With the popularization of 5G technology and the growth of data traffic demands, cellular traffic prediction has become crucial for network management. However, existing methods face the following challenges: (1) Most studies only consider normal traffic and neglect the dynamic impact of external environmental changes; (2) Due to model complexity, existing methods rely on short-term data and struggle to capture long-term traffic trends. To address these issues, this paper proposes a Multi-Feature Adaptive Spatiotemporal Trend Network (MASTTN), which includes feature embedding, mask reconstruction, and spatiotemporal trend extraction modules. First, a gated unit dynamically integrates temporal, spatial, and external features to capture the multidimensional correlations of traffic. Next, a random mask reconstruction approach extracts new sequences containing trend information from longer historical time series. Finally, dilated causal convolution and short-term spatiotemporal feature extraction modules are used to refine both long- and short-term features. Experimental results show that MASTTN achieves a minimum improvement of 5.63% and a maximum improvement of 16.78% in long-term prediction over 120 minutes, compared to baseline models, and the effectiveness of each module is verified through perturbation experiments.

The full-space capability of the reconfigurable intelligent surface (RIS) provides an intelligent radio environment for information transmissions. This paper investigates the RIS-assisted secure transmissions in the presence of multiple eavesdroppers (Eves), where the colluding and the non-colluding behaviors of Eves are considered. We first propose a tractable Gamma distribution to characterize the distributions of the signal-to-noise ratio (SNR) under the Rayleigh, the Rice and the Nakagami-m channels. Then we derive the theoretical expressions of the average security capacity (ASC) for colluding and non-colluding eavesdroppers. Besides, the asymptotic expressions of the ASC are also obtained when the SNRs are large in practical scenarios. The simulation results demonstrate that the RIS is capable of reducing the negative impact of the increase in the number of eavesdroppers on the security performance by deploying more RIS elements in both colluding and non-colluding eavesdroppers.

With the increasing density of base stations, the energy consumption of the 5-th generation mobile networks (5G) has become a serious issue and has attracted attention. To address this challenge, a novel model-based reinforcement learning (MBRL) algorithm for joint base station advanced sleep mode (ASM) and power control is proposed, aiming at optimizing the energy efficiency of small-cell networks. Taking the data rate and delay requirements of users into consideration, we develop a small-cell network model with diverse types of users. The energy efficiency optimization problem is formulated as a Markov decision process (MDP) and a model-based reinforcement learning approach is designed to solve this problem. Simulation shows that the proposed algorithm converges quickly and achieves higher energy efficiency (EE) and lower packet loss rates, compared with baseline methods, especially in high-load and high-interference conditions. This study provides both theoretical and practical insights for the green development of 5G and future communication networks.

A user-centric no-cell (UCNC) architecture has been proposed to achieve a consistent user experience and enhance system capacity. However, high user mobility and complex network topologies present significant challenges in realizing these objectives. To tackle these challenges, we investigate the clustering and resource allocation problems in the UCNC network to maximize spectral efficiency (SE). We split this problem into two sub-problems: user-centric clustering and resource allocation. First, we propose a clustering algorithm based on mobility prediction and train a Long Short-Term Memory (LSTM) neural network to forecast user trajectories. Second, based on the clustering results, we develop an improved two-stage graph coloring algorithm to minimize interference between users and maximize resource block (RB) gains. Simulation results indicate that our proposed approach significantly outperforms the benchmark in terms of system SE while reducing signaling overhead produced by the updating of clusters.

The integrated communication and localization (ICAL) has become as a pivotal technology in the evolution towards B5G and 6G networks, particularly for a variety of emerging wireless applications. In ICAL networks, resource allocation and beamforming design are critical components that significantly influence both the precision of localization and the efficiency of communication. Moreover, high accuracy synchronization is extremely challenging in wireless networks. In this paper, we investigate the tradeoff between spectral efficiency (SE) and position error bound (PEB) by formulating a robust power and time-slot allocation and beamforming design problem for asynchronous ICAL networks with the imperfect initial position. We first illustrate the coupling between SE and position error through channel estimation error. Then, we derive a lower bound on the position error in terms of the Fisher information matrix (FIM). The alternating optimization, convex approximate and Bernstein-type inequality algorithms are proposed to solve the non-convex problems. Finally, the simulation results reveal the tradeoff between SE and PEB, and validate the robustness and effectiveness of the proposed algorithms.

In this paper, a 4-weighted-type fractional Fourier transform (4-WFRFT) technology is presented to enhance the physical layer security (PLS) performance in a system of multiple eavesdroppers. The average signal-to-noise ratio (SNR) of eavesdroppers is first derived. Based on the derived average SNR, closed-form expressions of average security capacity (ASC) and secrecy outage probability (SOP) are obtained by employing the 4-WFRFT technology. The numerical results demonstrate that: 1) when the number of eavesdroppers increases, the 4 -WFRFT technology can also obtain a higher secrecy capacity. 2) the ASC decreases first but finally keeps at a constant value as the number of eavesdroppers increases. Simulations verify our analysis and demonstrate the 4 -WFRFT technology can validly improve the PLS performance in the multiple eavesdroppers system.

Improving long-term user satisfaction in user-centric networks while ensuring an acceptable delay in the presence of an eavesdropper is an important yet challenging task. In this paper, we investigate a long-term secure resource allocation for a user-centric network. Our objective is to maximize the user's long-term average satisfaction by controlling the network-layer data arrival rate and physical-layer power allocation at access points. This objective is mainly constrained by average delay requirements, average leakage rate, and data-queue stability conditions. These constraints are challenging to directly solve because of less-analytical expressions. To tackle this issue, we introduce two virtual queues as the debt of delay and leakage data. By using a Lyapunov optimization approach, we incorporate the stabilities of these virtual queues and the real data backlog queue into the objective function as a penalty. This allows us to transform the long-term optimization problem into a sequence of short-term subproblems that can be analytically solved at each slot. Simulation reveals that the proposed long-term secure resource allocation scheme outperforms the snapshot-based method in terms of the user's long-term satisfaction.

Non-orthogonal multiple access (NOMA) is capable of serving different numbers of users in the same time-frequency resource element, and this feature can be leveraged to carry additional information. In the orthogonal frequency division multiplexing (OFDM) system, a novel enhanced NOMA scheme called NOMA with informative envelope (NOMA-IE) is proposed to explore extra flexibility from the envelope of NOMA signals. In this scheme, data bits are conveyed by the quantified signal envelope in addition to classic signal constellations. The subcarrier activation patterns of different users are jointly decided by the envelope former at the transmitter of NOMA-IE. At the receiver, successive interference cancellation (SIC) is employed, and the envelope detection coefficient is introduced to eliminate the error floor. Theoretical expressions of spectral efficiency, energy efficiency, and detection complexity are provided first. Then, considering the binary phase shift keying modulation, the block error rate and bit error rate are derived based on the two-subcarrier element. The analytical results reveal that the SIC error and the index error are the main factors degrading the error performance. The numerical results demonstrate the superiority of the NOMA-IE over the OFDM and OFDM-NOMA in terms of the error rate performance when all the schemes have the same spectral efficiency and energy efficiency.

Efficient information gathering is a critical task for the Internet of underwater things (IoUT) that empowers the marine industry, but energy-constrained devices have become a bottleneck in the sustainability of IoUT. In this article, we focus on the unmanned aerial vehicle (UAV)-aided marine data collection in an air–ocean integrated network. We consider the mobility of buoys caused by waves during a collection period to achieve robust transmission, instead of assuming stationary buoys. Our objective is to reduce the energy consumption of UAV's flight and the communication energy of buoys and sensors via joint trajectory planning and resource allocation while ensuring transmission robustness. Due to the nonconvex objective function and coupled variables in constraints, we use an alternating optimization method to divide the original problem into two subproblems and solve them iteratively. The successive convex approximation technique is used to tackle the nonconvex constraints. Furthermore, the wave-induced mobility of buoys results in infinite number of constraints. To tackle this issue, we use an$\mathcal {S}$-procedure to transform these constraints into a series of deterministic linear matrix inequalities. Simulations reveal that the proposed scheme reduces energy consumption while achieving robust transmission. Specifically, the proposed scheme overcomes wave effects and achieves higher throughput than other nonrobust schemes. Meanwhile, our scheme is able to provide 27.3$\%$lower weighted energy consumption than the other robust transmission scheme.

Since the traffic administration at road intersections determines the capacity bottleneck of modern transportation systems, intelligent cooperative coordination for connected autonomous vehicles (CAVs) has shown to be an effective solution. In this paper, we try to formulate a Bi-Level CAVs intersection coordination framework, where coordinators from High and Low levels are tightly coupled. In the High-Level coordinator where vehicles from multiple roads are involved, we take various metrics including throughput, safety, fairness and comfort into consideration. Motivated by the time consuming space-time resource allocation framework, we try to give a low complexity solution by transforming the complicated original problem into a sequential linear programming one. Based on the “feasible tunnels” (FT) generated from the high-Level coordinator, we then propose a rapid gradient-based trajectory optimization strategy in the low-level planner, to effectively avoid collisions beyond high-level considerations, such as the unexpected pedestrian or bicycles. Simulation results and laboratory experiments show that our proposed method outperforms existing strategies. Moreover, the most impressive advantage is that the proposed strategy can plan vehicle trajectory in milliseconds, which is promising in real-world deployments. A detailed description include the coordination framework and experiment demo could be found at the supplement materials, or online at https://youtu.be/MuhjhKfNIOg.

In this paper, a stochastic geometry based analytical framework is proposed for secure simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) transmissions, where legitimate users (LUs) and eavesdroppers are randomly distributed. Both the time-switching protocol (TS) and energy splitting (ES) protocol are considered for the STAR-RIS. To characterize system performance, the channel statistics are first provided, and the Gamma approximation is adopted for general cascaded κ-μ fading. Afterward, the closed-form expressions for both the secrecy outage probability (SOP) and average secrecy capacity (ASC) are derived. To obtain further insights, the asymptotic performance for the secrecy diversity order and the secrecy slope are deduced. The theoretical results show that 1) the secrecy diversity orders of the strong LU and the weak LU depend on the path loss exponent and the distribution of the received signal-to-noise ratio, respectively; 2) the secrecy slope of the ES protocol achieves the value of one, higher than the slope of the TS protocol which is the mode operation parameter of TS. The numerical results demonstrate that: 1) there is an optimal STAR-RIS mode operation parameter to maximize the secrecy performance; 2) the STAR-RIS-NOMA significantly outperforms the STAR-RIS-orthogonal multiple access.

An analytical framework for physical layer security in simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) transmissions is proposed, where legitimate users and eavesdroppers are randomly deployed. To characterize system performance, the channel statistics are first provided, and the Gamma approximation is adopted for general cascaded$\kappa-\mu$fading. Afterwards, the energy splitting (ES) protocol is considered and closed-form expressions of average secrecy capacity are derived. To obtain further insights, the asymptotic secrecy slope is deduced. The theoretical results show that the secrecy slope of the ES protocol is one. The numerical results demonstrate that: 1) there is an optimal resource allocation ratio of STAR-RIS to maximize the system performance; 2) the STAR-RIS-aided NOMA significantly outperforms the STAR-RIS-aided orthogonal multiple access.

In the orthogonal frequency division multiplexing with index modulation (OFDM-IM) framework, we propose an enhanced non-orthogonal multiple access (NOMA) scheme called NOMA with informative envelope (NOMA-IE) to explore the flexibility of signal envelope. In this scheme, data bits are conveyed by the quantified signal envelope in addition to classic signal constellations. Subcarrier activation patterns of different users are jointly decided by the envelope former at the transmitter. At the receiver, successive interference cancellation (SIC) is employed, and we introduce the envelope detection coefficient to eliminate the detection error floor. Considering binary phase shift keying, we derive the asymptotic bit error rate (BER). Analytical results reveal that the imperfect SIC is the main factor degrading the error performance. Numerical results demonstrate the superiority of the NOMA-IE over the OFDM and OFDM-NOMA.

Ultra-dense network(UDN) improves the regional throughput, however, it has caused the problems of frequent handover and handover failure. Mobility prediction and signal strength prediction is a focus in recent research to solve these problems. In this paper, we propose a joint adaptive mobility prediction and signal strength prediction based cell selection algorithm for handover in UDN. Firstly, we predict the user's path through adaptive order Lagrange interpolation and the order is adjusted according to user's moving state. Then, we use the predicted path to estimate the time user stay in the neighbor cells, i.e., time of stay(ToS). Taking both the ToS and the prediction result of signal strength into account, the cell selection process is modeled as a multi-objective decision-making problem, and we use the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) framework to solve it. The research reveals the influence of ToS on frequent handover and the advantage of adaptive parameters adjustment on mobility prediction. Numerical results show that the proposed algorithm reduces the number of handovers by 16.8% and handover failures by 56.9% compared with the contrast algorithm.

High accuracy and seamless position information formulates the basis of many modern wireless applications, such as the Internet of Things (IoT) and intelligent transportation systems (ITSs). In this article, aiming at the ground user equipment (UE) those in the “blind spots,” where only limited navigation signals are provided, the temporary aerial-aided “anchors” such as the unmanned aerial vehicles (UAVs) are introduced as alternating solutions. We first give the general fundamental limits of the three-dimensional space–air–ground-integrated localization networks (SAGILNs) using both time and angle measurements. Unlike most existing investigations, we treat aerial nodes as “agents” whose positions are not known beforehand. We then try to formulate an efficient scheduling strategy, where proper networkbehaviors, including the resource optimization and UAV deployment, are provided. We find that the proposed scheduling problems could be formulated as standard semidefinite programming (SDP) problems and solved by off-the-shelf solvers. Numerical results are provided to validate our analysis. The proposed methods and analyses provide meaningful insights for performance benchmarks for the implementation of SAGILN.

The simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is capable of providing full-space coverage of smart radio environments. This work investigates STAR-RIS aided downlink non-orthogonal multiple access (NOMA) multi-cell networks, where the energy of incident signals at STAR-RISs is split into two portions for transmitting and reflecting. We first propose a fitting method to model the distribution of composite small-scale fading power as the tractable Gamma distribution. Then, a unified analytical framework based on stochastic geometry is provided to capture the random locations of RIS-RISs, base stations (BSs), and user equipments (UEs). Based on this framework, we derive the coverage probability and ergodic rate of both the typical UE and the connected UE. In particular, we obtain closed-form expressions of the coverage probability in interference-limited scenarios. We also deduce theoretical expressions in conventional RIS aided networks for comparison. The analytical results show that optimal energy splitting coefficients of STAR-RISs exist to simultaneously maximize the system coverage and ergodic rate. The numerical results demonstrate that: 1) STAR-RISs are able to meet different demands of UEs located on different sides; 2) STAR-RISs with appropriate energy splitting coefficients outperform conventional RISs in the coverage and the rate performance.

Edge computing assisted autonomous driving technology has become a promising method to satisfy exacting computation requirements of achieving high or even full automation. However, the computation and spectrum resources of multi-access vehicular edge computing (VEC) system are also limited, which may not guarantee the best experience for all users, so we make a tradeoff between resource consumption and user experience. First, according to the characteristics of task scalability in driving assistance applications, we model the problem as maximizing system utility under the deadline constraint and the total resource constraint. Then, we formulate a collaborative computation offloading and resource allocation optimization scheme (JORA). Since the problem is NP-Hard, the JORA scheme eventually solves the problem by the mutual iteration of the two sub-algorithms, which includes offloading strategy and resource allocation. Simulation results prove that the proposed algorithm can effectively improve the system utility.

Ultra dense network (UDN) is one of the key technologies to improve the network capacity by densely de-ployed small cells. As for the asymmetry and variations of future traffic, dynamic time division duplex (D-TDD) has been proposed as a promising solution to dynamically adjust the uplink (UL)/downlink (DL) configuration. In this paper, we propose a general and tractable analytical framework for the theoretical performance under D-TDD two-tier heterogeneous networks. We firstly model user equipment (UE) and base station (BS) as homogenous Poisson point process (HPPP). Then, by leveraging stochastic geometry and geometry relationship, we propose an analysis method based on geometry approximation and derive analytical expressions for the UL and DL coverage probability. To increase the accuracy of analysis, we consider the coupling between UEs and BSs, so that more accurate interference can be obtained. Our results show that the derived coverage probabilities match the simulation results quite well and suitable for heterogeneous UDN scenarios. In addition, a comparison of the coverage probabilities between D-TDD system and static TDD (S-TDD) system is also provided to show that compared with S-TDD system, D-TDD system sacrifices uplink coverage performance to obtain better downlink performance.

The increasing demand for the internet of vehicle (IoV) services has prompted the prosperity of cellular-based vehicle-to-everything (C-V2X). This paper investigates the resource allocation in an uplink SCMA-enabled C-V2X network. At the aim to maximize the sum rate of cellular links in condition of guaranteeing the reliability of V2X links, we propose a Two-Stage space code multiple access (SCMA) codebook allocation algorithm. The complicated resource matching problem is transformed into a 2-D matching problem by using V2X grouping algorithm at first. Then a Matching-Auction-based codebook allocation algorithm is adopted to address the issue of matching conflict. Finally, numerical simulation results indicate that the proposed scheme outperforms in terms of the sum data transmission rate of the cellular links and the reliability of V2X links.

Ultra-dense network (UDN) can effectively improve the network throughput by increasing the deployment density of base stations. However, due to the randomness of the large number of base station deployments, UDN will lead to huge computational complexity and signaling overhead. The existing clustering algorithms cannot obtain effective clustering results in extremely dense scenarios. In this paper, we propose a minimum separation clustering (MSC) algorithm, which selects the split base stations (SBSs) to connect the multiple dense cluster base stations (CBSs). SBSs can reduce the interference between CBS clusters by using different radio resources from CBSs, because it has higher priority in the resource allocation procedure. Furthermore, the traditional clustering evaluation indexes such as the sum of square error are not applicable to UDN where the base stations are deployed randomly, and hence we design the separation degree function, which evaluates the clustering effect from the compactness within a cluster and the dispersion between different clusters. Simulation results show that the proposed algorithm can not only reduce the proportion of SBSs so as to improve the spectral efficiency, but also reduce the inter-cluster interference and network scale.

Due to the explosive growth of mobile data traffic, the Ultra-Dense Networks (UDN) becomes one of the hot research technologies in the 5thGeneration mobile communication system (5G). With the multi-layer network structure, UDN brings spectrum multiplexing gain and system capacity improvement by densely deployed small cells in hot spot area. In this paper, in order to improve system Energy Efficiency (EE) and Spectrum Efficiency (SE), we propose a joint optimization algorithm considering both EE and SE for small cells in UDN with the constraints of interference threshold and transmission data rate requirement. We first formulate a compromised objective function considering both EE and SE, and then the optimization problem is transformed from the fractional form to subtractive form to simplify the solution procedure, and finally the results of resource allocation and power allocation are obtained by the iteration of Lagrangian dual decomposition method. Simulation results show that both EE and SE performance of the proposed algorithm is much better than the algorithms used in conventional communication systems, and compared with the algorithm to maximize SE in UDN, the EE can be significantly improved with very slightly reduced SE performance.

In order to satisfy the requirement of supporting massive connectivity accompanied by the cost of transmission latency and signaling overhead, uplink (UL) grant-free Sparse Code Multiple Access (SCMA) design has been proposed. Contention transmission unit (CTU) is the basic resource for contention transmission for UL SCMA. Most CTU allocation schemes allocate CTU just by the UE_ID, which may bring about high packet loss rate due to the collision of CTUs when the activeness of UEs is not similar. In this paper, we first study the equation of the average packet loss rate, where the optimization of average packet loss rate is proved to be a NP-hard problem as a function of the allocation scheme. In this paper, we proposed a novel scheme based on activeness via dynamic programming transforming the NP-hard problem to a solvable and low complexity problem, which can obtain the Pareto optimal solution ultimately. Simulation results demonstrate that the proposed CTU allocation scheme can greatly reduce the packet loss rate with extremely low complexity.

This paper proposes a Weighted fractional Fourier transform (WFRFT) based cooperation scheme to improve PHY layer security against eavesdropping in wireless communications. Rather than dissipating valuable transmission power to jam the eavesdropper, by leveraging the features of WFRFT, the information bearing signal can create “Artificial Noise” effect at the eavesdropper while imposing no effect on the legitimate receiver. Specifically, the proposed WFRFT based cooperation is performed in a two-phase manner, whereby the source first broadcasts its message to the intermediate nodes which then perform WFRFT operation to relay the message to the destination, with the objective of boosting the secrecy rate of the source-destination pair. Simulation results are provided, which demonstrate that the WFRFT-based user cooperation scheme can acehieve a significant performance gain, in terms of secrecy ergodic capacity, compared with conventional security-oriented user cooperation schemes.

In spectrum sharing networks with relay cooperation, primary users can benefit from the assistance of secondary users while secondary users accessing the primary bandwidth to transmit their signals. Reasonable relay selection strategy can improve the performances of both primary and secondary users in terms of higher transmission data rate and lower outage probability, and at the same time, frequent relay switching can be avoided. In this paper, we propose a relay selection strategy considering both relay mobility and the required transmission data rate of primary user. The metrics of relay selection combine the relay activation duration and the transmission data rate of the secondary users through the mobility prediction of relay nodes. Simulation results show that the proposed strategy can select the best relay with lower primary outage probability and longer relay activation duration compared with existing schemes, and the transmission data rate of secondary user can also be improved so that the total number of transmit information bits can be increased.

In this paper, weighted fractional Fourier transform (WFRFT) is employed to safeguard the physical layer (PHY) security of wireless communications. By leveraging the features of WFRFT, we propose a PHY security modulation scheme, which significantly degrades the equivalent signal-to-noise ratio (SNR) of the unauthorized receiver while imposing no impact on the legitimate receiver. With the proposed scheme, a robust nonzero secrecy capacity can be guaranteed. Moreover, the proposed scheme can conceal the actual modulation paradigms to prevent malicious signal detection, due to the variation in signal characteristics. A higher order statistics (HOS) based classifier is used to investigate the anti- recognition performance. Meanwhile, the secrecy performance of the proposed scheme is evaluated in terms of both secrecy capacity and average bit error rate (BER) by numerical simulations. Finally, as a proof-of-concept, an all-digital field programmable gate array (FPGA) based prototype system is developed to validate the practicability of the proposed scheme.

Owing to the rapid development of underwater applications, the research on underwater wireless sensor networks (UWSNs) is becoming more and more significant. Low bandwidth, high latency, limited energy and node float mobility are basic challenges for underwater sensor networks. Most of the theories for terrestrial sensor networks can not be applied to underwater sensor networks. In this paper, we focus on the localization and routing issues for dynamic UWSNs. Location based routing protocols can suit the dynamic situation of UWSNs well. However, most research assumes that the nodes know their locations, which may be not appropriate for some applications. This paper combines these two aspects together to design a localization based routing protocol for dynamic UWSNs. The simulation results show our method can effectively route data from the source nodes to the sink nodes in a dynamic environment.

In order to reduce interference to the primary system and further improve the spectrum efficiency, the Fractional Fourier Transform is introduced as a tool to solve the spectrum sharing problem and a new spectrum sharing protocol is proposed in this paper where sinusoidal signals and chirp signals are utilized for primary users and cognitive users, respectively. In our spectrum sharing protocol, secondary users take the initiative to access the spectrum or act as a DF relay to assist the primary system adaptively according to the channel conditions of the direct transmission link. Moreover, the joint optimization of power allocation and user selection of distributed secondary users is studied to achieve the maximum achievable data rate for the secondary system while guaranteeing the target data rate of primary user. Simulation results show that compared with previous protocols, the outage probability of both primary and secondary systems can be improved, and with an increase in the number of secondary users, a higher achievable data rate can be obtained for the secondary system.

Exploiting physical layer (PHY) characteristics has great potential to complement and secure upper-layer authentication protocols. Unlike existing PHY authentication mechanisms requiring special hardware designs, in this paper, we propose a practical PHY- aided authentication approach based on weighted fractional Fourier transform (WFRFT). Instead of exploiting the channel or hardware characteristics that are out of control, the proposed scheme can provide two-fold protection on upper-layer protocols by leveraging the intrinsic PHY features of the transmitted signal. Firstly, WFRFT can hide and forge the modulation paradigm to mislead attackers in signal demodulation. Secondly, WFRFT signal can be adjusted among different patterns automatically and dynamically to provide more security and freedom in PHY authentication, similar to frequency-hopping systems. Numerical simulations and analyses demonstrate that the proposed scheme can achieve more secure authentication with tolerate computational overhead.

Relay technique is introduced in the Long Term Evolution Advanced (LTE-Advanced) system to extend the network coverage, improve the performance of cell-edge user equipments (UEs) and increase the fairness among different UEs. The combination of multiple-input-multiple-output (MIMO) and relay can further increase frequency efficiency and improve system performance. In this paper, based on the architecture of MIMO relay-enhanced TD-LTE-Advanced system, a fairness -aware resource allocation algorithm is proposed, and the resource allocation is divided into 3 phases: a frequency resource partition scheme is firstly proposed to realize the tradeoff between fairness among UEs served by various relay nodes (RNs) and system throughput; secondly, a backhaul resource allocation algorithm is presented to match the eNB to relay transmission with the relay to UE transmission with reduced feedback overhead; finally, a resource allocation algorithm from eNB and relay to UEs is given to maximize the proportional fairness so that user fairness can be guaranteed. Simulation results show that both system throughput and user fairness can be improved with limited feedback overhead, using the proposed algorithms.

This paper addresses the multi-antenna relay beamforming problem in single-carrier frequency division multiple access (SC- FDMA) systems with imperfect channel state information (CSI) at the relay. Under the deterministic model of CSI errors, we formulate the optimizing problem as a minimax problem, which is to minimize the maximum mean-squared-errors (MSE) among all channels in the uncertainty sets. Despite of the non- convexity of the optimizing problem, we prove that the problem can be solved in closed form. More specifically, the saddle-point property for this minimax problem is established and the non- convex complex- vector optimizing problem is transformed into a convex real-value power allocation problem and solved in closed form. The simulation results verify the excellent performance and robustness of our proposed scheme.

In LTE-A downlink, beamforming is adopted to improve spectral efficiency and system capacity. Antenna selection in beamforming selects the proper receive signal subspace on different resource blocks (RBs), which can further improve system performance. In this paper, we first define the concept of effective data rate. Based on such concept, we propose a low complexity antenna selection algorithm for beamforming technology. Different from existing algorithms, the proposed algorithm first determines the data layer number of each user by considering both channel quality and user requirements, and based on the data layer number, it selects a corresponding number of receive antennas to form the receive signal subspace. As a result, dynamic switching between single-layer and dual-layer beamforming can be realized so that user requirements can be better satisfied. Then, the proposed algorithm calculates the spatial correlation to assign proper antennas on different RBs to reduce inter-layer interference. Simulation results show that the effective data rate of the proposed algorithm is higher than other algorithms when user number is bigger than 20 so that the requirements of more users can be satisfied, and user fairness can also be improved.

In this paper, Rate-Level-Based Scheduling (RLBS) Algorithm is proposed to support the heterogeneous traffic in downlink of Long Time Evolution (LTE) system. The proposed scheduling algorithm aims to minimize the packet loss ratio of real-time traffic while guaranteeing Quality of Service (QoS) requirements. We compares the performance of the proposed scheduling algorithm with Modified Largest Weighted Delay First (M-LWDF) algorithm, Exponential PF (EXP/PF) algorithm and Z-Based QoS Scheduler (ZBQoS) algorithm. Simulation shows that compared with other algorithms, the proposed scheduling algorithm can achieve a good tradeoff between satisfaction of QoS requirement and fairness, meanwhile, it can can satisfy the requirement of Guaranteed Bit Rate (GBR) traffic preferably and improve the Packet Loss Ratio (PLR) performance significantly.

Signal to leakage and noise ratio (SLNR) based precoding algorithm is widely researched in CoMP-JP system. Nevertheless, the equivalent channel gain for each stream can be severely unbalanced in multi-stream transmission, and the overall performance is limited by the worst data stream. An improved SLNR based precoding algorithm is presented, which generates new precoding matrix with the method of weighting and linear transformation based on original SLNR vectors to eliminate the disparity of performance among streams, and optimize overall performance in multi-stream system. The simulation results demonstrate that our proposed algorithm can achieve considerable gains in error performance over the original SLNR and eliminate co-channel interference (CCI) among UEs at the same time for multi-stream transmission.

In TD-LTE-A systems, feedback information of uplink channel is of importance for eNodeB to perform downlink scheduling, beamforming, and adaptive Modulation and Coding Scheme (MCS). Channel quality indicator (CQI) is the most important parameter in all feedback information, and therefore, how to improve the accuracy of CQI feedback is a key issue for system configuration. In this paper, we propose a frequency domain CQI feedback algorithm, using channel capacity invariability criterion and channel reciprocity. Simulations show that periodic feedback with frequency domain CQI feedback algorithm can reduce system first retransmission ratio by about 4% and improve system throughput by about 7%, compared with normal periodic feedback Mode 1-1. In addition, compared with aperiodic feedback Mode 3-1, the proposed CQI feedback algorithm costs less signaling overhead, while keeping similar performance in terms of system first retransmission ratio.

In TD-LTE-A downlink, multi-user beamforming is used to decrease co-channel interference of different users and increase system performance, and Signal-to-Leakage-and-Noise Ratio (SLNR) beamforming algorithm has been proved to have better performance in terms of sum capacity and average BER performance compared with other beamforming algorithms with moderate complexity. In order to further improve the performance, the power allocation algorithm is combined with the framework of SLNR beamforming. Based on the combined algorithm, we can maximize sum capacity and guarantee users' requirements in multiuser downlink scenario with multiple-input-multiple-output (MIMO). The problem is transformed into convex optimization and then solved by geometric programming. Simulation results show that sum capacity of the proposed algorithm is slightly inferior to water-filling algorithm, however, the proposed algorithm can satisfy users' requirement while water-filling algorithm cannot. Then, a sub-optimal algorithm is also proposed to reduce implementation complexity at the cost of 10% sum capacity loss.

This paper compares the achievable sum rates of multiple-input multiple-output (MIMO) single carrier frequency division multiple access (SC-FDMA) and orthogonal frequency division multiple access (OFDMA) systems with linear receivers in spatially uncorrelated frequency selective Rayleigh fading channels. Zero forcing (ZF) and linear minimum mean-squared error (MMSE) receivers are considered. We derive closed form expressions for lower bounds on the achievable sum rates of SC- FDMA so as to compare them with the achievable sum rates of OFDMA. In addition, the comparison in the asymptotic regimes of high and low signal-to-noise ratios (SNRs) is also presented. It is analytically demonstrated that, for ZF and MMSE receivers, the achievable sum rate of SC-FDMA is approximately equal to that of OFDMA when the number of transmitter and receiver antennas grows with a fixed ratio of less than one, in both high and low SNR regimes. The results apply to scenarios with arbitrary numbers of subcarriers and arbitrary-length channels.

This paper investigates the achievable sum rates of multiple-input multiple-output (MIMO) single carrier frequency division multiple access (SC-FDMA) systems with different receivers in spatially uncorrelated frequency selective Rayleigh fading channels. Zero forcing (ZF), linear minimum mean-squared error (MMSE) and the proposed per subcarrier maximum likelihood (PSML) receivers are considered. Closed form expressions for the upper and lower bounds on the achievable sum rates of ZF, MMSE and PSML receivers are derived. Through these expressions, we characterize the behavior of the receivers in various scenarios of different channel lengths and subcarrier numbers. It is found that compared with the optimal receiver, the PSML receiver can obtain the optimal sum rate with significantly reduced computational complexity in flat fading channels. In addition, for ZF or MMSE receivers, either the upper or lower bound can be an accurate approximation of the achievable sum rate under certain conditions and can also provide a theoretical reference to practical systems.

In TD-LTE-A system, the objective of conventional non-codebook beamforming algorithms is to maximize sum capacity to accommodate more users. However, fairness among users is not considered by these algorithms, and the performance of users with poor channel quality will always be bad. To relax the fairness requirement in resource allocation, this paper first introduces two parameters of user satisfaction into TD-LTE-A system for Guaranteed Bit Rate (GBR) and Non-GBR traffics, respectively. Then a user-satisfaction-based beamforming algorithm is proposed. This algorithm employs user satisfaction parameter to adjust the weights for weighted Signal-to-Leakage-plus-Noise Ratio (SLNR) algorithm. Finally, the weights of different traffics are also considered in the proposed beamforming algorithm so that average user satisfaction across different types of traffics can be modified according to the requirement of telecommunication operators. Simulation results show that the proposed algorithm can improve user satisfaction and user fairness, and average user satisfaction of GBR and Non-GBR traffics can be adjusted by changing of GBR priority parameter.

In TD-LTE-A downlink, user selection is a key technique when the number of users exceeds the amount could be supported by eNodeB at one Transmission Time Interval (TTI). In order to improve the fairness of different users and consider the difference of user traffic in the process of user selection, a Signal to Leakage and Noise-Ratio (SLNR) beamforming based joint user selection and beamforming algorithm is proposed in this paper. Since in TD-LTE-A systems, the traffic can be classified into two types: Guaranteed Bit Rate (GBR) traffic and Non-Guaranteed Bit Rate (Non-GBR) traffic, user satisfaction for GBR and Non-GBR traffic are defined at first, and then, based on the difference of traffic, a user satisfaction based joint user selection and beamforming algorithm is proposed. Simulation results show that compared with conventionally used joint user selection and beamforming algorithm, user satisfaction of GBR traffic can be increased by 300% due to the fact that GBR traffic always has higher priority than Non-GBR traffic. Moreover, user fairness can also be improved in terms of the variance of user satisfaction.

ABSTRACT In amplify‐and‐forward (AF)‐based cooperative spectrum sensing system, the bit‐error‐rate (BER) performance and detection probability will decrease because of the existence of channel estimation error. In this paper, the influence of channel estimation error on system performance is firstly deduced, and then, linear minimum mean‐square error (LMMSE) channel estimation algorithm with filtering delay time‐domain windowing (LMMSE‐filtering‐DTW) technique and modified singular value decomposition‐based LMMSE algorithm are proposed to improve the channel estimation performance for code division multiple access system and orthogonal frequency division multiplexing system in AF cooperative scenario, respectively. Simulation results verify the effectiveness of the two proposed channel estimation algorithms in cooperative spectrum sensing, and whenEb/N0is bigger than 20 dB, given the required false alarm probability smaller than 15%, the difference of detection probability between the channel obtained using the proposed channel estimation algorithms and the ideal channel is less than 2.5%, respectively. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, we propose an opportunistic spectrum sharing protocol that exploits the situation when the primary system experiences weak channel conditions. Specifically, when the outage rate of the primary systeme falls below the target rate, the secondary system tries to help the primary system achieve its target rate by acting as a decode-and-forward relay for the primary system, and allocating a fraction of its subcarriers to forward the primary signal. As a reward, the secondary system gains spectrum access by using the remaining subcarriers to transmit its own signal. We study the joint optimization of the set of subcarriers used for cooperation and the secondary subcarrier power allocation such that the transmission rate of the secondary system is maximized, while guaranteeing the primary system to achieve its target rate. Simulation results demonstrate that both primary and secondary systems can benefit from the proposed secondary spectrum access scheme.

Abstract Cognitive ultra‐wideband (C‐UWB) systems have recently received much attention because the huge bandwidth of ultra‐wideband (UWB) systems can better exploit the advantages of cognitive radio (CR) systems. Dynamic spectrum access (DSA) is a key technique in CR systems to implement dynamic spectrum change and can be easily implemented by changing the transmitted pulse shape in a C‐UWB communication system. In this paper, we propose an orthogonal expansion based pulse shaping method to implement DSA and to compensate for antenna distortion, which uses the orthogonal Hermite functions as the orthogonal basis. In order to eliminate the direct current (DC) component existing in even orthogonal Hermite functions and to reduce the computational complexity, two modified methods and a simplification procedure are also proposed. Our results indicate that the proposed orthogonal expansion based pulse shaping methods have a much lower computational complexity than the semi‐definite programming (SDP) method, while achieving a high power efficiency. Furthermore, we demonstrate that the distortion caused by the antenna effects can also be compensated during the pulse shaping process and a better signal‐to‐noise ratio (SNR) can thus be achieved. Therefore, the proposed method is very suitable for practical application in C‐UWB communications, in which the spectrum environment changes rapidly. Copyright © 2009 John Wiley & Sons, Ltd.

In order to achieve efficient dynamic spectrum access (DSA) in Cognitive Ultra-Wideband (C-UWB) systems, an orthogonal wavelets based dynamic pulse shaping method is proposed to obtain pulses which can adapt to any given spectral requirements. Using Meyer wavelet set as the orthogonal basis, pulses with high power efficiency can be achieved. The compact support property of Meyer wavelets enables us to efficiently reduce the computational complexity in dynamic pulse shaping calculation. Moreover, we demonstrate that the proposed method is easy to implement and can achieve a good balance between power efficiency and system complexity.

In impulse radio (IR) type Ultra-Wideband (UWB) communications, orthogonal waveforms confirm to given spectral mask are desired to improve system capacity. Therefore, in this paper, an orthogonal wavelet based pulse shaping algorithm is proposed and compactly supported Meyer wavelet is used as an example to show how to obtain orthogonal pulses. Simulation results show that the proposed algorithm can obtain orthogonal pulses with high power efficiency and the pulse generator can be implemented simply as well.