In this paper, an integrated sensing and communication (ISAC) system was proposed under cell-free architecture with different power allocation schemes for both communication and sensing functions. In addition to using uplink (UL) pilot transmission for channel estimation, a group of pre-designed orthogonal downlink (DL) pilot sequences are inserted and transmitted from each cooperative access point (AP) towards the user equipments (UEs). The inserted DL pilots in cell-free ISAC are utilized for both channel estimation in communication and cooperative localization in radar sensing. Based on the ISAC strategy, a power allocation scheme is proposed with the objective of minimizing the maximum channel estimation error for each user, under the power constraints of APs and minimum mean square error constraints of the localization. The full-power scheme which APs consume all the available power during the DL phase is also studied and analyzed. The performance of the proposed ISAC strategy is evaluated under a realistic highway scenario, and compared to the existing non-DL strategies. Additionally, we investigate the impact of the pilot ratio under a constrained signal length, as well as the impact of the pilot proportion that the pilot length to the entire signal frame length. Simulation results show that the performances of both channel estimation and localization can be significantly improved at a relatively low cost of extra power needed for APs. Moreover, the analysis provides insights into optimizing the DL/UL pilot ratio and pilot proportion which can significantly enhance both channel estimation and localization accuracy, while ensuring sufficient resources remain available for data payload.

As an evolution of cloud radio access network (C-RAN), fog radio access network (F-RAN) becomes promising for future mobile communications by enabling processing and caching at fog access points (FAPs). Different from the centralised C-RAN, F-RAN has a semi-distributed architecture, aiming to alleviate traffic load on the fronthaul links in C-RAN. Under the semi-distributed architecture in F-RAN, which employs a cell-free multiple input multiple output (MIMO) access technique, decisions on the joint user-FAP association and transmit power allocation are made at individual FAPs. To mitigate strong interference, FAPs will need to exchange cooperative status information, such as CSI, user association details or transmission power levels. However, this can lead to significant communication overhead within the network and introduce high complexity in the decision-making process. In this paper, accounting for the semi-distributed nature of the F-RAN architecture, reinforcement learning is leveraged as a potential solution to this kind of problem, and a novel multi-agent dual deep Q-network (MA-DDQN) algorithm is proposed by introducing experience exchange in partially observable Markov decision process environments. The simulation results show that the proposed reinforcement learning based algorithm outperforms the DDQN algorithm as well as the existing low-complexity algorithms.

In this paper, downlink (DL) pilot based integrated sensing and communication (ISAC) is explored in cell-free networks. To improve both accuracy of channel estimation and localization in the ISAC based cell free network, a group of pre-designed DL orthogonal pilot sequences are introduced in the proposed ISAC strategy for both channel estimation for communications and cooperative sensing with radars. A power allocation scheme is proposed with the objective of minimizing the maximum channel estimation error for each user, under the power constraints of APs and minimum mean square error of sensing based localization. The performance of the proposed ISAC strategy is evaluated under a realistic highway scenario, and compared to the conventional methods. The results show that the performances of both channel estimation and localization can be significantly improved at a relatively low cost of extra power needed for APs near users.

Mobile edge computing (MEC) and vehicle-to-everything (V2X) communications are two promising technics to support delay-sensitive applications for autonomous driving. In this paper, road side unit (RSU) and assistant vehicle offloading are jointly considered to minimize latency for vehicular tasks in an MEC-V2X network. The impact of Doppler spread caused by high moving speed is also considered. The offloading decision, transmit power, bandwidth, and computation resource allocations are solved by formulating them as a joint optimization problem. The simulation results show that the proposed scheme significantly reduced the task latency, compared to three traditional methods, where task either run locally, or at MEC server, or adaptively between MEC server and local.

Edge caching is a promising solution for next-generation networks by empowering caching units in small-cell base stations (SBSs), which allows user equipments (UEs) to fetch users’ requested contents that have been pre-cached in SBSs. It is crucial for SBSs to predict accurate popular contents through learning while protecting users’ personal information. Traditional federated learning (FL) can protect users’ privacy but the data discrepancies among UEs can lead to a degradation in model quality. Therefore, it is necessary to train personalized local models for each UE to predict popular contents accurately. In addition, the cached contents can be shared among adjacent SBSs in next-generation networks, thus caching predicted popular contents in different SBSs may affect the cost to fetch contents. Hence, it is critical to determine where the popular contents are cached cooperatively. To address these issues, we propose a cooperative edge caching scheme based on elastic federated and multi-agent deep reinforcement learning (CEFMR) to optimize the cost in the network. We first propose an elastic FL algorithm to train the personalized model for each UE, where adversarial autoencoder (AAE) model is adopted for training to improve the prediction accuracy, then a popular content prediction algorithm is proposed to predict the popular contents for each SBS based on the trained AAE model. Finally, we propose a multi-agent deep reinforcement learning (MADRL) based algorithm to decide where the predicted popular contents are collaboratively cached among SBSs. Our experimental results demonstrate the superiority of our proposed scheme to existing baseline caching schemes.

In this paper, a mobile edge computing (MEC) assisted multi-layer architecture is proposed to support the implementation of federated learning in Internet of Things (IoT) networks. In this architecture, when performing a federated learning based task, data samples can be partially offloaded to MEC servers and cloud server rather than only processing the task at the IoT devices. After collecting local model parameters from devices and MEC servers, cloud server makes an aggregation and broadcasts it back to all devices. An optimization problem is presented to minimize the total federated training latency by jointly optimizing decisions on data offloading ratio, computation resource allocation and bandwidth allocation. To solve the formulated NP hard problem, the optimization problem is converted into quadratically constrained quadratic program (QCQP) and an efficient algorithm is proposed based on semidefinite relaxation (SDR) method. Furthermore, the scenario with the constraint of indivisible tasks in devices is considered and an applicable algorithm is proposed to get effective offloading decisions. Simulation results show that the proposed solutions can get effective resource allocation strategy and the proposed multi-layer federated learning architecture outperforms the conventional federated learning scheme in terms of the learning latency performance.

This letter proposes a nonparametric detector, termed as Gini Correlation (GC), to solve the classical problem of detecting deterministic signals buried in impulsive noise. With the help of the popular Middleton’s Class-A impulsive noise (MCAN) model, we derive the expectation and variance of GC under alternative hypothesis and null hypothesis, which, along with the central limit theorem, are further employed for determining the detection probability and the detection threshold. The results show that the proposed detector possesses a constant false alarm rate property. Monte Carlo simulations verify not only the correctness of our theoretical findings but also the superiority of GC to other state-of-the-art methods in terms of receiver operating characteristic (ROC) curves and asymptotic relative efficiency (ARE) curves.

The application of non-orthogonal multiple access (NOMA) to multicarrier systems can improve the spectrum efficiency and enable massive connectivity in future mobile systems. Resource allocation in multicarrier NOMA systems is a non-deterministic polynomial time-hard problem requiring exhaustive search, which has prohibitive computational complexity. Instead, efficient algorithms that provide a good trade-off between system performance and implementation practicality are needed. In this paper, exact values of the optimal channel gain ratios between a pair of NOMA users are presented for the first time for quadrature amplitude modulation (QAM) schemes. Further, numerical limits are derived for the values of channel gain ratios that fulfill the system constraints. These findings are used to propose a user pairing algorithm with quasi-linear complexity. Further, a novel scheme for data rate and continuous power allocation is proposed. Through numerical simulations, it is proved that the proposed scheme yields an achievable sum-rate close to the performance of exhaustive search, and it outperforms other suboptimal resource allocation schemes.

This paper proposes a new simultaneous terahertz (THz) information and power transfer (STIPT) system, which utilizes a reconfigurable intelligent surface (RIS) for both the data and power transmission. We aim to maximize the information users’ (IUs’) sum data rate while guaranteeing the power harvesting requirements of energy users (EUs) and RIS. To solve the formulated non-convex problem, the block coordinate descent (BCD) based algorithm is adopted to alternately optimize the transmit precoding of IUs, RIS’s reflecting coefficients, and the position of RIS. Additionally, the penalty constrained convex approximation (PCCA) algorithm is proposed to optimize the deployment of the RIS, where the introduced penalties ensure that the solution is always feasible. The simulation results show that the proposed solution outperforms the benchmark schemes, and the proposed BCD algorithm can greatly improve the performance of the STIPT system.

In this paper, the performance analysis of non-orthogonal multiple access (NOMA) in a cloud radio access networks (C-RAN) is carried out. The problem of jointly optimizing user association, muting and power-bandwidth allocation is formulated for NOMA-enabled C-RANs. To solve the mixed integer programming problem, the joint problem is decomposed into two subproblems as 1) user association and muting 2) power-bandwidth allocation optimization. To deal with the first subproblem, we propose a centralized and heuristic algorithm to obtain a feasible solution to the remote radio head (RRH) muting problem for given bandwidth and transmit power. The second subproblem is then reformulated for tractibility purpose and a low-complexity algorithm is proposed to bandwidth and power allocation subject to users data rate constraints. Moreover, for given user association and muting states, the near optimal power allocation is derived in a closed-form expression. Simulation results show that the proposed NOMA-enabled C-RAN outperforms orthogonal multiple access (OMA)-based C-RANs in terms of total achievable rate, interference mitigation and can achieve significant fairness improvement.

The application of non-orthogonal multiple access (NOMA) to multicarrier (MC) systems can improve the spectrum efficiency and enable massive connectivity in future mobile communication systems. Resource allocation in MC NOMA is a non-deterministic polynomial time (NP)-hard problem with prohibitive computational complexity. Thus, efficient algorithms that provide a good trade-off between performance and complexity are needed. In this paper, exact values of the optimal channel gain ratios between a pair of NOMA users are presented for quadrature amplitude modulation (QAM). Further, numerical limits are derived for the values of channel gain ratios that fulfill the system constraints. Unlike previous works, it is demonstrated that the benefit of pairing users with very distinct channel gains is lost under practical QAM schemes, due to the inability of users with poor channel conditions to fulfill bit error rate (BER) constraints. These findings are used to propose a user pairing algorithm with quasi-linear complexity. Further, a novel scheme for data rate and continuous power allocation is proposed. Through numerical simulations, it is proved that the proposed scheme yields an achievable sum-rate close to the performance of exhaustive search, and it outperforms other suboptimal resource allocation schemes.

This letter proposes to apply two rank correlations, namely, Kendalls tau (KT) and Spearmans rho (SR), to the fundamental problem of detecting known signals in impulsive noise. Under the popular Middletons Class-A impulsive noise model, we derived the expectations and variances of KT and SR, which, along with the central limit theorem, are further employed to determining the detection threshold and the detection probability. Monte Carlo simulations not only verified the correctness of our theoretical findings but also demonstrated the superiority of KT and SR to the other five state-of-the-art methods in terms of detection probability.

In the fifth generation (5G) era, mobile networks will provide diversified services such as enhanced Mobile BroadBand (eMBB) and ultra-reliable low-latency communication (URLLC). Furthermore, the 5G architecture will be fog-like, enabling a functional split of network functionalities between cloud and edge nodes. In this article, we propose a non-orthogonal multiple access (NOMA)-enabled fog-cloud structure in a novel density-aware fog-based radio access networks (F-RAN) to tackle different aspects of high and low-density regions, in order to meet the heterogeneous requirements of eMBB and URLLC traffic. A framework of two different problem formulations is considered to cater the high throughput and low-latency requirements in a high and low-density mode respectively. In the first problem, we study the joint caching placement and association strategy aiming at minimizing the average delay. To deal with the first problem, we apply McCormick envelopes and Lagrange partial relaxation method to transform it into three convex sub-problems, which is then solved by proposing a distributed algorithm. The second problem is to jointly optimize transmission mode selection, subchannel assignment and power allocation to maximize the sum data rate of all fog user equipments (F-UEs) while satisfying fronthaul capacity and fog-computing access point (F-AP) power constraints. Moreover, for given transmission mode selection and subchannel assignment, the optimal power allocation is derived in a closed-form expression. Simulation results are provided to validate the effectiveness of the proposed NOMA-enabled F-RAN framework and reveal that the ultra-low latency and high throughput can be achieved by properly utilizing the available resources.

In this paper, a cooperative task computation framework exploits the computation resource in user equipments (UEs) to accomplish more tasks meanwhile minimizes the power consumption of UEs. The system cost includes the cost of UEs' power consumption and the penalty of unaccomplished tasks, and the system cost is minimized by jointly optimizing binary offloading decisions, the computational frequencies, and the offloading transmit power. To solve the formulated mixed-integer non-linear programming problem, three efficient algorithms are proposed, i.e., integer constraints relaxation-based iterative algorithm (ICRBI), heuristic matching algorithm, and the decentralized algorithm. The ICRBI algorithm achieves the best performance at the cost of the highest complexity, while the heuristic matching algorithm significantly reduces the complexity while still providing reasonable performance. As the previous two algorithms are centralized, the decentralized algorithm is also provided to further reduce the complexity, and it is suitable for the scenarios that cannot provide the central controller. The simulation results are provided to validate the performance gain in terms of the total system cost obtained by the proposed cooperative computation framework.

Fog-computing network combines the cloud computing and fog access points (FAPs) equipped with mobile edge computing (MEC) servers together to support computation-intensive tasks for mobile users. In this paper, we investigate the delay minimization problem for task offloading in a hierarchical fog-computing C-RAN network, which consists of three tiers of computational services: MEC server in radio units, MEC server in distributed units, and the cloud computing in central units. The receive beamforming vectors, task allocation, computing speed for offloaded tasks in each server and the transmission bandwidth split of fronthaul links are optimized by solving the formulated mixed integer programming problem. The simulation results validate the superiority of the proposed hierarchical fog-computing C-RAN network in terms of the delay performance.

In order to ensure the safety of workers and the stable operation of the power grid, the power grid companies in China have developed a very strict safety control system which contains many regulations, such as safety regulations and the two-ticket regulations. However, some workers are still lack of safety awareness in that they even do not wear safety helmets when carrying out construction or maintenance projects in substations. Safety helmet is an indispensable safety tool in electric power work, which can maintain the head safety of workers at all times and avoid fatal injuries such as electric shock and strike. Working without safety helmet is not only a violation of the safety control system, but also a manifestation of not being responsible for personal life and property. Nevertheless, the existing control means can not identify and prevent such behavior timely, efficiently and accurately. In order to better avoid this unsafe behavior, this paper proposes the Improved Faster R-CNN algorithm to inspect the wearing of safety helmet. Considering the real situation, the Retinex image enhancement is introduced to improve image quality for the outdoor complex scenes in substations. K-means++ algorithm is also adopted for better adaptation to the small size helmet. The experimental results show that compared with the Faster R-CNN algorithm, the mean average precision of the Improved Faster R-CNN is improved and the real-time automatic detection of the wearing of safety helmets is realized.

In vehicular communication systems, maximizing the number of served vehicles while simultaneously guaranteeing reliable coverage at all the vehicles can be a challenging proposition. A switched-beam based infrastructure can provide better reliability as the signal-to-interference-plus-noise ratio (SINR) can be improved. However, a simple switched-beam based vehicle-to-infrastructure (V2I) system alone may not suffice for serving all the vehicles because (i) the number of vehicle is more than the number of beam, and (ii) a vehicle may be out of the coverage region of a beam. Therefore, introducing vehicle-to-vehicle (V2V) communication becomes crucial in extending the number of served vehicles. In this paper, ajoint vehicle-beam allocation (VBA) and vehicular proximity (VP) algorithms for V2I and V2V, respectively are proposed to guarantee reliable coverage for vehicles. VBA is an SINR optimization algorithm, and VP is based on LTE Mode 4, a proximity based service for V2V communications. It is shown that setting a flexible SINR threshold helps in attaining a reliable beam coverage region in switched-beam based V2I communication. It is proven that the outage probability are also directly dependent on SINR thresholds. Lastly, the concept of utility ratio is also introduced as a metric for reliability. Simulation results show that joint V2I and V2V communication significantly improves the utility ratio.

Autonomous driving in future vehicle system has imposed a high demand for reliable and power efficient communication to provide safe-driving to vehicular users. In order to achieve reliability and power efficiency, in this paper, a vehicular trellis architecture (VTA) is proposed. VTA allows traffic information to be transmitted either via vehicle-to-infrastructure (V2I), through the dedicated remote radio head (RRH) and its dynamically select vehicle(s) or, direct vehicle-to-vehicle (V2V) communication. We investigated the adaptive switching over V2I/V2V, to enhance efficient system reliability while optimizing the average power consumption of VTA. This paper presents a vehicular trellis algorithm (VTRA), which approximate solutions to the optimization problem. Simulation results demonstrate that the selection of joint V2I/V2V communication reduces the total power consumption of the system for a varying number of threshold distance and vehicles.

The problem of resource allocation in multicarrier non-orthogonal multiple access (NOMA) systems is non-deterministic polynomial time (NP)-hard and requires exhaustive search, which has prohibitive computational complexity. Computationally-efficient algorithms that provide a performance close to optimal are needed. In this paper, the problem of resource allocation is divided into two sub-problems, namely subcarrier assignment and power allocation. The optimal users' channel condition relationship is derived in terms of effective system sum-rate, and a computationally-efficient ideal partner search algorithm (IPSA) is proposed. Further, optimal power allocation (OPA) is studied in terms of fairness, and an OPA coefficient is theoretically derived based on the channel condition ratio of two NOMA users. Numerical results show that IPSA with OPA outperforms IPSA with fractional transmit power allocation (FTPA), the strongest user-weakest user (SUWU) scheme and user grouping (UG) in terms of achievable system effective sum-rate, average user bit error rate (BER) and number of users with a poor BER. Further, the computational complexity of IPSA with OPA is much lower than that of exhaustive search.

Rapid deployment is crucial for building up drone aided emergency communications to ensure the coverage and service support after the disaster. The chaos in the post-disaster area, such as the number of ground users and scattered locations, makes difficult on the decision of drone deployment. In this paper, an unsupervised machine learning method is conducted for drone deployment in drone aided emergency communications. Considering the importance of sustainable services for drones, the drone deployment problem is formulated with the aim of minimizing the total power of drones with all users' coverage while maintaining their rate requirements, with constraints on drones' coverage area, capacity and limited power. The problem is solved by two steps. A modified k-means clustering algorithm is proposed to obtain the number of drones and an optimal altitude and minimum transmit power algorithm is then derived. Simulation results show that although the number of drones obtained by the modified algorithm is more than that of the original k-means algorithm, all users are served and the minimum power of drones is guaranteed by proposed algorithms.

In this paper, the performance analysis of non-orthogonal multiple access (NOMA) in heterogeneous cloud radio access networks (H-CRAN) is carried out, where coordination of macro base station (MBS) and remote radio heads (RRHs) for H-CRAN with NOMA is introduced to improve network performance. We formulate the problem of jointly optimizing user association, coordinated scheduling and power allocation for NOMA-enabled H-CRANs. To efficiently solve this problem, we decompose the joint optimization problem into two subproblems as 1) coordinated scheduling 2) power allocation optimization. Firstly the users are divided based on interferences they suffer from. This interference-aware NOMA approach account for the inter-tier interference. Based on the user scheduling scheme, optimal power allocation optimization is performed by the hierarchical decomposition approach. Simulation results show that the proposed NOMA-enabled H-CRAN outperforms orthogonal multiple access (OMA)-based H-CRANs in terms of total achievable rate, interference mitigation and can achieve significant fairness improvement.

To support millimeter-wave (mmWave) communications successfully, a large number of antennas (in the order of hundreds or thousands) must be implemented to mitigate significant propagation and scattering losses. Designing phased arrays for carrier frequency is a great method for narrowband systems, but the performance degrades significantly with larger bandwidth. We show that as the system bandwidth increases, the beams steer away from the focus direction, which is an effect known as beam squint in wideband systems. In this paper, at first, analysis of capacity is performed for an increasing number of antennas, to show the significance of beam squint. Then, a solution in digital domain is proposed. Conventionally, a single beam would be allocated to a user. By exploiting beam squint effect, in this solution more than one beam can carry a single-user’s data, which improves the system’s performance significantly, especially when the number of antennas in an array is large and there are multiple users.

In this paper, the user cooperative task computation is explored by sharing the computing capability of the user equipments (UEs) so as to enhance the performance of mobile edge computing (MEC) networks. The number of completed tasks is maximized while minimizing the total power consumption of the UEs by jointly optimizing the user task offloading decision, the computational speed for the offloaded task and the transmit power for task offloading. An iterative algorithm based on the linear programming relaxation is proposed to solve the formulated mixed integer non-linear problem. The simulation results show that the proposed user cooperative computation scheme can achieve a higher completed tasks ratio than the non-cooperative scheme.

High-speed trains are being widely deployed around the world. To meet the high data rate transmission requirements, millimeter wave high-speed train communication systems with large antenna arrays have drawn increasingly attentions. Since channel conditions vary rapidly in high-speed train communication scenarios, frequent channel estimation is required. Moreover, due to the limit period of each transmission time interval, the key challenge in channel estimation is to design an efficient beam searching scheme to allow more time for data transmission. This paper formulates the beam searching problem into a multi-armed bandit problem, and proposes a bandit inspired beam searching scheme to reduce the number of measurements. The performance of the proposed scheme is evaluated in terms of regret, and simulation results show that the proposed scheme can approach the theocratical limit quickly.

With low cost and high mobility, drones are envisioned to be an important contributor to emergency communications. In this paper, we consider a unique drone aided emergency communication deployed in hills and mountains areas, where power-constrained drones serve as relays to improve the uplink sum rates via amplify-and-forward (AF) relaying. The channel models between drones and ground users in this communications and the ground users distributions are greatly different from that in conventional relay networks, while drones have their coverage areas and capacity constraint. By taking these specific characteristics into account, we formulate the joint power and subcarrier allocation problem to maximize the uplink throughput in the drone aided emergency communications under constrains to the transmit power budget for each drone and the number of accessed users on each subcarrier. Due to the intractability of the formulated problem, it is decomposed into two subproblems: power allocation optimization and subcarrier allocation optimization. Then a joint resource allocation algorithm is proposed. The simulation results show that the proposed algorithm outperforms the others.

This paper addresses the energy minimization problem in Device-to-Device (D2D) assisted Mobile Edge Computing (MEC) networks under the latency constraint of each individual task and the computing resource constraint of each computing entity. The energy minimization problem is formed as a two-stage optimization problem. Specifically, in the first stage, an initial feasibility problem is formed to maximize the number of executed tasks and the global energy minimization problem is tackled in the second stage while maintaining the maximum number of executed tasks. Both of the optimization problems in two stages are NP-hard, therefore a low-complexity algorithm is developed for the initial feasibility problem with a supplementary algorithm further proposed for energy minimization. Simulation results demonstrate the near-optimal performance of the proposed algorithms and the fact that with the assistance of D2D communication, the number of executed tasks is greatly increased and the energy consumption per executed task is significantly reduced in MEC networks, especially in dense user scenario.

Moving to millimeter wave (mmWave) frequencies and deploying massive multiple input multiple output (MIMO) antenna arrays have shown great potential of supporting high-data-rate communications in the fifth-generation (5G) and beyond wireless networks, thanks to the availability of huge amounts of mmWave frequency bandwidth and massive numbers of narrow and high gain beams. A number of massive MIMO beamforming techniques have been proposed, among which the fixed-beam scheme has attracted considerable interests from both academia and industry due to its simplicity and requirement of a small number of radio frequency (RF) chains compared to the number of base-station (BS) antennas. Moreover, a beam allocation based pure analog fixed-beam system requires much lower complexity and less signalling overhead than the hybrid beamforming based fixed-beam system, which can therefore be easily implemented in the practical systems. In this paper, the sum data rate of beam allocation based multi-user massive MIMO systems is studied where a near-optimal low complexity beam allocation algorithm is adopted. Simulation results show that our derived average sum data rate serves as a good approximation of the simulation results.

In this paper, we develop novel precoders and combiners for multi-user hybrid digital to analog (D-A) beamforming for uplink massive multiple-input multiple-output millimeter wave systems. Considering the possibility that uplink transmissions from different users can go through the paths sharing the same physical scatters, some transmission paths of different users may have overlapped angle of arrivals (AoAs) at the base station. Therefore, the intrinsic focus is on substantially maximizing the desired signal while reducing the system interference. The analog precoders and combiners are designed by using the eigenvalue decomposition and the Riemannian optimization method based on Stiefel manifold algorithms respectively. The digital combiner adapts the minimum mean-square error by judiciously exploiting the effective uplink analog channel gains. Ultimately, simulation results show that the proposed algorithms outperform the existing algorithms in hybrid D-A paradigms in terms of the achievable uplink rate.

The problem of resource allocation in non-orthogonal multiple access (NOMA) systems is nondeterministic polynomial time (NP)-hard and requires exhaustive search. Hence, fast and computationally efficient algorithms that provide a performance close to optimal are needed. In this paper, the problem of resource allocation is divided into the sub-problems of subcarrier assignment and power allocation. The optimal users' channel condition relationship is derived in terms of the effective system sum-rate, and a fast ideal partner search algorithm (IPSA) is proposed in terms of that relationship. The performance of IPSA is verified under fractional transmit power allocation (FTPA). Simulation results show that our algorithm outperforms the strongest user-weakest user (SUWU) scheme, user grouping (UG) and random subcarrier and power allocation (RSPA) in terms of achievable system effective sum-rate, average user bit error rate (BER) and number of users with a poor BER.

Resource allocation of cellular-assisted device-to-device (D2D) communication is very challenging when frequency reuse is considered among multiple D2D pairs within a cell, as intense inter D2D interference is difficult to tackle and generally causes extremely large signaling overhead for channel state information (CSI) acquisition. In this paper, a novel resource allocation framework for cellular-assisted D2D communication is developed with low signaling overhead while maintaining high system capacity. By utilizing the spatial dispersion property of the D2D pairs, a geography-based sub-cell division strategy is proposed to divide the cell into multiple sub-cells and the D2D pairs within one sub-cell are formed into one group. Then, sub-cell resource allocation is performed independently among the sub-cells without the need of any prior knowledge of inter D2D interference. Under the proposed resource allocation framework, a tractable approximation for the inter D2D interference modeling is obtained and a computationally efficient expression for the average ergodic sum capacity of the cell is derived. The expression further allows us to obtain the optimal number of sub-cells, which is an important parameter for maximizing the average ergodic sum capacity of the cell. It is shown that with small CSI feedback, the system capacity can be improved significantly by adopting the proposed resource allocation framework, especially in dense D2D deployed systems.

The mobility management will be more complex and will have a great impact on the quality of service in the future cellular networks, as these networks will have to handle a huge number of user equipments (UEs) and their frequent hand offs due to very dense short-footage small cells. This paper presents a framework to model and derive the coverage of small cells, the cell sojourn time, and the hand off rate in multi-tier small cell networks. The distribution of the small cells around a reference UE’s path is studied by taking into consideration the overlaps among the small cells. Two types of hand off rates are introduced to estimate the load managed by different cells, where inter-frequency hand off rate and intra-frequency hand off rate represent the fraction of hand offs managed by the first tier and the other tiers, respectively. Our analysis shows that ignoring the overlaps among the small cells affects the accuracy of the results significantly. The simulation results validate the accuracy of the analytical results and also show the impact of different parameters, such as the small cell density, the number of tiers and the size of the small cells on the small cell sojourn time, the macro cell sojourn time, and the hand off rate.

Mingmin Jin, Xin Luo, Huiling Zhu, Hankz Hankui Zhuo. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018.

Next-generation network is considered as a device-to-device (D2D)-enabled system. The overlay in-band scheme can be used by the cellular user equipments and D2D user equipments (DUEs) to send data. The cellular and D2D links experience the in-band emission interference (IEI) from the DUEs that use the adjacent frequencies. This paper models the IEI impact by using stochastic geometry and analytically investigates this impact on cellular and D2D links. The IEI inter-cell and IEI intra-cell are separately assessed, and the expected D2D resource block (DRB) reuse factor is evaluated. Furthermore, the distance-density-based strategy is proposed to mitigate the IEI by controlling the number and location of served DUEs for each DRB. Also, the optimal power allocation algorithm is proposed by calculating the optimal DUEs transmission power profile that mitigates IEI and maximizes DUEs sum rate. The performance is improved significantly for the proposed methods. The application scenario is identified for each mitigation method.

Massive multiple-input-multiple-output (MIMO) has become a promising technique to provide high-data-rate communication in fifth-generation mobile systems, thanks to its ability to form narrow and high-gain beams. Among various massive MIMO beamforming techniques, the fixed-beam scheme has attracted considerable attention due to its simplicity. In this paper, we focus on a fixed-beam based multiuser massive MIMO system, where each user is served by a beam allocated to it. To maximize the sum data rate, a greedy beam allocation algorithm is proposed under the practical condition that the number of radio frequency chains is smaller than the number of users. Simulation results show that our proposed greedy algorithm achieves nearly optimal sum data rate. As only the sum data rate is optimized, there are some “worst-case” users, who could suffer from strong inter-beam interference and thus experience low data rate. To improve the individual data rates of the worst-case users while maintaining the sum data rate, an adaptive frequency reuse scheme is proposed. Simulation results corroborate that our proposed adaptive frequency reuse strategy can greatly improve the worst-case users' data rates and the max-min fairness among served users without sacrificing the sum data rate.

The overlay in-band device to device (D2D) scheme can be used by cellular user equipments (CUEs) and D2D user equipments (DUEs) to transmit the uplink and D2D data. The CUEs experience in-band emission interference (IEI) from the DUEs that transmit D2D signals in the adjacent channels. This paper evaluates the IEI impact in D2D-enabled cellular networks in terms of typical CUE outage probability for different DUE densities and DUE transmission powers. Further, the IEI intra-cell and IEI inter-cell are examined separately to determine the dominating part of IEI in the system. The results show the IEI impact has a harmful impact and causes the outage in the system with high probability when the DUE density is high. Also, a remarkable result finds that the IEI intra-cell and IEI inter-cell dominate the typical CUE outage probability similarly when the DUE density is low, whilst at high DUE density the IEI intra-cell does.

High-speed train (HST) has drawn considerable attention and become one of the most preferable conveyance mechanisms. Every year the manufacture corporations achieve a higher speed record and expect to attain 1000 km/h by 2021 using hyperloop one technology. Moving at such a high speed results in a high handover rate which makes it challenging for high speed railway (HSR) mobile wireless communication to preserve steady link performance. Employing distributed antenna systems (DASs) along with the two-hop architecture, this paper proposes a fast predictive handover algorithm. In this strategy, the serving cell starts the handover preparation phase in advance by inferring the train's current location. Issuing the handover preparation phase in advance reduces the handover latency and handover command failure probability as well. Lower handover command failure probability means lower handover failure probability which could greatly improve the end-users' quality of services (QoS). The analytical results show that the proposed scheme outperforms the conventional handover scheme.

In wireless communication networks, caching and delivering popular content via the device to device (D2D)communication has recently been proposed as an exciting and innovative technology in order to offload network data traffic. In this paper, a novel method of content delivery using multiple devices to the single device (MDSD) communication via D2D links is presented. An expression of the outage probability (Pout) is analytically derived and validated by simulation to determine the success of the content delivery to the user equipment (UE). Zipf distribution with exponent shape parameter is adopted to model the UE requests and content caching popularity which affects the achievable link data rate (Ra). The results show that Pout decreases as the popularity of the content increases. Meanwhile, MDSD substantially improves the UE experience in terms of Pout compared to the single D2D link based method.

Previously, a scheme in [1] was proposed for the outdated channel state information (CSI) problem, for data transmission in time division duplex (TDD) systems. In user movement environment, the actual channel of data transmission at downlink time slot is different from the estimated channel due to channel variation. In this paper, the effect of different user mobility on TDD downlink multiuser distributed antenna system is investigated. An efficient autocorrelation based feedback interval technique is proposed and updates CSI at less the cost of the downlink time slots. In the proposed technique, the frequency of CSI feedback for different users is proportional to their speed. Cooperative clusters are formed to maximize sum rate where channel gain based antenna selection and user clustering based on signal-to- interference plus noise ratio (SINR) threshold is applied to reduce computational complexity. Numerical results show that sum rate superiority of the proposed scheme over the user mobility.

The cell sojourn time and the handoff rate have been considered as the main parameters in the mobility management of the cellular systems. In this paper, we address the mobility management in a small cell network and propose a framework to study the impact of different system parameters on the handoff rate and the small cell sojourn time. In the proposed framework, the overlapping coverage among the small cells and the number of overlaps on the path of a reference user equipment (UE) are derived to obtain the actual time that the reference UE spends in each small cell during its movement from the starting point to the destination point. The results validate the accuracy of the analysis in this paper in comparison to the analysis when ignoring the impact of the overlaps. The results also confirm the importance of considering the overlaps among the small cells in dense networks.

Hybrid digital-to-analog (D-A) precoding is a promising technology to reduce the number of radio frequency (RF) chains in a millimetre-wave (mm-Wave) multiple-input multiple-output (MIMO) system. To reap the full scale benefits of the hybrid D-A precoding, in this paper, two algorithms are proposed to maximise the capacity of the hybrid D-A mm-Wave MIMO system. The first algorithm is based on the principle of manifold optimisation (MO). The second algorithm operates on particle swarm optimisation (PSO). These two algorithms are compared with three existing hybrid D-A precoding algorithms in the literature. The simulation results show that the proposed algorithms achieve higher capacity than the existing hybrid D-A precoding algorithms with lower computational complexity.

Inter-frequency scan (IFS) is a process performed by the user equipment (UE) to discover small cells in heterogeneous networks (HetNets) for high data rate and boosting the spectral efficiency. It is anticipated that the role of IFS will have a significant impact on the quality of service (QoS) and the energy efficiency in the future cellular systems. In this paper, a framework is presented to model and evaluate the impact of IFS on the system performance by using stochastic geometry. The energy efficiency is derived as performance metric to obtain the optimum value of the IFS rate (optimum number of scans per unit time) by taking into consideration the tradeoff between the power consumption and exploiting the abundant frequency resources at the small cells efficiently. Considering the energy consumption for performing IFSs along with the energy consumption for maintaining the uplink (UL) transmission will help to find the optimum value of IFS rate that achieves the best energy efficiency. The analysis and results show that the optimum IFS rate depends on different system parameters such as the small cells' density, UE's speed and the transmit power of the small cells (small cells coverage).

As a promising solution to offload cellular traffic, device-to-device (D2D) communication has been adopted to help disseminate contents. In this paper, the D2D offloading utility is maximized by proposing an optimal content pushing strategy based on the user interests and sharing willingness. Specifically, users are classified into groups by their interest probabilities and carry out D2D communications according to their sharing willingness. Although the formulated optimization problem is nonconvex, the optimal solution is obtained in closed-form by applying Karush-Kuhn-Tucker conditions. The theoretical and simulation results show that more contents should be pushed to the user group that is most willing to share, instead of the group that has the largest number of interested users.

High-speed railway (HSR) has witnessed a huge growth globally, and now is reaching a maximum speed of 575 km/h. This record of speed makes mobile communications difficult for HSR since the handover (HO) frequency increases which results in a high loss of connectivity. Based on distributed antenna systems (DASs), this paper utilizes the two-hop network architecture for HSR broadband wireless communication systems. With the target of achieving high system capacity, superior transmission reliability, and consequently high-quality broadband wireless communication service for passengers in HSR. Moreover, a Frequency Switch (FSW) scheme is proposed for the two-hop network architecture to alleviate the frequent HO issue in traditional HSR wireless communication systems where HO generally happens between the successive remote antenna units (RAUs) connecting to the same central unit (CU) control. The FSW scheme provides mobility robustness signalling process that guarantees a successful frequency switching instead of HO, and reduces the probability of radio link failure (RLF) compared to HO process in traditional HSR systems, where the HO failure (HOF) rate is about 21%. The analytical results show that the proposed scheme outperforms traditional HO schemes.

In this paper, optimal content caching strategy is proposed to jointly minimize the cell average outage probability and fronthaul usage in cloud radio access network (Cloud-RAN). Closed form expression of the outage probability conditioned on the user's location is presented, and the cell average outage probability is obtained through the composite Simpson's integration. The caching strategy for jointly optimizing the cell average outage probability and fronthaul usage is formulated as a weighted sum minimization problem, which is a nonlinear 0-1 integer NP-hard problem. In order to deal with the NP-hard problem, at first, two particular caching placement schemes are investigated: the most popular content (MPC) caching scheme and the proposed location-based largest content diversity (LB-LCD) caching scheme. Then a genetic algorithm (GA) based approach is proposed. Numerical results show that the performance of the proposed GA-based approach with significantly reduced computational complexity is close to the optimal performance achieved by exhaustive search based caching strategy.

High-speed railway (HSR) has witnessed a huge growth all over the globe reaching a maximum speed of 575 km/h. This record of speed makes mobile communications difficult for HSR since the handover (HO) frequency increases which frequently results in a loss of connectivity. This paper proposes a specialized network architecture based on distributed antenna systems (DAS) for HSR broadband wireless communication systems along with the two- hop architecture. Further, a frequency switch (FSW) scheme is proposed aiming to eliminate the need for HO between the successive small coverage remote antenna units (RAUs) that fall under the same central unit (CU) control. The analytical results show that the proposed scheme outperforms traditional HO schemes and can support the application with high quality of services (QoS) requirement.

High-speed trains have become one of the most leading transportation means, where each year the manufacture companies reach a new speed record. This progressive speed records increase the handover (HO) rate which makes it very difficult for high speed railway (HSR) mobile communication to sustain a reliable communication link. Utilizing distributed antenna systems (DASs) along with the two-hop architecture, this paper analyzes the conventional handover scheme based on this architecture and proposes a faster HO strategy. The proposed scheme reduces the HO latency and failure probability which could greatly improve the end-users quality of services (QoS). The analytical results show that the proposed scheme performs better than the conventional HO scheme.

The capacity of a millimetre-wave (mm-Wave) system can be improved by adopting a hybrid digital-to-analog (D-A) precoding system. Therefore, in this paper, an algorithm is proposed to maximise the capacity of the hybrid D-A mm-Wave system. This algorithm is a geometric approach which is based on the principle of Stiefel Manifold optimisation (SMO). Our proposed algorithm is compared with three known hybrid D-A precoding algorithms in the literature. The analytical and simulation results show that the proposed algorithm achieves higher capacity than the existing hybrid D-A precoding algorithms.

In non-orthogonal multiple access (NOMA), signals of different users are independently encoded and modulated, then superposed in the power domain before transmission. The choice of a suitable combination of power allocation factor (PAF) and transmit constellations is hence critical to enhance the system performance. The aim of this work is to develop a tool for adaptively selecting a suitable PAF and transmit constellations for an enhanced system data rate, given some individual user bit error rate (BER) constraints that need to be jointly considered. For this purpose, analytical bit error probability (BEP) expressions are derived and evaluated. This is the first attempt to analytically evaluate the BER in NOMA systems. The expressions are evaluated in order to propose the best combination of MCS and PAF. The trade-offs involved in selecting a certain combination of transmit constellations and PAF are also investigated. Moreover, numerical evaluations prove that the attainable BEP at the near user is affected by that of the far user. Look-up tables of suitable combinations of PAF and transmit constellations are derived using the BEP expressions, with a focus on enhancing the system data rate for some given BER constraints at both users.

Device to Device (D2D) communication with content caching has recently been proposed as an exciting and innovative technology for next generation cellular networks. This paper presents a novel content caching and delivery method which allows multiple devices caching the same content and the content being sent via multiple devices to single device (MDSD) communication using D2D links to enhance user experience in terms of outage probability. A closed form expression of the outage probability is derived by considering how the content caching popularity affects achievable signal to interference plus noise ratio (SINR). The simulation and theoretical results show that as the popularity of the video increases, the outage probability of the system decreases substantially. On the other hand, the results show using MDSD enhances the SINR performance and decreases the outage probability of the system significantly.

Offloading traffic from the macro cells (MCs) with limited frequency resources to the high frequency small cells (SCs) improves the spectral efficiency and the energy efficiency in the inter-frequency heterogeneous networks (HetNets). Inter-frequency measurement (IFM) is an essential process prior to offloading terminals and their traffic to the SCs, and has a great impact on the utilization of the system resources. In this paper, we address the role of IFM in a two-tier HetNet and investigate other system parameters that impact on the offloading process. The uplink energy efficiency (UEE) is derived as a performance metric to minimize the trade-off between the power consumption at the terminals' side and exploiting the system resources. The results show that considering different number of IFM scans per unit time according to the density of SCs can improve the energy efficiency in the system significantly.

Supporting high user density and improving millimeter- wave (mm-Wave) spectral-efficiency (SE) is imperative in 5G systems. Current hybrid digital-to-analog beamforming (D-A BF) base stations (BS) can only support a particular user per radio frequency (RF) chain, which severely restricts mm-Wave SE. In this paper a novel low-complexity selection combining (LC- SC) is proposed for supporting high user density for mm-Wave BS. When compared with the current state of the art hybrid D-A BF, simulations show that LC-SC can support high user density and attain higher SE.

Device-to-Device (D2D) communication has been proposed as a promising way to offload traffic from the cellular network. In this paper, with the joint impact of user preference and selfishness, the D2D assisted content dissemination process is investigated in order to maximize the offloading gain via D2D communications. An alternative group pushing optimization (AGPO) algorithm is proposed to solve the formulated nonconvex problem. In addition, for the special case of two groups, the optimal solution is derived in closed-form to help validate the algorithm. Finally, the simulation results show that the AGPO algorithm converges to the global optimum and has a much lower complexity compared to exhaustive search.

In distributed massive multi-input multi-output (DM-MIMO) system, the number of users simultaneously served is greatly restricted if the pilots allocated for users are orthogonal. In this paper, a dynamic pilot reuse strategy within a single cell DM-MIMO system is proposed in order to reduce pilot overhead. The reuse in this strategy is applied so that maximum average sum-rate is satisfied within limited pilot resources. Specifically, two users in different subcells separated by large distance and meeting a specific data rate level can share the same pilot sequence. To perform this strategy, an expression for signal to interference plus noise ratio (SINR) is first derived for any pair of users who uses the same pilot. Based on this expression, an algorithm is proposed to choose which pairs of users are able to use the same pilot by comparing their potential data rates with a certain threshold. Finally, a method is employed to find the near-optimal threshold that can be utilized in the suggested algorithm to produce the maximum average sum-rate. The simulation results demonstrate that the uplink achievable sum-rate for the proposed strategy is higher than the both cases when no pilot reuse or random pilot reuse are considered.

In distributed massive multi-input multi-output (DM-MIMO) systems, orthogonal pilot sequences are generally utilized to acquire the channel state information (CSI). However, this highly restricts the number of users simultaneously served. In this paper, a pilot reuse within a single cell DM-MIMO system is proposed to serve more users than the available pilot sequences. The reuse in this strategy is applied so that maximum achievable sum-rate is satisfied with the constraint of predefined pilot resource. On this basis, two users in different subcells separated by a large distance and satisfying a specific signal to interference plus noise ratio (SINR) level can share the same pilot sequence. An expression for SINR is derived for any pair of users who use the same pilot. Based on this expression, an algorithm is proposed to choose which pairs of users are able to use the same pilot with the constraint of satisfying the minimum SINR required for these users. The simulation results demonstrate that the uplink achievable sum-rate for the proposed strategy is higher than both cases when no pilot reuse or random pilot reuse are considered.

Cloud radio access network(C-RAN) has been proposed as a novel mobile network architecture allowing centralized processing. Resource allocation (RA) is the core task in order to coordinate transmissions.In this paper efficient resource allocation technique in non-orthogonal multiple access (NOMA) based C-RAN systems is proposed. The task of RA is solved by centralized solutions in a C-RAN.The problem of maximizing the weighted sum-rate of users with target quality of service(QoS)is addressed subject to various constraints. The problem is divided into sub- problems and then sub-optimal solutions are proposed. Numerical experiments show that the proposed algorithms can improve the system performance as compared to orthogonal multiple access(OMA)-based C-RAN systems.

Device-to-device (D2D) assisted offloading heavily depends on the participation of human users. The content preference and sharing willingness of human users are two crucial factors in the D2D assisted offloading. In this paper, with consideration of these two factors, the optimal content pushing strategy is investigated by formulating an optimization problem to maximize the offloading gain measured by the offloaded traffic. Users are placed into groups according to their content preferences and share content with intergroup and intragroup users at different sharing probabilities. Although the optimization problem is nonconvex, the closed-form optimal solution for a special case is obtained, when the sharing probabilities for intergroup and intragroup users are the same. Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem. Finally, simulation results are provided to demonstrate the offloading performance achieved by the optimal pushing strategy for the special case and AGO algorithm. An interesting conclusion drawn is that the group with the largest number of interested users is not necessarily given the highest pushing probability. It is more important to give high pushing probability to users with high sharing willingness.

This paper provides a unified framework to deal with the challenges arising in dense cloud radio access networks (C-RAN), which include huge power consumption, limited fronthaul capacity, heavy computational complexity, unavailability of full channel state information (CSI), and so on. Specifically, we aim to jointly optimize the remote radio head (RRH) selection, user equipment (UE)-RRH associations and beam-vectors to minimize the total network power consumption (NPC) for dense multi-channel downlink C-RAN with incomplete CSI subject to per-RRH power constraints, each UE's total rate requirement, and fronthaul link capacity constraints. This optimization problem is NP-hard. In addition, due to the incomplete CSI, the exact expression of UEs' rate expression is intractable. We first conservatively replace UEs' rate expression with its lower bound. Then, based on the successive convex approximation technique and the relationship between the data rate and the mean square error, we propose a single-layer iterative algorithm to solve the NPC minimization problem with convergence guarantee. In each iteration of the algorithm, the Lagrange dual decomposition method is used to derive the structure of the optimal beam-vectors, which facilitates the parallel computations at the baseband unit pool. Furthermore, a bisection UE selection algorithm is proposed to guarantee the feasibility of the problem. Simulation results show the benefits of the proposed algorithms and the fact that a limited amount of CSI is sufficient to achieve performance close to that obtained when perfect CSI is possessed.

The non-orthogonal multiple access (NOMA) allows one subcarrier to be allocated to more than one user at the same time in an orthogonal frequency division multiplexing (OFDM) system. NOMA is a promising technique to provide high throughput due to frequency reuse within a cell. In this paper, a novel interference cancellation (IC) technique is proposed for asynchronous NOMA systems. The proposed IC technique exploits a triangular pattern to perform the IC from all interfering users for the desired user. The bit error rate and the capacity performance analysis of an uplink NOMA system with the proposed IC technique are presented, along with the comparison to orthogonal frequency division multiple access (OFDMA) systems. The numerical and simulation results show that the NOMA with the proposed asynchronous IC technique outperforms the OFDMA. It is also shown that employing iterative IC provides significant performance gain for NOMA and the number of required iterations depends on the modulation level and the detection method. With hard decision, two iterations are sufficient, and however, with soft decision, two iterations are enough only for low modulation level, and more iterations are desirable for high modulation level.

This paper jointly optimizes the precoding matrices and the set of active remote radio heads (RRHs) to minimize the network power consumption for a user-centric cloud radio access network, where both the RRHs and users have multiple antennas and each user is served by its nearby RRHs. Both users' rate requirements and per-RRH power constraints are considered. Due to these conflicting constraints, this optimization problem may be infeasible. In this paper, we propose to solve this problem in two stages. In Stage I, a low-complexity user selection algorithm is proposed to find the largest subset of feasible users. In Stage II, a low-complexity algorithm is proposed to solve the optimization problem with the users selected from Stage I. Specifically, the re-weighted l1-norm minimization method is used to transform the original problem with non-smooth objective function into a series of weighted power minimization (WPM) problems, each of which can be solved by the weighted minimum mean square error (WMMSE) method. The solution obtained by the WMMSE method is proved to satisfy the Karush-Kuhn-Tucker conditions of the WPM problem. Moreover, a low-complexity algorithm based on Newton's method and the gradient descent method is developed to update the precoder matrices in each iteration of the WMMSE method. Simulation results demonstrate the rapid convergence of the proposed algorithms and the benefits of equipping multiple antennas at the user side. Moreover, the proposed algorithm is shown to achieve near-optimal performance in terms of NPC.

Millimetre waves (mm-Waves) with massive multiple input and multiple output (MIMO) have the potential to fulfill fifth generation (5G) traffic demands. In this paper, a hybrid digital-to-analog (D-A) precoding system is investigated and a particle swarm optimisation (PSO) based joint D-A precoding optimisation algorithm is proposed. This algorithm maximises the capacity of the hybrid D-A mm-Wave massive MIMO system. The proposed algorithm is compared with three known hybrid D-A precoding algorithms. The analytical and simulation results show that the proposed algorithm achieves higher capacity than the existing hybrid D-A precoding algorithms.

Millimeter-wave (mm-Wave) systems with hybrid digital-to-analog beamforming (D-A BF) have the potential to fulfill 5G traffic demands. The capacity of mmWave systems is severely limited as each radio frequency (RF) transceiver chain in current base station (BS) architectures support only a particular user. In order to overcome this problem when high density of users are present, a new algorithm is proposed in this paper. This algorithm operates on the principle of selection combining (SC). This algorithm is compared with the state of the art hybrid D-A BF. The simulation results show that our proposed hybrid D-A BF using SC supports higher density of users per RF chain. Furthermore, our proposed algorithm achieves higher capacity than what is achieved by the current hybrid D-A BF systems.

This paper jointly optimizes the precoding matrices and the set of active remote radio heads (RRHs) to minimize the network power consumption for a cloud radio access network (C-RAN) where both the RRHs and users all have multiple antennas. Both users' rate requirements and per-RRH power constraints are considered. Due to these conflicting constraints, this optimization problem may be infeasible. We propose to solve this problem with two phases. In Phase I, a new approach is proposed to check the feasibility of the original problem. If the feasibility is guaranteed, in Phase II, a low- complexity algorithm is proposed to solve the original optimization problem. Simulation results demonstrate the rapid convergence of the proposed algorithms and the benefits of equipping multiple antennas at the user side.

In this paper, a closed-form expression of the outage probability in a downlink two-tier heterogeneous network (HetNet) is derived. The second tier uses dedicated spectrum and adopts an unsynchronized time division duplex (TDD) system with a dynamic frame configuration. The marked point process is used to model both locations of transmitters (users equipment/small cell base station), in addition to the time that has passed through each small cell sub-frame at any time of a small cell sub-frame of interest. The system performance is evaluated under different traffic dominators (uplink and downlink) by taking into account the impact of the structure of the frame- configurations. Furthermore, the system parameters, such as small cell density and the uplink control factor, are also evaluated.

Wireless networks are today employed as complementary access technology, implemented on the last hop towards the Internet end-user. The shared media that wireless deployments provide and which is relevant to interconnect multiple users has a limited technical design, as only one device can be served per unit of time, design aspect that limits the potential applicability of wireless in dense environments. This paper proposes and evaluates a novel MAC-layer mechanism that extends current wireless networks with the possibility to perform downstream transmission to multiple devices within a single transmission time-frame, resulting in improved fairness for all devices. The mechanism, which is software-defined, is backward-compatible with current wireless standards and does not require any hardware changes. The solution has been validated in a realistic testbed, and the paper provides details concerning the computational aspects of our solution; a description of the implementation; and results extracted under different realistic scenarios in terms of throughput, packet loss, as well as jitter.

This paper addresses the beam allocation problem in a switched-beam based massive multiple-input-multiple-output (MIMO) system working at the millimeter wave frequency band, with the target of maximizing the sum data rate. This beam allocation problem can be formulated as a combinatorial optimization problem under two constraints that each user uses at most one beam for its data transmission and each beam serves at most one user. The brute-force search is a straightforward method to solve this optimization problem. However, for a massive MIMO system with a large number of beams N, the brute-force search results in intractable complexity O(NK), where K is the number of users. In this paper, in order to solve the beam allocation problem with affordable complexity, a suboptimal low-complexity beam allocation (LBA) algorithm is developed based on submodular optimization theory, which has been shown to be a powerful tool for solving combinatorial optimization problems. Simulation results show that our proposed LBA algorithm achieves nearly optimal sum data rate with complexity O(K log N). Furthermore, the average service ratio, i.e., the ratio of the number of users being served to the total number of users, is theoretically analyzed and derived as an explicit function of the ratio N/K.

Massive multiple-input multiple-output (MIMO) is a promising technique to greatly increase the spectral efficiency and may be adopted by the next generation mobile communication systems. Base stations (BSs) equipped with large-scale antennas can serve multiple users simultaneously by exploiting the downlink precoding in time division duplex (TDD) mode. However, channel state information (CSI) of uplink transmissions cannot be simply used for downlink precoding, because the gain mismatches of the transceiver radio frequency (RF) circuits disable the channel reciprocity. In this paper, we focus on antenna calibration for massive MIMO systems with maximal ratio transmit (MRT) precoding to solve the channel nonreciprocity problem. A new calibration method, called mutual coupling calibration, is proposed by using the effect of mutual coupling between adjacent antennas. By exploiting this method, the BS can perform the calibration without extra hardware circuit and users' involvement. We also build up the model of calibration error and derive the closed-form expressions of the ergodic sum-rates for evaluating the impact of calibration error on system performance. Simulation results verify the high calibration accuracy of the proposed method and show the significant improvement of system performance by performing antenna calibration.

In this paper, a novel interference cancellation (IC) technique is proposed for asynchronous non-orthogonal multiple access (NOMA) systems. The bit error rate (BER) performance of an uplink NOMA system with the proposed IC technique is presented. Numerical and simulation results have shown that NOMA with the proposed asynchronous IC technique outperforms NOMA with a conventional-IC technique for uplink transmissions. It is also shown that employing iterative IC provides significant performance gain in NOMA and the number of required iterations depends on the modulation level and the received power ratio between users.

The channel state information (CSI) is used to optimise data transmission in time division duplex (TDD) systems, which is obtained at the time of channel estimation. The actual channel of data transmission at downlink time slot is different from the estimated channel due to channel variation in user movement environment. In this paper the impact of different user mobility on TDD downlink multiuser distributed antenna system is investigated. Based on mobility state information (MSI), an autocorrelation based feedback interval technique is proposed and updates CSI and mitigate the performance degradation imposed by the user speed and transmission delay. Cooperative clusters are formed to maximize sum rate and a channel gain based antenna selection and user clustering based on SINR threshold is applied to reduce computational complexity. Numerical results show that the proposed scheme can provide improved sum rate over the non cooperative system and no MSI knowledge. The proposed technique has good performance for wide range of speed and suitable for future wireless communication systems.

In this paper, a novel interference cancellation technique is proposed for asynchronous non-orthogonal multiple access (NOMA) systems and the performance is theoretically investigated in a small cell uplink scenario. It is shown that unlike synchronous communications, at uplink transmission, NOMA users' performance strongly depends on the relative time offset between interfering users.

Device-to-device (D2D) communication is proposed as a vital technology to increase the system capacity and spectral efficiency, while reducing the latency and energy consumption. Existing researches usually investigate the resource allocation for D2D communications underlaying the orthogonal frequency division multiple access (OFDMA) based cellular network, un- der the scenario in which spectrum can be spatially reused. However, most of these researches did not consider individual power constraint of each D2D device (e.g. a smart phone), which is generally limited for every device. Therefore, with the consideration of the transmit power limitation per device, the resource allocation issue is investigated in this paper for the multiple D2D pairs underlaid OFDMA-based cellular system with the target of achieving the optimal system throughput. By exploring the relationship between the number of subcarriers per D2D pair and maximum power constraint for each D2D pair, a sub-optimal joint power and subcarrier allocation algorithm is proposed to achieve high spectral efficiency with low complexity. Simulation results demonstrate that the performance of the proposed algorithm is very close to the optimal solution obtained by global exhaustive searching method. Meanwhile, the effect of number of subcarriers allocated to each D2D pair on the system performance is analysed through simulation results.

This paper focuses on the beam allocation problem with the target of maximizing the sum rate in a switched-beam based massive multiple input multiple output (MIMO) system working at the millimeter wave (mmWave) frequency band. A simple suboptimal beam allocation algorithm is developed, whose average sum rate performance is shown to be nearly optimal while the complexity is greatly reduced. Different from conventional switched-beam systems, with a large number of beams in the massive MIMO systems, the inter-beam interference closely depends on the beam allocation result. By adopting the suboptimal beam allocation algorithm, the effect of the inter-beam interference is investigated through simulations. The results further show that the average sum rate increases with both the number of BS antenna elements and the number of users even though the inter-beam interference is enlarged with an increasing number of users.

Providing high data rate wireless transmissions has been difficult in indoor environments, particularly in multi-floor buildings. One way to achieve high data rate wireless transmissions is to reduce the radio transmission distance between the transmitter and the receiver by using distributed antenna systems (DASs) and employing frequency reuse. However, due to the reuse of the limited available spectrum, co-channel interference can severely degrade system capacity. In this paper, the uplink spectral efficiency of an in-building DAS with frequency reuse is studied, where remote antenna units (RAUs) deployed on each floor throughout the building are connected to a central unit (CU) where received signals are processed. The impact of co-channel interference on system performance is investigated by using a propagation channel model derived from multi-floor, in-building measurement results. The proposed scheme exploits the penetration loss of the signal through the floors, resulting in frequency reuse in spatially separated floors, which increases system spectral efficiency and also reduces co-channel interference. A comparative analysis with conventional co-located antenna deployment at the floor center is provided. Location based RAU selection and deployment options are investigated. System performance is evaluated in terms of location-specific spectral efficiency for a range of potential mobile terminal (MT) locations and various in-building propagation characteristics.

As a promising technology, Device-to-device (D2D) communication as an underlay to cellular mobile networks is proposed to improve the spectral and energy efficiency. In OFDMA cellular networks, fractional frequency reuse (FFR) is an efficient frequency reuse scheme. This paper focuses on analysing the performance of D2D communications as an underlay to the FFR based OFDMA cellular network and analytically evaluates how spectral efficiency performance is affected by parameters, such as the ratio of the transmit power for the D2D transmission to that for the cellular transmission and radius ratio of the central area to the whole cell. Also, the optimal radius ratio to achieve the highest spectral efficiency is investigated for the D2D communication underlaying to the OFDMA cellular network.

In the orthogonal frequency division multiple access (OFDMA) system, one of the efficient and low complex methods to allocate radio resources among multiple users is chunk-based resource allocation, which groups a number of adjacent subcarriers into a chunk and allocates resources chunk by chunk. In this paper, performance analysis of chunk-based resource allocation is studied in the multi-cell OFDMA environment. Fractional frequency reuse (FFR) is considered in the cellular OFDMA. Basically, FFR divides each cell into central and edge areas where two different values of the frequency reuse factor are assumed. This paper analytically evaluates how spectral efficiency performance is affected by system parameters, including radius ratio of the central area to the whole cell, transmit signal to noise ratio (SNR), number of users, number of subcarriers per chunk, and coherence bandwidth. The numerical results show that there exists an optimal radius ratio to achieve the highest spectral efficiency in the proposed research. The optimal radius ratio is about 0.7, which is almost irrespective of the SNR, number of users, and number of subcarriers per chunk. In other words, the sizes of the central area and the edge area of the whole cell are almost equal when achieving the optimal performance.

It is well known that providing high data rate wireless mobile services is a major challenge in indoor environments, particularly in multi-storey buildings. One way to achieve high data rate wireless transmissions is to reduce the radio transmission distance between the transmitter and the receiver by using distributed antenna systems (DASs) employing frequency reuse. However, due to the reuse of the limited available frequency spectrum, co-channel interference can severely degrade system performance. In this paper, the uplink performance of an in-building DAS with frequency reuse is studied, where remote antenna units (RAUs) deployed on each floor throughout the building are connected to a central unit (CU) where received signals are processed. The impact of RAU selection and location strategies on the performance of the interference-limited system is analysed by using a propagation channel model derived from multi-floor, in-building measurement results. The proposed scheme exploits the penetration loss of the signal through the floors, resulting in frequency reuse in spatially separated floors, which increases system spectral efficiency and also reduces co-channel interference. RAU location is shown to be a dominant factor influencing the levels of co-channel interference, and consequently, have a major implications on system performance.

This paper presents comprehensive performance analyses of a novel scheduling policy for wireless communications where users have mixed real-time (RT) and non-real-time (nRT) traffic. Also, it introduces novel characteristics to scheduling where the QoS perceived by RT and nRT streams within a mixed traffic system can be differentiated and managed. Performance comparisons with popular proportional fair scheduling policy as well as the convergence analysis are also included.

In this paper, the achievable rate of distributed antenna systems (DASs) in high buildings is investigated for indoor downlink high data rate wireless transmission. A DAS, where radio transmission/reception within one or several neighbouring floors is controlled by a central unit (CU) exploiting the entire system bandwidth is considered. The same frequency channels are reused by all the CUs, co-channel interference is caused. A mathematical channel model for transmission to one user per floor including direct signal propagation between floors within the building and reflection from a nearby building is built based on practical measurements. Using the model, it is shown that the indoor path loss exponent and the Nakagami channel fading parameter have a significant effect on the achievable rate performance.

The distributed antenna system (DAS) is a promising system to provide high data rate transmissions in wireless communications. So far, most researches in the performance analysis for the DAS have been focused on single-user cases. This paper aims to investigate and present an optimal resource allocation scheme in downlink multiuser DASs. Different from the resource allocation in a conventional cellular system, the resource allocation in the multiuser DAS must consider multiple channel conditions of the transmission links between multiple remote antenna unites (RAUs) and any user, which increases the complexity of the resource allocation. In order to provide insights in the multiuser DAS, the effect of the number of RAUs used to communicate with each user is investigated extensively. In addition to power allocation, subcarrier allocation and bit allocation are studied in the orthogonal frequency division multiple access (OFDMA) DAS. To reduce the complexity of the resource allocation in the downlink multiuser DAS, the chunk allocation technique is adopted by grouping a set of contiguous subcarriers into one chunk and allocating resources chunk by chunk to users and an equivalent channel fading factor per subcarrier for a user is proposed to represent the combined channel gain from multiple RAUs to the user. The numerical results show that by using the proposed resource allocation method, each user only needs to be connected to a few RAUs, depending on the location of the user.

Over the last few years high data rate wireless transmission has gained considerable attention in hot spot areas, including high buildings. It has been demonstrated that distributed antenna systems (DASs) improve the performance of the indoor environment by covering dead spots. In this paper, the achievable rate is investigated for indoor high data rate wireless transmission in high buildings when DASs are employed. In the system, radio transmission/reception within one or several neighbouring floors is controlled by one central unit (CU) exploiting the entire system bandwidth. In order to efficiently use the spectrum, the same frequency channels are reused among floors controlled by different CUs. The radio signals in high buildings can propagate vertically and reach the neighbouring floors. Therefore, the performance of the system is limited by cochannel interference. Direct propagation inside the building and reflection from nearby buildings are considered in the channel model. The achievable rate of the system is evaluated through analysis and simulation. The impact of representative system parameters on the achievable rate, including the number of remote antenna units (RAUs), the frequency reuse factor, the floor penetration loss, the path loss exponent, and the Nakagami fading parameter, is discussed.

This paper presents a novel scheduling policy for wireless communications where users contain mixed real-time (RT) and non-real-time (nRT) traffic. The proposed policy introduces a novel tradeoff concept in scheduling, where a value of quality of service (QoS) satisfaction can be traded off with the achievable system throughput. Two weighting factors, corresponding to RT and nRT traffic, are introduced in the novel scheduling policy. The proposed policy is evaluated by simulation results. The simulation results show an optimal range of the weights to meet QoS satisfactions.

In this paper, the impact of co-channel interference on the achievable uplink spectral efficiency of an in-building wireless communication system employing DAS is examined. In the system, remote antenna units (RAUs) are deployed on each floor throughout the building and connected to a central unit (CU) where received signals are processed. System performance is investigated by using a propagation channel model derived from multi-floor, in-building measurement results. The proposed scheme exploits the penetration loss of the signal through the floors, resulting in frequency reuse in spatially separated floors, which increases system spectral efficiency and also reduces co-channel interference. Location based RAU selection and deployment options are investigated. System performance is evaluated in terms of location-specific spectral efficiency for a range of potential mobile terminal (MT) locations and various in-building propagation characteristics.

In OFDMA systems, chunk-based resource allocation is an effective approach to reduce the complexity of resource allocation by grouping a number of adjacent subcarriers into a chunk and allocating resources chunk by chunk. In this paper, chunk-based resource allocation is investigated in a multi-cell environment. To improve the spectral efficiency in the multi-cell system, fractional frequency reuse (FFR) is also adopted in the chunk-based OFDMA system. After theoretically analyzing the spectral efficiency of the chunk-based OFDMA system with FFR, the optimal value of the radius ratio, which is the ratio of the radius of the central area to the radius of the cell, to achieve the optimum system performance is given by numerical simulations. Numerical results show that the average spectral efficiency increases with increasing the number of users in the system. However, the value of the radius ratio to achieve the largest spectral efficiency is not affected by the number of users or the number of subcarriers per chunk.

This paper presents a behavioral fairness-based resource allocation (RA) algorithm for uplink transmission of a multiuser orthogonal frequency division multiplexing system. The aim of fairness- based RA is to boost users' willingness to start and keep cooperating with each other and behave well to keep their trust and reputation high. An interesting notion of differentiated streams is also included in the proposed RA, which can fine-tune RA result to transfer excess bandwidth and power from real-time streams to non-real-time streams, i.e. increase useful throughput. In order to reduce the complexity of RA, a set of contiguous subchannels are grouped into a chunk to allocate resource chunk by chunk. The effects of users' contribution and the number of subchannels grouped in a chunk on the average throughput is analyzed and shown by numerical simulations.

Distributed antenna system (DAS) can provide high speed data services for mobile terminals (MTs) within multi-floor buildings by reducing the radio transmission distance between the transmitter and the receiver. In this paper, the uplink spectral efficiency of an in-building DAS with frequency reuse is studied, where remote antenna units (RAUs) are deployed on each floor throughout the building and connected to a central unit (CU) where received signals are processed. The proposed scheme exploits the penetration loss of the signal through the floors, resulting in frequency reuse in spatially separated floors, which increases system spectral efficiency and also reduces co-channel interference. The impact of co-channel interference on system performance is investigated using a propagation channel model derived from multi-floor in-building measurement results. System performance is evaluated in terms of location-specific spectral efficiency for a range of potential mobile terminal (MT) locations and various in-building propagation characteristics. Numerical results obtained suggest that the proposed scheme can facilitate better use of the available radio spectrum, and provide higher data rates for indoor MTs.

With the deployment of high speed train (HST) systems increasing worldwide and their popularity with travelers growing, providing broadband wireless communications (BWC) in HSTs is becoming crucial. In this paper, a tutorial is presented on recent research into BWC provision for HSTs. The basic HST BWC network architecture is described. Two potential cellular architectures, microcells and distributed antenna systems (DASs) based cells, are introduced. In particular, the DAS is discussed in conjunction with radio over fiber (RoF) technology for BWC for HSTs. The technical challenges in providing DAS-based BWC for HSTs, such as handoff and RoF are discussed and outlined.

In high speed train (HST) system, real-time multimedia entertainments are very important applications in which a data stream often contains packets with different quality of service requirements. For example, video stream encoded with scalability contains the base layer packets with high quality (HQ) bit error rate (BER) requirement and enhancement layers' packets with low quality (LQ) BER requirement. When a conventional allocation approach, which only considers one BER constraint for one data stream, is applied to orthogonal frequency division multiple access (OFDMA) systems, the BER constraint will be the strictest one among multiple requirements from different types of packets, which leads to inefficient allocation when each data stream has multiple BER requirements. This paper aims to develop novel resource allocation approach by considering multiple BER requirements for different types of packets in one data stream. In order to not only simplify the resource allocation, but also to compensate for the channel estimation error caused by Doppler shift in the HST environment, a proper number of contiguous subcarriers are grouped into chunks and spectrum is allocated chunk by chunk. Simulation results show that the developed resource allocation scheme outperforms the conventional scheme, particularly when the BER ratio of HQ packets to LQ packets is larger than one. Furthermore, in order to reduce the complexity of resource allocation further, an empirical allocation scheme is proposed to allocate better chunks to HQ packets. It is shown that the performance of the empirical allocation scheme is quite close to that of the optimal scheme.

By grouping a number of adjacent subcarriers into a chunk, resource allocation can be carried out chunk by chunk in orthogonal frequency division multiple access (OFDMA) systems. Chunk-based resource allocation is an effective approach to reduce the complexity of resource allocation in OFDMA systems. In this paper, a chunk-based resource allocation scheme, i.e. joint chunk, power and bit allocation, is proposed and analyzed by maximizing the throughput under a total transmit power constraint. A scaling factor is introduced to achieve optimal allocation. Considering the digital nature of bits per symbol per subcarrier (bits/symbol/subcarrier), a digitization process is proposed to digitize the theoretically allocated bits/symbol/subcarrier to integer. System parameters, such as the power constraint, number of users, coherence bandwidth, number of subcarriers and number of chunks, are introduced and their impacts on the average throughput are studied. The performance of the dynamic power allocation scheme is compared with the fixed power allocation scheme. The numerical results show that the theoretical throughput of the fixed power allocation scheme is quite close to that of the dynamic power allocation scheme. However, when the digital nature of bits/symbol/subcarrier is considered, the average throughput of the dynamic power allocation outperforms the fixed power allocation scheme.

In wireless systems, providing high data rate wireless services is a major challenge particularly in high building environments. The system performance is impaired by co-channel interference due to the need to reuse the limited available spectrum. In this environment, distributed antenna systems (DASs) can provide adequate coverage and high speed data services in the presence of multipath fading and co-channel interference by optimally combining the same signal from several antennas. This paper proposes and investigates the impacts of DAS for uplink transmission in high-rise buildings; where remote antenna units (RAUs) are deployed on each floor to reduce the radio transmission distance while at the same time exploiting spatial diversity. The RAUs are connected to a central unit (CU) where received signals are processed. The performance of the system is analysed in terms of achievable spectral efficiency using a propagation channel model derived from multi-floor in-building path loss values retrieved from measurement data. This model accounts for the propagation between different floors and ceilings and includes possible reflections from surrounding buildings. The effects of different numbers of receive antennas per floor and deployment conditions are investigated. Numerical results obtained suggest that the proposed scheme can facilitate better use of the available radio spectrum and provide higher data rates for indoor mobile terminals (MTs).

The distributed antenna system (DAS) is a promising system to provide high data rate for future wireless communications, since it can reduce the radio transmission distance. This paper aims to investigate the average spectrum efficiency and the cell edge spectrum efficiency in the downlink transmission of the DAS. Firstly, the approach of antenna unit selection for spatial diversity is presented in the DAS without frequency reuse. Then, to achieve high spectrum efficiency, frequency reuse is exploited in the DAS. In order to show the advantage of frequency reuse, the spectrum efficiency of the DAS with frequency reuse is theoretically compared with the DAS without frequency reuse. Numerical results show that reusing frequency in the DAS can increase the spectrum efficiency significantly. It also shows that when the frequency reuse area increases, the performance gain from the frequency reuse is impaired because of the increase of the co-channel interference.

Over the last few years high data rate wireless transmission has gained considerable attention in hot spot areas, including high buildings. It has been demonstrated that distributed antenna systems (DASs) improve the performance of the indoor environment by covering dead spots. In this paper, the DAS is investigated in high building to provide high data rates for indoor wireless mobile communications by exploiting spatial diversity and reducing radio transmission distance. In the proposed indoor DAS, several neighbouring floors compose a floor-bank and are controlled by one central unit (CU). The spectrum is not reused in a floor-bank, but can be reused among different floor-banks, which causes co-channel interference. In order to analyse the performance of the indoor DAS in high building with the presence of co-channel interference, an accurate propagation model of the interference from other floor is a key requirement. Direct propagation inside the building and reflection from nearby buildings have been considered in the channel model. Based on the theoretical analysis, the impact of several system parameters on the performance is presented in terms of BER. Numerical results indicate that the position of the user in the floor has significant effect on the system performance and the attenuation introduced by the floor separation in high buildings should be taken into consideration during the planning of the number of floor in each floor-bank.

Indoor mobile communication systems are expected to provide significantly higher data rates and coverage than that offered by the conventional microcell system. However, the system performance is impaired by co-channel interference due to the need to reuse the limited available spectrum. To mitigate the effect of co-channel interference in this environment, distributed antenna systems (DASs) can be used to reduces the overall transmit power (and hence co-channel interference) by shortening the radio transmission distance between the transmitter and the receiver. In this paper, the impacts of DAS on uplink transmission in high-rise buildings is investigated, where remote antenna units (RAUs) are deployed on each floor throughout the building and connected to a central unit (CU) where received signals are processed. The performance of the system is analysed using a propagation channel model derived from multi-floor in-building path loss values retrieved from measurement data. For different system parameters, the average spectral efficiency is computed for a given maximum required BER, and parameters which yield the maximum spectral efficiency are identified. Numerical results obtained suggest that the proposed scheme can facilitate better use of the available radio spectrum, and provide higher data rates for indoor MTs.

Performance of distributed antenna systems (DASs) is investigated for high data rates transmission in high buildings. Downlink transmission is considered, neighbouring floors are grouped together and controlled by a central unit (CU). The spectrum is not reused in the floors controlled by the same CU, however it can be reused among floors belonging to different CUs. Therefore, co-channel interference occurs among CUs. Radio signals can propagate among floors in high buildings and reflections from a nearby buildings can have an effect on the performance. In this paper, the effect of the frequency reuse factor on the channel capacity performance is shown.

In wireless systems, coverage and capacity is a major challenge especially in high buildings. The system performance is impaired by co-channel interference due to the need to reuse the limited available spectrum in neighbouring floors. In this environment, distributed antenna systems (DASs) can provide adequate coverage and high speed data services in the presence of multipath fading and co-channel interference by optimally combining the same signal from several antennas. This paper proposes a DAS for uplink transmission in high-rise buildings; where remote antenna units (RAUs) are deployed on each floor so as to reduce the access distance while at the same time exploiting spatial diversity. The RAUs are connected to a central unit (CU) where received signals are processed. To analyse the bit error rate (BER) performance of the system with diversity reception, Nakagami/Rayleigh fading channel is assumed for different building geometries and a propagation channel model for in-building propagation is developed based on multiple floor in-building path loss values retrieved from measurement data. This model accounts for the propagation between different floors and ceilings and includes possible reflections from surrounding buildings. The effects of different numbers of receive antennas per floor and deployment conditions are investigated. Numerical results indicate that the proposed scheme provides improved BER performance, leading to many more simultaneous users being supported on the same frequency in high buildings when compared with a system with a single antenna per floor.

In wireless systems, providing high data rate wireless services is a major challenge, particularly for mobile terminals (MTs) in multi-floor buildings. The system performance is impaired by co-channel interference due to the need to reuse the limited available spectrum. One way to achieve higher data rates and better signal quality in this environment, is to reduce the radio transmission distance between the transmitter and the receiver through the use of distributed antenna systems (DASs). DAS reduces the overall transmit power (and hence co-channel interference) while at the same time exploiting spatial diversity. This paper proposes and investigates the impacts of DAS for uplink transmission in high-rise buildings; where remote antenna units (RAUs) are deployed on each floor throughout the building and connected to a central unit (CU) where received signals are processed. The performance of the system is analysed in terms of achievable spectral efficiency for a variety of system parameters and deployment conditions using a propagation channel model derived from multi-floor in-building path loss values retrieved from measurement data. Numerical results obtained suggest that the proposed scheme can facilitate better use of the available radio spectrum and provide higher data rates for indoor MTs than the conventional macrocell system using centralised base station antennas.

In this paper, the packet combining technique in the downlink OFDMA system is introduced in conjunction with frequency diversity to enhance the reliability of retransmissions and thus reduce the large time delay caused by retransmissions. The novel retransmission technique aims to reduce the maximum number of retransmissions for failed packets, while maximizing the throughput. A suboptimal algorithm is proposed, in which the retransmitted packets have higher priorities to be given resources than new packets. At the receiver, failed and retransmitted packets are combined before detection by using maximal ratio combining (MRC). It is shown that the proposed retransmission scheme can reduce the maximum packet delay significantly, while maintaining the maximum throughput of the conventional retransmission schemes.

It has been demonstrated that distributed antenna systems (DASs) improve the transmission performance in indoor environment by reducing the radio transmission distance and providing macro diversity. In this paper, indoor DAS is proposed for high building environments. The objective is to provide high data rate transmission for indoor mobile users. The radio signal in high buildings can propagate through floors, a mathematical channel model is proposed in this work based on measurement results. The spectrum is reused among floors but can not be used in the same floor. Therefore co-channel interference exists between floors using the same frequency. Theoretical analysis is presented based on the mathematical channel model proposed. The performance of the system is evaluated in terms of bit error rate (BER) and the effect of the frequency reuse factor is presented. It is demonstrated as well that the shape of the floor and the deployment of the RAUs have a significant effect on the BER performance.

In this paper, a distributed antenna system (DAS) is investigated for indoor high data rate wireless transmission in high buildings. In the proposed indoor DAS, radio transmission/ reception within several neighbouring floors is controlled by one central unit (CU) by exploiting the whole system bandwidth. However, the frequency channels can be reused among the CUs which results in co-channel interference. The capacity of the system is analyzed considering direct propagation inside the building and reflection from a nearby building. The impact of several system parameters, such as the position of the user on the floor, the number of remote antenna units (RAUs), the shape of the floor and the position of the RAUs on the performance is discussed.

With the capability of reducing the radio transmission distance, the microcellular system and distributed antenna system (DAS) became two promising systems to provide high data rate for future wireless communications. In this paper, in order to achieve high spectrum efficiency, spectrum reuse is exploited in both of the microcellular system and the DAS. The performances between the two systems are theoretically compared in a network topology with seven macrocells. Numerical results show that, when spectrum reuse is adopted, the spectrum efficiency in the DAS is larger than these in the microcellular system.

The microcellular system and distributed antenna system (DAS) are two promising systems to provide high data rate for future wireless communications, especially for the cell edge of the macrocell, because both systems can reduce the radio transmission distance. The cell edge spectrum efficiency is theoretically compared between the two systems in a network topology with seven macrocells, each of which has seven hexagonal sectors. Numerical results show that, when the spatial diversity and spectrum reuse are adopted in the DAS, the cell edge spectrum efficiencies per sector in the DAS is larger than these in the microcellular system.

The microcellular system and distributed antenna system (DAS) are two promising systems for future high data rate wireless communications, since both systems can reduce the radio transmission distance between the transmitter and the receiver. This paper aims to compare the average spectrum efficiency and the cell edge spectrum efficiency between the two cellular systems in the downlink transmission. In order to achieve high spectrum efficiency, frequency reuse and/or spatial diversity are exploited in these two systems. The performances between the two cellular systems are theoretically compared in a network topology with seven macrocells, each of which has seven hexagonal sectors (or microcells). Moreover, the approach of antenna unit selection in the DAS for spatial diversity is presented. Numerical results show that the average spectrum efficiency per sector and the cell edge spectrum efficiency in the microcellular system are better than those in the DAS without frequency reuse. However, when the frequency reuse is considered in the DAS, the DAS outperforms the microcellular system in both of the average and cell edge spectrum efficiencies.

In this paper, the performance of multi-level quadrature amplitude modulation (M-QAM) systems is studied analytically when Alamouti space-time transmit diversity (STTD) coding is used for transmission over Rayleigh fading channels. The effect of self-interference (interference from another simultaneously transmitted symbol in the STTD scheme for the same user) due to imperfect channel estimation is investigated. Based on the characteristic function method, a closed-form expression of the bit error rate (BER) is derived. Numerical results for 16/64-QAM show that, with the Alamouti STTD technique, the BER performance of the QAM system can be improved significantly. The effect of receive antenna diversity is also investigated. It is shown that high-order QAM constellations can be employed even in low signal to noise ratio (SNR) with the transmit diversity technique in conjunction with receive antenna diversity.

In wireless systems, coverage and capacity is a major challenge especially in high buildings. The need to reuse the limited available spectrum results in cochannel interference. Cochannel interference is a very critical factor affecting system performance. It limits the uplink coverage and capacity of wireless networks such as femtocells. Joint processing of the received signal among cochannel receivers has recently been shown to be very beneficial from an interference cancellation point of view. This paper proposes a femtocell based distributed antenna system (DAS) for uplink transmission in high buildings where distributed antenna units deployed on each floor of the building are connected to femto base stations (BS). The femto BSs can cooperate through joint signal processing for all cells in order to estimate the received signal, reduce cochannel interference introduced by frequency reuse among the femtocells and maintain high spectral efficiency. Analysis and numerical results show remarkable gains especially when interference cancellation is employed at each cooperative femto BS, leading to many more simultaneous users being supported on the same frequency and resulting in large capacity increase when compared with the traditional system with no interference cancellation technique.

In orthogonal frequency division multiple access (OFDMA) systems, efficient resource allocation is very important to improve the performance of the OFDMA system. In this paper, the resource allocation scheme is investigated by considering different criterions to packets on first transmissions and on retransmissions. Under a bit error rate (BER) constraint, the objective is to maximize the throughput of packets on first transmissions, meanwhile decreasing the longest packet delay caused by retransmitted packets and guaranteeing all packets on retransmissions to be sent out. A low-complexity suboptimal algorithm that separates allocation for packets on retransmissions and on first transmissions is proposed. Adaptive modulation scheme is adopted to guarantee the BER constraint, except the modulation for each retransmitted packet remains the same. In order to improve retransmission liability, the retransmitted packets are combined with its failed packets in previous transmission.

In this paper, performance analysis of multi-level quadrature amplitude modulation (M-QAM) systems with Alamouti space-time transmit diversity (STTD) in Rayleigh fading channels is analytically studied. The effect of self-interference (interference from another simultaneously transmitted symbol in the STTD from the same user) due to imperfect channel estimation is investigated. Based on the characteristic function method, an analytical bit error rate (BER) is presented in a closed form. Numerical results for M-QAM show that with Alamouti STTD technique, the BER performance of the M-QAM system improves significantly. In addition, the effect of receive antenna diversity is investigated. It is shown that high-level QAM can be employed even in low signal to noise ratio (SNR) with the STTD technique in conjunction with the receiving antenna diversity technique.

In orthogonal frequency division multiple access (OFDMA) systems, efficient resource allocation is very important to improve the performance of the OFDMA system. The general principle of resource allocation in an OFDMA system is to assign each subcarrier to the user with the best channel condition for that subcarrier. However, in delay tolerant traffic, current work did not consider that packets on retransmissions may have different allocation criteria from those on their first transmissions. In this paper, the resource allocation scheme is investigated by considering different criterions to packets on first transmissions and on retransmissions. Under a bit error rate (BER) constraint, the objective is to maximize the throughput of packets on first transmissions, meanwhile decreasing the longest packet delay caused by retransmitted packets and guaranteeing all packets on retransmissions to be sent out. A low-complexity suboptimal algorithm that separates allocation for packets on retransmissions and on first transmissions is proposed. Adaptive modulation scheme is adopted to guarantee the BER constraint, except the modulation for each retransmitted packet remains the same. In order to improve retransmission liability, the retransmitted packets are combined with its failed packets in previous transmission.

Over the last decade high data rate wireless transmission has gained considerable attention in hot spot areas, including high buildings. It has been demonstrated that distributed antenna systems (DASs) improve the performance of the indoor environment by providing spatial diversity and covering dead spots. In this paper, indoor wireless communications have been studied together with a femtocell based DAS. In this DAS, a femtocell managed by a central unit (CU) is deployed to cover several neighbouring floors, which compose a floor-bank. Since the radio spectrum becomes limited and expensive, the spectrum should be reused among different floor-banks. The performance of downlink DAS transmission is analysed in terms of bit error rate (BER) in the presence of co-channel interference from other floor-banks. Numerical results show that when decreasing the number of floors in a floor-bank, the BER performance degrades due to the strong co-channel interference. The number of floors in a floor-bank has a significant effect on the BER performance in high buildings.

In wireless systems, coverage and capacity is a major challenge especially in high buildings. The system performance is impaired by cochannel interference created due to the need to reuse the limited available spectrum in nearby floors. Each base station (BS) does not only receives signals from the desired user but also from cochannel interferers in the neighbouring floors, thereby limiting the coverage and capacity of the indoor networks. Joint processing of the received signal among cochannel receivers has drawn considerable attention in recent years due to its enormous benefits from an interference cancellation point of view. This paper proposes and investigates the uplink of a femtocell based distributed antenna systems (DAS) in high buildings where remote antenna units deployed (RAU) on each floor of the building are connected to femto BS. The femto BSs can cooperate through joint signal processing for all femtocells in order to estimate the received signal, reduce cochannel interference introduced by frequency reuse among the femtocells and maintain high spectral efficiency. Investigation and numerical results show remarkable gains especially when interference cancellation is employed at each cooperative femto BS, resulting in large capacity increase when compared with the traditional system with no interference cancellation technique.

This paper is focused on the study of layered space-time-frequency (LSTF) architectures with channel coding for orthogonal frequency division multiplexing (OFDM) multiple-input multiple-output (MIMO) multiplexing systems for high speed wireless communications over a frequency-selective fading channel. In order to achieve the available spatial, temporal and frequency diversities, and also make the system implementation feasible for high speed OFDM MIMO multiplexing, a novel LSTF architecture with multiple channel encoders is proposed with each independently coded layer being threaded in the three-dimensional (3-D) space-time-frequency transmission resource array. The maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD) is adopted. An irregular low-density parity-check (LDPC) code is chosen as the channel code. Simulation results show that the performance of the proposed multiple-encoders LSTF architecture is very close to that of the conventional single-encoder LSTF where coding is applied across the whole information stream. However, due to the use of multiple parallel encoders/decoders with a shorter codeword length, the proposed LSTF architecture is more suitable for high speed wireless communications.

In orthogonal frequency division multiple access (OFDMA) systems, efficient resource allocation is very important to improve the performance of the OFDMA system. The general principle of resource allocation in an OFDMA system is to assign each subcarrier to the user with the best channel condition for that subcarrier. However, in delay tolerant traffic, current work did not consider that packets on retransmissions may have different allocation criteria from those on their first transmissions. In this paper, the resource allocation scheme is investigated by considering different criterions to packets on first transmissions and on retransmissions. Under a bit error rate (BER) constraint, the objective is to maximize the throughput of packets on first transmissions, meanwhile decreasing the longest packet delay caused by retransmitted packets and guaranteeing all packets on retransmissions to be sent out. A low-complexity suboptimal algorithm that separates allocation for packets on retransmissions and on first transmissions is proposed. In the proposed algorithm, for packets on retransmissions the resource allocation can be formulated to minimize power consumption; for packets on first transmissions the resource allocation is carried out to maximize throughput. Adaptive modulation scheme is adopted to guarantee the BER constraint, except the modulation for each retransmitted packet remains the same. In order to improve retransmission liability, the retransmitted packets are combined with its failed packets in previous transmission.

In this paper, the performance of the downlink multicode CDMA systems with bit interleaved coded multi-level quadrature amplitude modulation (BIC-MQAM) is studied with the consideration of interference cancellation. Generally, multicode transmission and adaptive multi-level modulation are used for flexible data rate transmissions in CDMA systems. In order to improve the system performance, multistage parallel interference cancellation and soft decision Viterbi decoding techniques are employed at the receiver. An analytical closed form of bit error rate (BER) is derived in presence of pilot channel estimation error due to multipath interference. Numerical results show that by using interference cancellation, the multipath interference can be effectively reduced, which leads to significant performance improvement even in presence of both channel estimation error and multipath interference. Also, system throughput can be increased by using high-order modulation without extra bandwidth expansion.

In order to minimize the total transmit power in the downlink orthogonal frequency division multiplexing (OFDM) system, an adaptive resource management approach is proposed in this paper by considering that an application, such as real-time video and high quality music stream, can have different quality of service (QoS) requirements for different layers. When multiple layers are addressed in resource allocation, a chunk-based resource management scheme is performed. According to analysis, the proposed scheme can efficiently reduce the complexity. Simulation results show that the proposed resource management scheme outperforms the conventional single-queue resource management scheme, especially when the bit error rate (BER) ratio or the data rate ratio of the low priority layer to the high priority layer of data streams is large.

In this paper, performance analysis of multi-level quadrature amplitude modulation (M-QAM) systems is analytically studied when Alamouti space-time transmit diversity (STTD) in Rayleigh fading channels is exploited. The effect of self-interference (interference from another simultaneously transmitted symbol in the STTD from the same user) due to imperfect channel estimation is investigated. Based on the characteristic function method, a closed form of bit error rate (BER) is presented. Numerical results for 16/64-QAM show that with Alamouti STTD technique, the BER performance of the QAM system improves significantly. In addition, the effect of receive antenna diversity is investigated. It is shown that high-level QAM can be employed even in low signal to noise ratio (SNR) with the STTD technique in conjunction with the receive antenna diversity technique.

Chunk-based resource allocation can effectively reduce the complexity of resource allocation in multiuser orthogonal frequency division multiplexing (OFDM) systems by grouping a number of neighboring subcarriers into a chunk and being carried out chunk by chunk. To ensure the bit error rate (BER) constraint within a chunk, an adaptive BER-based chunk allocation scheme is proposed and analyzed in this paper with the objective of maximizing the average throughput under a limited total transmit power. Numerical results illustrate that under the same power constraint, the average throughput of the adaptive chunk allocation is very close to that of the subcarrier-based allocation in the multiuser OFDM system.

This paper analyzes throughput performance of the chunk-based subcarrier allocation by considering the average bit-error-rate (BER) constraint over a chunk in downlink multiuser orthogonal frequency division multiplexing (OFDM) transmission. The outage probabilities per subcarrier are compared between the average BER-constraint based chunk allocation and the average signal-to-noise-ratio (SNR) based chunk allocation. The effects of system parameters, including the coherence bandwidth, the number of subcarriers per chunk, and the number of users, are evaluated. The numerical results show that, when the chunk bandwidth is smaller than the coherence bandwidth, the average downlink throughput of the chunk-based subcarrier allocation is very close to that of the single-subcarrier-based allocation. The effective throughput of the average BER-constraint based chunk allocation is higher than that of the average SNR based chunk allocation, especially when the number of users is large.

In this paper, throughput performance analysis of the chunk-based subcarrier allocation is presented by considering the average bit-error-rate (BER) constraint over a chunk in downlink multiuser orthogonal frequency division multiplexing (OFDM) transmission. The outage probabilities per subcarrier are compared between the average BER-constraint based chunk allocation and the average signal-to-noise-ratio (SNR) based chunk allocation. The effects of system parameters, such as the number of users, the number of subcarriers per chunk, and the coherence bandwidth, are evaluated. The numerical results show that, when the chunk bandwidth is smaller than the coherence bandwidth, the average downlink throughput of the chunk-based subcarrier allocation is very close to that of the single-subcarrier-based allocation. When the number of users is small, the average throughput increases dramatically with increasing the number of users due to multiuser diversity, whereas when the number of users is large, the multiuser diversity gain is saturated. The effective throughput of the average BER-constraint based chunk allocation is higher than that of the average SNR based chunk allocation, especially when the number of users is large or when the ratio of the chunk bandwidth to the coherence bandwidth is large.

This paper concerns the design of robust controller for a nonlinear system that can be represented or approximated in a non-affine form. The control algorithm is based on sliding mode control that incorporates a fuzzy tuning technique, and it superposes equivalent control, switching control, and fuzzy control. An equivalent control law is firstly designed based on a nominal system model that was obtained by using curve fitting techniques underMATLAB. Switching control is then added to guarantee that the state reaches the sliding surface in the presence of parameter and disturbance uncertainties. Also, fuzzy tuning schemes, which can be supported by learning techniques derived from neural networks, are employed to improve control performance and to reduce chattering in the sliding mode. To verify the performance of this controller, an experimental platform of a pneumatically actuated top-guided single-seated control valve, which belongs to a classical complex nonlinear system, was constructed. Also, the experimental results show that high performance and attenuated chatter are achieved and thus verify the validity of the proposed control approach to dynamic systems characterized by severe uncertainties.

In wireless environments, the inherent time-varying characteristics of the channel pose great challenges on medium access control design. In recent years, multiuser diversity and opportunistic medium access control schemes have been proposed to deal with the channel variation in order to efficiently improve the network throughput. In this paper, we propose a novel MAC protocol called Contention-Based Prioritized Opportunistic (CBPO) Medium Access Control Protocol. This protocol takes advantage of multiuser diversity, rate adaptation, which utilizes the multi-rate capability offered by IEEE 802.11, and black-burst (BB) contention to access the shared medium in a distributed manner. In particular, rather than simply measuring the channel condition for a node pair in communications each time, with the help of multicast RTS, the candidate users with qualified channel condition are selected and prioritized. Then the qualified receivers contend to send back prioritized clear-to-send message (CTS) with BB, which is a pulse of energy, the duration of which is proportional to the CTS priority. The user with the best channel quality is always selected to send back CTS and receive packets from the sender. Extensive simulation results show that our protocol achieves much better performance than IEEE 802.11 and other auto rate schemes with minimal additional overhead.

Traditional traffic descriptor-based and measurement-based admission control schemes are typically combined with a node by node resource reservation scheme, rendering them unscalable. Although some Endpoint Admission Control schemes can resolve this problem, they impose significant signaling overhead. To cope with these two problems, this paper proposes a statistical connection admission control framework which can easily and efficiently estimate the network resource for a pair of ingress-egress nodes and make admission decision based on this estimated result. In this framework, the network is considered as a "black box." For a certain ingress-egress node pair, the egress node measures the QoS constraint violation ratio and feeds this information back to the ingress node periodically. With this information and the measured statistical characteristics of the existing aggregated traffic, the ingress node estimates the achievable capacity between the ingress-egress node pair, and makes the admission decision for a new traffic connection request. The signaling overhead of this framework is very small. Simulation results show the effective throughput is relatively high.

QoS routing, which satisfies diverse application requirements and optimizes network resource utilization, needs accurate link states to compute paths. Suitable link state update (LSU) algorithms which ensure timely propagation of link state information are thus critical. Since traffic fluctuation is one of the key reasons for link state uncertainty and existing approaches cannot effectively describe its statistical characteristics, we propose a novel stability-based (SB) LSU mechanism which consists of a second-moment-based triggering policy and a corresponding stability-based routing algorithm. They incorporate knowledge of link state stability in computing a stability measure for link metrics. With extensive simulations, we investigate the performance of the SB LSU mechanism and evaluate its effectiveness compared with existing approaches. Simulation results show that SB LSU can achieve good performance in terms of traffic rejection ratio, successful transmission ratio, efficient throughput and link state stability while maintaining a moderate volume of update traffic.