in Wireless Sensor Networks by using the cooperative MIMO scheme. Considering Alamouti and Tarokh space-time block codes, the number of antennas at both the transmission and the reception sides are selected with respect to the cluster load. By using cooperative MIMO transmission instead of SISO, it is shown that the load based adaptive selection of cooperative nodes in clusters renders uniform energy consumption in the network.

Providing voice over IP (VoIP) service in wireless networks is especially challenge for the tight delay requirement and the small voice packet. This paper addresses the unique issues when providing VoIP in TD-SCDMA HSDPA (time duplex division-synchronous code division multiple access high speed downlink packet access) systems. The impact of smart antenna was analyzed, which results in relative small gain of AMC (adaptive modulation and coding). An optimized scheduling and multiplexing scheme combining both time- and code-multiplexing was proposed. The VoIP performance is investigated via simulation. Results are obtained for different scheduling and multiplexing strategies, different AMC and hybrid ARQ (hybrid automatic retransmission request) settings. It was shown that the capacity of VoIP is significant higher than that of dedicated channel bearing voice.

In this paper, the results of the quality of service for VoIP service over TD-SCDMA HSDPA system are presented. The performances of the system with different scheduling algorithms and different retransmission times are simulated and analyzed. Dynamic scheduling, adaptive modulation and code (AMC), dynamic HARQ are implemented in the system-level simulation and some recommends for HARQ channel number and retransmission time and optimality are given.

Installing multiple antennas at user equipments (UEs) may pose great challenges. In virtual multiple-input multiple-output (MIMO) concept, multiple single-antenna UEs can be grouped to transmit signals at the same time. Their signals can be separated at the base station (BS) by the same methods already used in conventional point-to-point MIMO scenarios. An important problem in virtual MIMO application is which users can be scheduled simultaneously to achieve a good balance between various system targets, e.g. aggregate throughput and user fairness. In this paper, a novel scheduling scheme is proposed which combines the advantages of proportional fair and maximum rate rules, based on successive interference cancellation (SIC) MIMO receiver architecture. Simulation results show that the proposed scheme can achieve a good tradeoff between system throughput and user fairness. Compared with other scheduling schemes already proposed in virtual MIMO context, e.g., orthogonality pairing scheduling (OPS), the proposed scheme can be justified by its low computational complexity and flexibility.

Multimedia broadcast/multicast service (MBMS) is an important part of the UTRAN evolution and supports downlink streaming and download-and-play type services to large groups of users. For enhanced MBMS (E-MBMS) under 3GPP long term evolution (LTE) system, there are two ways to transmissions being performed: multi-cell transmissions and single-cell transmissions. One requirement identified to be supported is that the capability of the network to detect at least one MBMS user interested receiving one given MBMS service in the cell which belongs to above scenarios. It is significant to avoid unnecessary MBMS transmission in a cell where there is no MBMS user especially for single-cell transmissions mode. In this investigation, a low complex method is discussed to solve the detection on MBMS interested users in one cell and we also introduce code diversity strategy into the feedback signal transmission. Theoretical analysis and simulation results all show that the efficiency of proposed detection scheme is obvious which can dramatically reduce the average MBMS service polling time and control overhead.

This paper presents a general detection method for linearly constructed distributed space-time codes (DSTC) in amplify-and-forward (AF) mode of wireless cooperation networks. A two-phase model for the network is utilized. In the first phase, multiple-antenna transmit nodes send signals simultaneously. Then the relays encode received signals with linearly constructed DSTC. Since linear dispersion (LD) codes subsume all linearly constructed STCs as special cases, when such DSTCs are used in AF mode of the network, a LD equivalent system model which is similar to V-BLAST structure is given in this paper. Thus, detection algorithms for V-BLAST can be utilized for the model effectively. Especially, linear complexity detection algorithms can be used in the network for practical implementations. Simulation results prove the LD equivalent model valid at last.

We consider a multi-hop wireless sensor network in which a large number of sensor nodes are grouped into cooperative clusters. Multi-hop transmission is carried out between the source and the destination nodes by concatenating consecutive cluster-to-cluster hops. For each hop, both the transmit and the receive clusters can exploit node cooperation such that cooperative distributed multiple-input multiple-output (MIMO) channels can be formed. As proposed in [1], a time-division protocol is employed for transmissions within a cluster and between clusters, i.e., the intra-cluster slot is used for broadcasting within the transmit cluster, and the inter-cluster slot is used for transmissions between clusters. Distinguished from the scheme in [1] that space-time codes (STC) are utilized for inter-cluster transmissions, random beamforming is proposed in this paper, which is shown to outperform STC in term of energy efficiency provided that the number of nodes within receive cluster is adequately large. We demonstrate that even with moderate number of nodes within receive cluster, e.g., 10 nodes, random beamforming can offer higher energy efficiency for inter-cluster links, at 5% outage rate. The "random" nature incorporated in random beamforming scheme assigns the clusterhead node within receive cluster in an alternate manner, thus balancing energy consumption within receive cluster.

In practical systems, due to the time-varying radio channel, the channel state information (CSI) may not be known well at both transmitters and receivers. For most of the current multiuser multiple-input multiple-output (MIMO) schemes, they suffer a significant degression on the performance due to the mismatch between the true and estimated CSI. To alleviate the performance penalty, a robust downlink multiuser MIMO scheme is proposed in this paper by exploiting the channel mean and antenna correlation. These channel statistics are more stable than the imperfect CSI estimation in the time-varying radio channel, and they are used, in the proposed scheme, to minimize the total mean squared error under the sum power constraint. Simulation results demonstrate that the proposed scheme effectively mitigates the performance loss due to the CSI mismatch.

The energy saving mechanism is very important for supporting the mobility and extending the battery life in the wireless packet access network. For example, the sleep-mode has been standardized in both IEEE 802.16e and 3G long term evolution (LTE) systems. According to the definition in the standards, an adaptive energy saving mechanism (AESM) for enhancing the standardized energy saving mechanism (ESM) is proposed, in which the sleep interval is determined by both the system load and traffic properties. The proposed AESM determines the initial sleep interval and the period sleep interval adaptively according to the proposed parameters gamma and Psi, which are the multiplying step size of the sleep interval and the traffic's property respectively. In order to demonstrate the proposal validity, the theoretical analysis based on the Markov chain model is presented, and the total energy consumption for the heavy load and the light load is compared. Simulation results illustrate that the proposed scheme can achieve a good balance between the energy saving efficiency and the transmission response time delay.

In TD-SCDMA systems, the multi-user detection (MUD) and adaptive smart antenna techniques are adopted in both uplink and downlink. Considering the complexity of cancelling inter-cell interference, the technique of MUD in this paper mainly focuses on the interference suppression of intra- cells. The adaptive smart antenna technique is adopted to suppress the interference from both intra- and inter-cells. Since these two motioned techniques are not adopted in WCDMA and cdma2000 systems, the corresponding capacity and load evaluating models for TD-SCDMA systems must be reinvestigated. In this paper, a theoretical analysis model for CDMA capacity constraints is presented firstly when employing the adaptive smart antenna and MUD techniques in both uplink and downlink, in which the factors of average beamforming interference and intra-cell MUD factors are proposed for evaluating the impacts of adopting these key techniques. Based on the theoretical model, the pole capacity and load estimation models are deduced. The simulation results demonstrate the theoretical analytical models specified for TD-SCDMA systems available. According to our proposals, the TD-SCDMA network planning and optimization can be processed efficiently.

In this paper, a framework is presented to analyze the performance of multiuser diversity (MUD) in multiuser point-to-multipoint (PMP) MIMO systems with antenna selection. Based on this framework, the tight closed-form expressions of outage capacity and average symbol error rate are derived for the multiuser transmit antenna selection with maximal-ratio combining (TAS/MRC) system, by which we show how and with what characteristics antenna selection gains, MIMO antenna configurations and fading gains impact on the system performance, with an emphasis on the study of multiuser diversity influence. From both theoretical and simulation results, our study shows that in multiuser PMP TAS/MRC systems an diversity order equals to the product of the number of transmit antennas, number of receive antennas and number of users can be achieved; what's more, users plays a key role in the system performance and can be viewed as equivalent "virtual" transmit antennas, which is the source of the multiuser diversity inherent exists in the multiuser system. This kind of diversity can be efficiently extracted in the design of multiantenna systems.

Double space time transmit diversity (D-STTD) is a promising open loop MIMO scheme for spatial rate 2 in the system with four transmit antennas, which has been adopted in LTE and 802.16e. In this paper, we propose an adaptive HARQ scheme based on quasi-orthogonal space-time block coding (QOSTBC) for D-STTD system under quasi-static channel environment. "Adaptive" means that there are two possible coding forms of QOSTBC and one of them will be chosen according to the lower inter-antenna interference in the equivalent channel matrix. At the same time, the adaptation leads to the employment of a low-complexity linear detection at the receiver. With one-bit feedback, this adaptive HARQ scheme is demonstrated to exploit more gain than the traditional Chase- Combing or Increment Redundancy scheme.

Hybrid automatic-repeat-request(HARQ) scheme can be incorporated with the linear precoder in multi-input multi- output(MIMO) transmission to ensure highly reliable communications. To fully utilize type-I HARQ diversity gain especially in the slow fading channels, we propose the optimal design principle of linear precoders, whose column vectors are orthogonal to each other correspondingly. Simulation results demonstrate the effectiveness of these precoders in reducing the detection bit-error rate and increasing the unified throughput.

In this paper, we propose a new multimedia broadcast network architecture, in which the cellular base stations act as digital fixed relays and cooperate with the broadcast station to deliver messages to the whole network, forming the so-called cooperative broadcast network . This concept fully exploits the benefits of cooperative relaying . Through the evaluation of coverage and throughput by theoretical analyzing and simulation, it is consistently shown that this scheme can dramatically extend the broadcast station coverage range without any capacity penalty, and it can also provide very high data rate service in an almost-ubiquitous manner throughout the network. Also we can come to the conclusion that the relay strategy is especially efficient for mobile terminals at the edge of the cell that would have poor channel conditions.

Frequency allocation is a critical issue for cellular relaying networks. In this paper we present spectrum-efficient frequency allocation policies that are applicable for fixed two-hop cellular relaying networks. The frequency allocation problem is decomposed into two sub-problems: inter-cell and intra-cell frequency allocation. The goal is to make more users to be served with satisfactory service quality. Through numerical analysis, the basic inter-cell frequency allocation scheme is proposed, including frequency reuse pattern and reuse factors for each type of links. Then we propose a method to realize safe intra-cell frequency reuse, in the sense that higher spectrum efficiency is achieved through this tighter frequency reuse while the signal- to-interference (SIR) quality for the links of concern is still guaranteed. Simulations show that our schemes are beneficial to obtain more satisfied users and low outage ratio, when compared to the cases without intra-cell frequency reuse scheme and the cases with fixed intra-cell frequency reuse scheme.

The paper investigates the advantages of employing spatial reuse on the deployment of relay stations in a multi-hop network. To quantify the gain and interference from spatial reuse, the concepts "interference level" and "reuse factor" are introduced innovatively. By comparing the performance of relay-based multi-hop systems with conventional single-hop systems, we conclude in this paper that a large number of relay stations can lead to better spectral efficiency if the distance is long enough. The relationship between optimal number of hops of a multi-hop chain and distance from the source station to the destination station is also derived.

In this paper, a method based on max SINR criterion is proposed to mitigate the interuser interference for downlink multiuser spatial multiplexing MIMO systems. Unlike Zero Forcing (ZF) scheme in which the SNR is decreased when the interference is eliminated completely, max SINR method makes a compromise between noise and interuser interference. When the number of substreams is larger than the difference between the number of base station antennas and the sum of interference mobile station antennas, the ZF is infeasible. An existing Coordinated tx-rx Block Diagonalization(COOR BD) method uses a preprocessing at receiver to cancel the interuser interference. However it cannot obtain more receive diversity gain due to the preprocessing. Analysis and simulation show that the max SINR scheme has better performance than the ZF method. Moreover when the ZF is infeasible, the max SINR scheme can obtain more receive diversity gain than COOR BD in two users case.

The inter-cell interference in the downlink for IEEE 802.16 wireless metropolitan area network (MAN) mainly depends on the distance between the base station (BS) and the subscriber station (SS). In order to improve the spectrum efficiency and make the frequency reuse factor approach 1.0, the wireless scheduling for supporting the diverse quality of service (QoS) should consider the other-cell interference. In this paper, the wireless packet scheduling algorithms are based on the jointly considering inter-cell interferences, service status, and channel conditions. The advanced scheduling algorithms are proposed for Unsolicited Grant Service (UGS), real time polling service (rtPS), non real time polling service (nrtPS), and best effort (BE) services. Numerical results reveal that the proposed interference coordination based scheduling algorithm improves the overall network throughput, provides an efficient user throughput, and guarantees the diverse QoS requirements.

The inter-cell interference in the downlink for IEEE 802.16 wireless metropolitan area network (MAN) mainly depends on the distance between the base station (BS) and the subscriber station (SS). In order to improve the spectrum efficiency and make the frequency reuse factor approach 1.0, the wireless scheduling for supporting the diverse quality of service (QoS) should consider the other-cell interference. In this paper, the wireless packet scheduling algorithms are based on the jointly considering inter-cell interferences, service status, and channel conditions. The advanced scheduling algorithms are proposed for Unsolicited Grant Service (UGS), real time polling service (rtPS), non real time polling service (nrtPS), and best effort (BE) services. Numerical results reveal that the proposed interference coordination based scheduling algorithm improves the overall network throughput, provides an efficient user throughput, and guarantees the diverse QoS requirements.

The time-variation of channels during one OFDM symbol destroys the orthogonality among subcarriers and results in intercarrier interference (ICI), which may detail substantial error performance. Assumed channels vary in linear fashion during one OFDM symbol, we propose an iterative partial-ICI-cancellation (PIC) based detector for OFDM systems with linear modulation over doubly-selective Rayleigh fading channels. The tentatively detected information of channel and data are fed back to regenerate the ICI and then partially subtracted from the received signals. The optimal partial ICI cancellation factor (PICF) is determined by minimizing the mean square error (MSE) of data estimation. The proposed detector iteratively renews the channel estimation and data detection after PIC, and results in performance enhancement. Based on Jake's model for the Doppler effects, the bit error ratio (BER) performance of the proposed detector is illustrated for OFDM systems with phase-shift keying (PSK) and quadrature-amplitude modulation (QAM) in Rayleigh fading channels at several speeds.

Current deployed emergency communications systems are only available to the rescuing workers. In this paper, a framework of wireless emergency communications is proposed for common communications in the disasters based on relaying and cognitive radio. In this framework, relaying provides small coverage expansion and high capacity for common communications. On the other hand, cognitive radio based frequency lowering provides large coverage expansion and low system capacity for special number communications. The coverage performance is evaluated by the calculation and simulation. To balance the tradeoff between coverage and capacity, both two-hop relaying and cognitive radio are adopted appropriately to satisfy the requirements of emergency communications according to their characteristics. The performance of the proposed framework is also investigated in this paper.

In this paper, channel aware adaptive resource allocation scheme in two-hop wireless relay networks (WRNs) is proposed to achieve maximum system throughput and better delay performance. Both the routing selection and resource scheduling algorithm are designed to accomplish the resource allocation scheme. Considering the network throughput, a routing algorithm is proposed to select the optimal RS based on an optimization problem. A fairly resource scheduling algorithm based on the Signal-to-Noise-Rate (SNR) is provided, which combined both the link and data scheduling. Both the routing and scheduling algorithms are designed with channel state considered. Theoretical analysis and simulation results show our proposed channel aware resource allocation scheme is efficient and can enjoy a good network performance in two-hop WRNs.

This paper investigates the multiple-input multiple-output (MIMO) antenna subset selection combined with space-time coding (STC) in retransmit system, e.g. hybrid automatic repeated request (HARQ). As we know space-time coding (STC), transmit antenna selection (TAS), as well as some receive diversity combining techniques such as selection combing (SC) and maximal ratio combining (MRC) offer considerable diversity gain. Therefore, they are combined in a system named TAS/STBC/HARQ which has been investigated in this paper. The performance of bit error rate (BER) is analyzed in flat fading channel. The numerical results based on the SC and MRC reveal that the scheme achieves great diversity gain. The diversity gain is greater than the MIMO transmit antenna subset selection with STC, when no HARQ is utilized, except for little coding gain loss and larger time delay. Moreover, our system also has the advantage of throughput with turbo encoder.

This paper introduces two kinds of receivers, chip-level receivers and symbol-level receivers with Grake receivers. We propose an adaptive finger selection scheme of symbol- level receivers and it reduces almost a half of original complexity. When channel paths are dense, for symbol-level receivers with non-ideal channel estimation, we develop a receive scheme which combines channel estimation and receive finger selection. It increases system reliability effectively. We introduce serial interference cancellation (SIC) and soft-decision SIC to suppress multiple antennas interference. At the same time, it refers that soft-decision is necessary for V-BLAST structure of multiple antennas multiplexing. At last, simulation results prove the conclusion valid in this paper.

In this paper, a framework to study the error performance of multiuser diversity in point-to-multipoint (PMP) MIMO transmit antenna selection networks is presented. Based on this framework, we derive the exact closed-form symbol error rate formula in terms of antenna selection gain, MIMO configurations, multiuser diversity and amount of fading gain to study the insight interaction between these factors. Our analytical results indicate that, (1) in PMP MIMO antenna selection system with large number of receive antenna, a diversity order equals to the product of the number of transmit antennas, receive antennas and users can be extracted; (2) the number of users provides the same effect on the error performance as that of the transmit antenna, and users can be viewed as "virtual" transmit antennas which is the inherent multiuser diversity; and (3) largest performance gain is achieved by equally distributing antennas over transmit and receive ends.

This paper develops a framework to analyze the outage capacity of multiuser diversity in a multiuser MIMO transmit antenna selection with maximal-ratio combining (TAS/MRC) system. A closed-form expression of the system outage capacity is derived, through which we show how and with what characteristics the MIMO configurations, the number of users and the multiuser diversity affect the outage capacity performance. Both the analytical and simulation results show that (1) the outage capacity increases with the increase of mean of effective average SNR and decreases with the increase of variance of the effective average SNR; (2) to obtain a higher outage capacity, the number of receive antennas should be no more than that of transmit antennas. This paper has presented some conclusions which can be used for the efficient design of multiuser MIMO systems.

In this paper, tabu search (TS) is applied to the detection algorithm of MIMO system, which is originally designed to find the approximate solution of combinatorial optimization problems. Resorting to an original two embedded cubes stereograph, we give a simple illustration of TS process. As a simple add-on to traditional suboptimal detectors, TS provides the potential of moving toward the best ML solution. The method of skipping out of the search under a certain condition in advance is proposed, leading to the flexible tradeoff between the performance and the complexity. Simulation results show that the advantage of TS detection on performance comparing with the traditional detection is great, especially when the system has more transmit-antennas.

In orthogonal frequency division multiplexing (OFDM) systems, conventional channel estimation techniques using comb- type preambles and interpolation between pilot subcarriers give relatively large mean square errors (MSEs) at the edge sub- carriers. Furthermore, the spacing between pilot subcarriers in the frequency domain has to be close enough according to sampling theorem. To solve these problems, an iterative discrete Fourier transform (DFT)-based channel estimation with comb-type pilot-aided is proposed in this paper. The complete channel frequency responses (CFRs) including virtual subcarrier positions are estimated by recursive method with the small size of DFT/Inverse DFT. Simulation results show that the proposed algorithm outperforms the conventional linear minimum mean square error(LMMSE) algorithm using comb-type preamble.

Cyclic delay diversity (CDD) is an attractive approach to achieve spatial and multipath diversity. Its simplicity and conformability with current standards makes it desirable for orthogonal frequency division multiplexing (OFDM) systems. In this paper, we propose the transmission diversity scheme with hierarchical modulation for the broadcast service in the mobile communication system, where CDD is applied between the different cells and space-time block coding (STBC) or CDD is used inside the cell. A hierarchical modulation scheme is adopted in order to provide the layered transmission in the broadcast area with high frequency efficiency. Computer simulation results show that the proposed transmit diversity technique increase the diversity order greatly. Furthermore, this technique with hierarchical modulation scheme outperforms that with the common modulation scheme when different prioritized streams are transmitted.

The capacity of relay channel is determined not only by the number of relays but also the relations among them. Cooperation among relays will greatly improve the network capacity by further reducing information uncertainty. Based on this theory, this paper introduces cooperative two-relay channel models with or without path loss, as well as the method for their capacity analysis. In these models, the work mode of the relays has two schemes, that is, the two relays select the same or different codebooks respectively. On calculating the capacity, we will analyze it without path loss firstly. Then based on this very result, we will further analyze the capacity with path loss. A numerical example without path loss is given in order to certify the result. It shows that the capacity is confined to the combination of the broadcast channel and multi-access channel and by finding the best way of power allocations we can achieve the maximum channel capacity.

WiBro (wireless broadband), the standard of high-speed portable internet (HPI) based on OFDMA/TDD and IP network in Korea, is the subset of consolidated version of IEEE 802.16e wireless MAN standard. In this paper, the architecture and key physical layer technologies of WiBro are briefly introduced, whereas the convolutional turbo code (CTC) with high-order modulation is presented in detail. The performance of convolutional Turbo coded WiBro system with QPSK, 16QAM and 64QAM over ITU-R channel models is simulated, where pilot tones aided channel estimation and 1-tap equalization are applied. Simulation results show that the good BER performances of CTC with short code block size in WiBro systems, which facilitates the flexibility of channel resource allocation. Given the same code block size, CTC outperforms TC (turbo codes) and CC (convolutional codes).

In cognitive radio network, power control is necessary to not only decrease the interference among the unlicensed users, but also avoid the negative effect to the licensed users. In this paper, a noncooperative power control model is proposed for the unlicensed users using game theory. In order to restrict the interference to the licensed users, an exponential part indicating the effect to the licensed users is added into the pricing function. Through game theoretic deduction, it is obtained that a unique Nash equilibrium solution exists under appropriating parameter value of the payoff function. Further, the Nash equilibrium solution of the proposed power control game with exponential pricing is Pareto optimality and achieves maximum total throughput under strict constraint of the interference temperature limitation. The appropriate value of the new parameter in the pricing function is discussed. The performance of the proposed power control algorithm is investigated by numeral results.

This paper represents a method based on generalizing Delbrouck's algorithm for calculating the access capacities of multi-service time division duplex-code division multiple access (TDD-CDMA) networks. The method models the system as a multi-service model with state dependent soft blocking probabilities, and it uses the soft capacity limit caused by TDD-CDMA system in calculating the call blocking rate of multi-services. The traffic models used in this method are insensitive to the service time distribution and thus the method is very robust for applications. So it is more accurate than multi-dimensional Erlang-B formula, which does not consider the soft capacity, and it is also simpler than resolving the complex linear system equations with soft capacity. The paper provides both analytical results and simulation results to support the method, and these results match. Thus the proposed method can be used in TDD-CDMA network dimensioning and optimizing.

In cognitive radio network, the interference of the unlicensed users to the licensed users should be limited under interference temperature constraints. In this paper, the optimal power control scheme of a network is analyzed without interference temperature constraints firstly. Based on this, considering interference temperature constraints, the optimal power control in cognitive radio network is modeled as a concave minimization problem. Some useful properties of the power control optimization problem are exploited. According to these properties, an improved branch and bound algorithm which is more efficient than the general branch and bound algorithm is proposed for optimal power control optimization problem in cognitive radio network.

This letter develops a framework to analyze the multiuser diversity (MUD) gain in multiple-input multiple-output (MIMO) transmit antenna selection with a maximal-ratio combining (TAS/MRC) system, through which the transmitter selects the optimal antenna out of the total transmit antennas based on the channel state information (CSI) feedbacks. Over a flat-fading Rayleigh channel, a tight analytical closed-form expression of the MUD gain in terms of outage probability is derived. The analytical results show that 1) the MUD system can achieve an order of diversity equal to the product of the number of users, number of transmit antenna, and number of receive antennas; 2) users can be viewed as equivalent "virtual" transmit antennas, and the number of users has a great impact on the system outage probability

We investigate good coprime interleavers that perform well in turbo codes and allow for memory-efficient implementation. We first evaluate the spread and the randomness properties of these interleavers using the cycle correlation sum (CCS) and the variance of the second order spread spectrum (VSSS) criteria, respectively. A critical parameter cpoweris introduced for interleavers whose lengths are power of 2. It is found that a large cpowertypically associates with a small CCS value, indicating a good minimum spread of the coprime interleaver, but the degree of randomness decreases with growing cpower- We next develop rules on choosing good parameters that strike a good balance between minimum spread and degree of randomness. Simulation results confirm that the coprime interleavers designed from our rules perform as well as or better than S-random interleavers.

This paper proposes a promising detection that applies PSO (particle swarm optimization) as the selection of surviving paths in QRM detection for the coded MIMO system, named as QRM-PSO. Because only a few children nodes's metric are needed to calculate in the PSO search process, QRM-PSO can cut down the complexity further, while keeping the same performance as QRM due to the quasi-random movement of the particles. Simulation results demonstrated that the advantage of QRM-PSO in complexity is obvious especially when antenna number and modulation level are high. The required real multiplication number of QRM-PSO is only 0.4% of that of QRM when transmit antenna number is 20 and 16QAM is employed.

This paper proposes a novel symbol timing synchronization method for localized OFDMA uplink system. Two neighboring pilot symbols are designed for timing synchronization utilizing the property of successive subcarrier assignment. For OFDMA separation, there is almost no inter-user interference, which is very beneficial for timing synchronization. At receiver, the position of the pilot symbols can be found by correlating the received signal with the local pilot replica. For better correlation result, Zadoff-Chu sequence is employed as the pilot data for its ideal autocorrelation property, which can well suppress the inter-multipath interferences. Furthermore, a novel timing metric is constructed according to the obtained correlation profile by using the special pilot structure. The timing metric is proportional to the received SNR and has a plateau since the CP length is designed larger than the maximum channel delay. The timing estimator is dedicated to locate in the middle position of the ISI-free CP part for this timing offset will not degrade system BER performance. Simulations results demonstrate that the proposed timing estimator can work well in localized OFDMA uplink system. As long as the maximum channel delay is shorter than the CP length, it can reach the same BER performance with that of ideal synchronization.

In this paper, we present the adaptive multiuser frequency-time domain radio resource allocation model which adaptively allocates the radio resource jointly in the frequency and time domain to exploit the frequency diversity and time diversity as well as multiuser diversity. Then we give an in-depth capacity analysis of the proposed radio resource allocation with frequency-time domain power adaptation in the downlink OFDMA systems and draw a comparison with the conventional frequency domain resource allocation method. Simulation results show that: 1) the proposed resource allocation method achieves much higher spectral efficiency than the conventional frequency-domain resource allocation; and 2) for the proposed two-dimensional allocation method, the performance of water-filling power allocation is almost the same as that of the equal power allocation, especially when the number of user is large

A crucial aspect for adaptive bit and power loading algorithms is to determine all usable subchannels. In this paper, a simplified bandwidth optimization method is proposed to search for all usable subchannels for loading algorithms which aim at the minimization of power consumption with constraint of constant data rate and target bit error rate (BER). Based on this method, an efficient loading algorithm is developed. Simulation results show that the proposed algorithm can achieve the same bit allocation results to that of the well-known Hughes-Hartogs and Fischer et al. algorithm. This algorithm is appropriate for OFDM systems in time-varying channels due to its low complexity.

Efficient radio resource allocation is essential to provide quality-of-service (QoS) for wireless networks. In this paper, we propose an adaptive multiuser radio resource allocation model for the downlink of OFDMA system, which efficiently exploits the time diversity, frequency diversity as well as multiuser diversity in the time, frequency and user domain, respectively. According to the allocation algorithm's computational complexity, two different-complexity adaptive resource allocation algorithms algorithm A and algorithm B - are proposed which adopt a two-step allocation method to reduce the scheduling complexity and meanwhile improve the scheduling performance. Simulation results show that while the performance of algorithm A and B is slightly different, both of the proposed algorithms yield much higher spectral efficiency and much lower outage probability, which are flexible and efficient for the downlink of OFDMA systems

This paper investigates a new ARQ method for turbo coded MC-CDMA systems in the multipath fading environment. Some typical phenomena were observed, then a new parameter to control the ARQ protocol was defined. Encouraged by the prediction of BER in the EXIT chart, we compute a threshold for the new parameter. Simulation results show that the improved ARQ method decreases the bit error rate in less system cost and complexity.

In this paper, we present the theoretical work (model) of the radio resource allocation (RRA) of DS-CDMA reverse link (uplink) and forward link (downlink) based on QoS constraint models. Our goal is to optimally allocate the users' data rate and power levels to minimize the total transmission power under each accessing user's QoS constraint model, i.e., taking into account user's application BER and data rate requirements. We show that through strict theory deduction, the proposed model provides the optimal joint data rate and power allocation for both the reverse link and the forward link in multimedia DS-CDMA systems.

This paper presents a new efficient bit and power loading algorithm for orthogonal frequency division multiplexing (OFDM) systems, which aims to minimize the transmit power while maintaining a constant data rate and target bit error rate (BER). This algorithm is based on greedy allocation approach. After grouping, sorting and clustering, the greedy allocation procedure is performed over clusters other than over all subchannels. Compared with conventional optimal loading algorithms, the proposed algorithm can reduce the algorithmic complexity significantly, and the performance degradation may be negligible if algorithmic parameters are selected appropriately. Simulation results indicate advantages of the proposed algorithm.

Code division multiplex access with cyclic prefix (CP-CDMA) is regarded as one of the best candidates for the broadband wireless communication systems in the uplink. This paper proposes a selective parallel interference cancellation (SPIC) for uplink CP-CDMA. With less complexity and good resistance to near-far effect, the S-PIC can achieve better bit error rate(BER) performance than the conventional interference cancellation. Computer simulation demonstrates its effectiveness and conclusion is followed.

OFDM combined with CDMA has emerged as an attractive technique due to its low equalization complexity and good performance in multipath fading channels due to frequency Rake receiver. Using the transmitter diversity scheme and layered space-time (LST) architecture with OFDM-CDMA, high spectral efficiency and good error rate performance can be achieved at the same time. In this paper, the transceiver structure in OFDM-CDMA with multiplexed space-time block codes (STBC) is proposed, in which the number of receive antennas can be less than that of transmit antennas. Computer simulation demonstrates effectiveness of this detector and conclusion is followed

This paper proposes a novel detection algorithm for multiple-input multiple-out (MIMO) code division multiplex-orthogonal frequency division multiplex access (CDM-OFDMA) system in the uplink. Vertical Bell Laboratories Layered Space-Time (V-BLAST) detection is processed only after despreading/combining at the receiver, which not only achieves good frequency diversity gain but also has low implementation complexity. Parallel interference cancellation (PIC) algorithm can also be applied to improve the performance of systems with heavy loads. Computer simulation demonstrates effectiveness of this detector and conclusion is followed.

This paper proposes a time and frequency synchronization solution for MIMO OFDM systems. The synchronization is achieved using one preamble which is simultaneously transmitted from all transmit antennas in the same OFDM time instant. The synchronization is accomplished sequentially by coarse time synchronization, fractional frequency offset estimation, integral frequency offset estimation and fine time synchronization. Simulation results demonstrate that the proposed synchronization algorithms have a satisfactory performance even at a low SNR in a rich multipath environment. And the synchronization performance in a MIMO channel are superior to those in a SISO channel due to its larger diversity gain.

OFDM-CDMA systems have been regarded as the most promising candidates for future mobile communication systems. This paper explores a novel OFDM-CDMA system with joint time-frequency spreading method proposed. The average bit error probability of this system using maximum-ratio combining (MRC) is derived in a frequency-selective fading channel. Numerical analysis and simulation results indicate in detail that the proposed system outperforms the conventional MC-CDMA system.

Many system load evaluations have been proposed, and some applications, such as admission control strategies, have been discussed. It is observed, however, that, due to the TDD-CDMA specialization in the uplink (UL), i.e., multiuser detection (MUD) technology is used and the transmission is discontinuous per frame, all those schemes which are based on the FDD mode should be carefully investigated for the TDD system. The well-known formulation of UL background noise rise (BNR) for FDD-CDMA is modified and enhanced, and a modified BNR is presented for TDD-CDMA. Pole capacity, load and capacity estimation of the UL based on modified BNR are all described. The distribution of the parameter, j, which is used to define the ratio of other cell to own cell interference, is discussed based on the picocell scenario. Finally, in order to demonstrate the efficiency of the load strategy for TDD-CDMA, an admission control strategy based on modified BNR is evaluated and simulated. All works demonstrate that modified BNR gives a very good representation for capacity and load estimation in TDD-CDMA systems.

Many published channel prediction algorithms focused on the narrow communication systems. In This work we propose a new prediction algorithm for wideband wireless communication systems. Since the frequency elements of channel response have the same correlation characteristic, this algorithm can compute their future frequency channel response with the same channel prediction coefficients based on a certain frequency element. Thanks to the good frequency property, this prediction algorithm only cost slight larger computation than that in flat fading channel. The final numeric results show the prediction performance and complexity of the prediction algorithm.

A wireless token ring protocol (WTRP) built on top of the IEEE 802.11 distributed control function (DCF) provides guaranteed QoS in terms of high throughput and bounded transmission delay. It is also applicable in a small-scale wireless ad hoc network where all nodes can hear each other and where throughput and delay requirements are stringent. As nodes in the network have different traffic styles and the number of nodes ready for transmission is highly dynamic, the aggregate throughput and delay of WTRP is degraded. Furthermore, each node keeps on forwarding the token, even though it is not ready for transmission, thus the power consumed by inactive nodes is high. An energy-efficient wireless token ring protocol is proposed to reduce the power consumption. It is shown that E/sup 2/WTRP could prolong the standby time for inactive nodes two-fold.

We propose an efficient frame-based two-dimensional frequency-time grid (FTG) allocation algorithm to maximize the system throughput while satisfying users' rate requirements in a multiuser and multirate service environment. The FTG scheduling algorithm is done per OFDM frame, allocating each frequency-time grid to different users according to both channel state information (CSI) and users' QoS constraints. The performance of the frame-based FTG algorithm is obtained in a multiuser frequency selective fading environment. The results show that the system using the proposed FTG algorithm has significant lower outage probability and higher capacity which is very near the upper bound (maximum allocation method).

In this paper a simplified differential amplitude demodulation scheme is proposed for 64-DAPSK (differential amplitude and phase shift keying), which needs less quantity of decision thresholds compared with the conventional schemes. The arithmetic mean threshold (AlMT) scheme is proposed and analyzed with the simplified system in AWGN and flat Rayleigh fading channels. By these proposed schemes, system complexity is reduced considerably, but no performance degradation occurs. In the case of channel coding, the concatenated code consisting of an inner convolutional code and an outer Reed-Solomon code can be applied to 64-DAPSK. Compared with coherent 64-QAM system which employs pilot symbols for channel estimation, 64- DAPSK can achieve the performance close to or even better than that of the former by utilizing the additional redundancy for outer coding, provided that the channel SNR is high enough.

In this paper, an effective ARQ (automatic repeat request) scheme is proposed to improve TCP (transport control protocol) performance over wireless networks. Unlike the conventional scheme specified in IS-99 is to limit the maximum retransmission number for per frame, it limits the maximum retransmission number for per packet and can adaptively allocate retransmission number to frames belonging to the same packet. The link layer packet error rate and transmission delay of two schemes are derived in mathematics to compare these two schemes. The Padhye's TCP throughput model is used to evaluate the TCP performance with link layer ARQ. Numerical results demonstrate the proposed scheme can achieve much lower packet error rate with shorter delay and higher TCP throughput than the conventional scheme.

Multi-carrier code division multiplex access (MC-CDMA) is one of the best candidates for the future broadband wireless multimedia communication systems. This work investigates the influence of channel estimation on the performance in MC-CDMA systems and the optimum pilot-to-data power ratio (PDR) is derived. Numerical results are presented and our conclusion is followed.

The paper proposes a scheme to measure and quantify the topology, traffic, number of sources and other factors affecting the performance of ad hoc and gives a mechanism to auto-configure the routing protocol parameters based on the measurements. The factors which have significant effects on the performance are changing frequently, so the parameters of the routing protocols are supposed to reflect the variety and be configured according to the state of the networks. Unfortunately, the currently proposed mobile ad hoc routing protocols lack the mechanism to sense the variation and to configure their parameters dynamically. So we propose a scheme for auto-configuration and the corresponding simulation results show that higher performance is obtained.

The challenges and recent progress of mobility management are first reviewed. The next-generation mobile networks are described. A solution to mobility management in next-generation mobile networks is proposed which adapts mobile IPv6, hierarchical mobile IPv6 and fast handovers for mobile IPv6 into mobile networks. Finally comments on the proposed solution are given.

Compared to uplink (UL), the analysis on downlink (DL) is much more challenging because of the DL power allocation problem. In this paper, we propose some new theoretical approaches to investigate the DL system performance. A new investigation approach for the DL pole capacity, which is based on the total transmission power, is presented firstly. Additionally, a simple theoretical analysis in the downlink power increase estimation due to new or modified bearer for real and nonreal time traffic service is described. Furthermore, an advanced downlink power allocation, based on the dynamic control of the maximum code power, is proposed. An advanced static system level simulator to evaluate capacity is developed. By comparing our analytical results with simulations, we show that our analytical approaches have very good match with simulation results.

The low cost distributed network may be a feasible solution scheme for the wireless networks in the future. Therefore, the wireless ad-hoc networks are taken more attention recently. In this paper, the novel distributed channel access and power control algorithms are proposed for the ad-hoc network based on code division multiple access (CDMA) technology. These algorithms are distributed/autonomous, maintain the required quality of service (QoS) of active links, and make the channel access process efficiently.

This paper presents a handover performance analysis suitable for implementation in TDD-CDMA cellular network. Firstly, RSCP (received signal code power)-triggered and SIR (signal to interference ratio)-triggered hard handover measurement criteria for TDD-CDMA are analyzed theoretically and their performances are compared by simulations. Secondly, the handover parameter T/spl I.bar/margin, which is defined as the margin of measurement value used in adding/dropping users to/from active set or full candidate set to avoid ping-pong effect, is carefully set and addressed. Thirdly, the optimum value of measurement reporting period is investigated. Finally, the influence of measurement error is described. As outcome of these analysis and simulations, some simulation results are illustrated and the conclusion is drawn that SIR-triggered scheme is more available to make measurement criteria. Simulations are carried out in a hexagonal macro cellular network with a dynamic system level simulator.

Data transmission control schemes have significant influence on QoS and system capacity. In this paper, three types of data transmission control scheme are presented and their influences on the system performance are simulated. According to the simulation results, some conclusions are obtained.

In the 3G mobile communication systems, the services consist of symmetric services such as voice service and asymmetric services such as WWW browsing. The TDD mode CDMA systems can adapt itself well to time varying asymmetric traffic. In this paper, a new dynamic channel allocation (DCA) model based on Markov decision programming (MDP) has been established to dynamically adapt the switching point in the TDD radio frame according to the states of the system. Simulation results have shown that it will decrease the system blocking rate and increase the resource usage compared with the fixed channel allocation (FCA) scheme.

The algorithm of the multiuser detector (MUD) based on decision-feedback is analyzed in this paper. The performance of the proposed detector is evaluated and simulated. Numerical and simulation results show that, under ideal power control, this detector is better than the conventional and decorrelating multiuser detectors in terms of BER performance, while in terms of "near-far" resistance, after ranking the signals in descending order of received powers, this detector is still better than conventional and decorrelating ones and finally approaches to the single-user bound.