In autonomous driving, environment perception is the fundamental task for intelligent vehicles which provides the necessary environment information for other applications. The main issues in existing environment perception can be categorized into two aspects. On the one hand, all sensors are prone to measurement errors and failures. On the other hand, in complex driving environments, vehicles may encounter a variety of blind spots caused by vehicle occlusions, overlaps, and harsh weather conditions, which will cause sensors to experience low-quality data or to miss crucial environmental information. To cope with these issues, a multivehicle and multisensor (MVMS) cooperative perception method is presented to construct the occupancy grid map (OGM) of vehicles in a global view for the environment perception of autonomous driving. Distinct from existing environment perception methods, our proposed MVMS-OGM not only provides continuous geographical information but also captures and fuses continuous information with soft occupancy probabilities, resulting in more comprehensive and raw environmental information. Simulations and real-world experiments demonstrate that the proposed approach not only expands the perception range in comparison with single-vehicle sensing but also better captures the uncertainty of sensor data by fusing the occupancy probabilities with soft information.

For autonomous driving of unmanned vehicles in intelligent transportation systems, multi-vehicle cooperative perception supported by vehicular networks can greatly improve the accuracy and reliability of the perception decisions. Currently, the perception decisions for a single vehicle are mostly provided by neural networks. Therefore, in order to fuse the perception decisions from multiple vehicles, the credibility of the neural network outputs needs to be studied. Among various factors, the environment is one of the most important affecting vehicles' perception decisions. In this paper, we propose a new evaluation criteria for the neural networks used in the perception module of unmanned vehicles. This criterion is termed as Environmental Sensitivity (ES), indicates the sensitivity of the network to environmental changes. We design an algorithm to quantitatively measure the ES value of different perception networks based on the extracted features. Experimental results show that our algorithm can well capture the sensitivity of the network in different environments and the ES values will be helpful to the subsequent decision fusion process.

The mobility status of vehicles play a crucial role in most tasks of Autonomous Vehicles (AVs) and Intelligent Transportation System (ITS). To operate securely, a precise, stable and robust mobility tracking system is essential. Compared with self-tracking that relies only on mobility observations from on-board sensors (e.g. Global Positioning System (GPS), Inertial Measurement Unit (IMU) and camera), cooperative tracking increases the precision and reliability of mobility data greatly by integrating observations from road side units and nearby vehicles through V2X communications. Nevertheless, cooperative tracking can be quite vulnerable if there are malicious collaborators sending bogus observations in the network. In this paper, we present a dynamic sequential detection algorithm, dynamic model based mean state detection (DMMSD), to exclude bogus mobility data. Simulations validate the effectiveness and robustness of the proposed algorithm as compared with existing approaches.

Unmanned aerial vehicle (UAV)-assisted communications are expected to become an important part of the next generation mobile communication systems, due to the high mobility of the UAVs. Non-orthogonal multiple access (NOMA) is regarded as a rosy technology in the fifth generation (5G) mobile communication systems, since it can effectively improve the spectral efficiency. In this paper, we combine the advantages of the UAV-assisted communications and NOMA, and propose a device-to-device (D2D)-enhanced UAV-NOMA network architecture, in which D2D is introduced to increase the file dispatching efficiency. Resource reuse based on spatial reuse is also allowed to further improve the spectral efficiency. Then, we propose a graph-based file dispatching (GFD) protocol to control the interference and minimize the UAV-assisted file dispatching mission time. Simulation results verify the advantages of our proposed D2D-enhanced UAV-NOMA network architecture and the efficiency of our designed GFD protocol.

Unmanned aerial vehicle (UAV)‐assisted communications have been regarded as a promising technology, which can be used in dynamic heterogeneous networks, since the UAVs can be applied as mobile base stations (MBSs). It is more efficient to set the UAVs as MBSs in different layers according to their functions. Due to the ability in communicating with other vehicles or facilities, vehicle‐to‐everything (V2X) makes the information required by the vehicles be efficiently transmitted and processed, so as to increase the safety of driving. However, because of the rapid change of topology and the huge demand of data transmission, it is hard to guarantee the efficient coverage of all the vehicles only by the support of terrestrial wireless communication networks. Considering this, this study combines UAV and V2X communications together, and proposes a multi‐layer aerial‐road vehicular (MLARV) architecture. The UAVs in the higher layer are in charge of overall monitoring, while the UAVs in the lower layer are responsible for hot‐spot area coverage. To solve the throughput maximisation problem, the authors further propose a density‐aware deployment (DAD) scheme with an iterative three‐dimensional matching resource allocation algorithm. Simulation results show that the proposed DAD scheme with the MLARV architecture outperforms the traditional UAV‐assisted V2X communications with single layer architecture.

The mobility status of self and surrounding vehicles provides important information to various tasks in autonomous driving (AD) and intelligent transportation system (ITS). Accordingly, a precise, stable, and robust mobility tracking framework is essential. Compared with self-tracking that relies only on mobility observations from onboard sensors [e.g., global positioning system (GPS), inertial measurement unit (IMU), and camera], cooperative tracking markedly increases the precision and reliability of the mobility information by integrating observations from roadside units (RSUs) and nearby vehicles through vehicle-to-everything (V2X) communications in the Internet of Vehicles (IoV). Nevertheless, cooperative tracking can be quite vulnerable if there are malicious users sending bogus observations in the cooperative network. In this article, we present a malicious user detection framework, which includes two sequential detection algorithms and a secure mobility data exchange and fusion model to detect and remove bogus mobility information and integrate proposed detection algorithms with previous data fusion algorithms, which secures the cooperative mobility tracking in AD, ITS. Simulations validate the effectiveness and robustness of the proposed framework under different types of attacks.

As a newly emerging communication assistant equipment, unmanned aerial vehicles (UAVs) can be exploited to dispatch data files quickly to specific areas and support rapid deployment of communication links in complex terrain, which is of great significance for specific communication demands in disaster and remote areas. Nonorthogonal multiple access (NOMA), as a rosy technology in the fifth generation (5G) and future mobile communication systems, has been widely studied because of its ability in improving spectral efficiency and reducing transmission latency to enhance the overall Quality of Service (QoS) and meet the strict communication requirements. Based on these, in this article, we propose a device-to-device (D2D)-enhanced UAV-NOMA network architecture, in which D2D is introduced to increase the file dispatching efficiency. In our proposed D2D-enhanced UAV-NOMA network, the ground users (GUEs) that have already received file blocks (FBs) are allowed to reuse the time-frequency resources assigned to NOMA links to share their FBs with other GUEs, which significantly improves the efficiency of file dispatching. But this also leads to a complicated interference environment. In order to effectively manage the interference and minimize the UAV-assisted file dispatching mission time, we propose a graph-based file dispatching (GFD) protocol, in which the complicated joint optimization problem is decomposed to be solved efficiently and graph theory-based algorithms are proposed for resource allocation. The simulation results verify the advantages of our proposed D2D-enhanced UAV-NOMA network architecture and the efficiency of our designed GFD protocol in minimizing the total UAV-assisted file dispatching mission time.

Vehicle-to-everything (V2X) communications are regarded as the key technology in future vehicular networks due to its ability in improving the traffic efficiency and safety, and reducing congestion. Recently, non-orthogonal multiple access (NOMA), as a promising solution in the fifth generation (5G) mobile communication systems, has drawn much attention because it can significantly improve the network throughput and lower the accessing and transmission latency to meet the requirements of many 5G-enabled applications. Noticing these, in this paper, we propose to introduce NOMA in device-to-device (D2D)-enhanced V2X networks, where D2D-enabled resource sharing based on spatial reuse for different V2X communication groups are permitted through centralized resource management. Such an enhanced NOMA-V2X architecture results in a more complicated and challenging interference scenario. In order to efficiently solve the interference management and resource allocation problem in the NOMA-V2X network, we construct a weighted 3-partite interference hypergraph to model the relationships among different communication groups. Then, based on the constructed hypergraph, we further propose an interference hypergraph-based 3-dimensional matching (IHG-3DM) resource allocation protocol with a greedy 3DM algorithm. Simulation results verify the efficiency of our proposed IHG-3DM resource allocation protocol for NOMA-V2X communications in improving the network throughput.

Vehicular communication network is a core application scenario in the fifth generation (5G) mobile communication system which requires ultrahigh data rate and ultralow latency. Most recently, nonorthogonal multiple access (NOMA) has been regarded as a promising technique for future 5G systems due to its capability in significantly improving the spectral efficiency and reducing the data transmission latency. In this paper, we propose to introduce NOMA in device-to-device-enhanced vehicle-to-everything (V2X) networks, where resource sharing based on spatial reuse for different V2X communications are permitted through centralized resource management. Considering the complicated interference scenario caused by NOMA and spatial reuse-based resource sharing in the investigated NOMA-integrated V2X (NOMA-V2X) networks, we construct an interference hypergraph (IHG) to model the interference relationships among different communication groups. In addition, based on the constructed IHG, we further propose an IHG-based resource allocation (IHG-RA) scheme with cluster coloring algorithm, which can lead to both effective and efficient resource block assignment with low computational complexity. Simulation results verify the efficiency of our proposed IHG-RA scheme for NOMA-V2X communications in improving the network sum rate.

Vehicular communication network is a core application scenario in the fifth generation (5G) mobile communication system which requires ultra high data rate and ultra low latency. Most recently, non-orthogonal multiple access (NOMA) has been regarded as a promising technique for future 5G systems due to its capability in significantly improving the spectral efficiency and reducing the data transmission latency. In this paper, we propose to introduce NOMA in D2D-enabled V2X networks, where resource sharing based on spatial reuse for different V2X communications are permitted through centralized resource management. Considering the complicated interference scenario caused by NOMA and spatial reuse-based resource sharing in the investigated NOMA-integrated V2X networks, we construct an interference hypergraph to model the interference relationships among different communication groups. In addition, based on the constructed hypergraph, we further propose an interference hypergraph-based resource allocation (IHG-RA) scheme with cluster coloring algorithm, which can lead to both effective and efficient QoS-guaranteed resource block (RB) assignment with low computational complexity. Simulation results verify the efficiency of our proposed IHG-RA scheme for NOMA-integrated V2X communications in improving the network sum rate.

In this paper, we propose an innovative spatial-modulation (SM) based full-duplex (FD) decode-and-forward (DF) relaying protocol where the energy-constrained dual-antenna relay is powered by the radio frequency (RF) energy from the single-antenna source using the time-switching (TS) architecture. In this system, either one or both of the relay antennas receive the energy signal from the source in the energy harvesting phase. In the information transmission phase, one of the two relay antennas is selected to be active to decode and forward the information transmitted from the source and the other relay antenna receives the information from the source at the same time. In this way, the throughput of the information transmission between the relay and the destination can be significantly improved by the additional information mapped to the active antenna index which consequently leads to the improvement of the overall system throughput. Since the current SM capacity solution is not in a closed-form, we propose two tight SM capacity upper bounds and present the solution of the optimal time split ratio for the maximum system throughput according to the proposed upper bound. Monte-carlo simulations are conducted to verify the analysis and reveal the throughput gain of the proposed SM-FD relaying protocol in comparison with conventional FD relaying protocol.

We investigate the problem of resource allocation in a downlink orthogonal frequency-division multiple access (OFDMA) broadband network with an eavesdropper under the condition that both legitimate users and the eavesdropper are with imperfect channel state information (CSI). We consider three kinds of imperfect CSI: (1) noise and channel estimation errors, (2) feedback delay and channel prediction, and (3) limited feedback channel capacity, where quantized CSI is studied using rate-distortion theory because it can be used to establish an informationtheoretic lower bound on the capacity of the feedback channel. The problem is formulated as joint power and subcarrier allocation to optimize the maximum-minimum (max-min) fairness criterion over the users’ secrecy rate. The problem considered is a mixed integer nonlinear programming problem. To reduce the complexity, we propose a two-step suboptimal algorithm that separately performs power and subcarrier allocation. For a given subcarrier assignment, optimal power allocation is achieved by developing an algorithm of polynomial computational complexity. Numerical results show that our proposed algorithm can approximate the optimal solution.

We develop a channel estimation algorithm for wideband millimeter wave (mmWave) systems using low-resolution phase shifters (PSs). Since the limited scattering feature of mmWave channels, the estimation problem is formulated as a compressive sensing (CS) problem. To avoid the mismatch between the continuous and discrete spatial frequencies, we propose an adaptive grid matching pursuit algorithm to reduce the signal power leakage. Moreover, a hybrid precoding design is developed using low-resolution PSs. Simulation results demonstrate the advantage of the proposed channel estimation with an improved accuracy over the orthogonal matching pursuit (OMP) method. Furthermore, it is shown that the proposed channel estimation method can approach a close spectral efficiency to that achieved by the perfect channel knowledge.

This paper proposes a resource allocation policy which enhances physical layer security in vehicular communication networks. Due to the high mobility in vehicular networks, the feedback channel state information (CSI) can easily get outdated, especially when it takes non-negligible time to obtain the resource-allocation solution. Under the assumption that only outdated CSI is available, we formulate the problem as joint power and subcarrier allocation in order to optimize the uses' secrecy rate based on maximum-minimum (max-min) fairness criterion. The formulated optimization problem is a mixed integer nonlinear programming problem. To reduce the complexity, we further propose a two-step suboptimal algorithm that performs power and subcarrier allocation separately. For a given subcarrier assignment, the optimal power allocation is solved by developing an algorithm of polynomial computational complexity. Numerical results show that the performance of our proposed algorithm can approximate to the optimal one.

In this study, the authors investigate the energy‐efficient resource allocation in a multiuser downlink multiple‐input multiple‐output (MIMO) orthogonal frequency‐division multiple access system with block diagonalisation. Unlike the existing works in which one subcarrier is exclusively used, they consider the multiple user MIMO case on each subcarrier. An optimisation problem involving user selection, receive‐signal subspace selection and power allocation is formulated to maximise the system energy efficiency (EE). As optimising the orientation of the receive‐signal subspace is difficult, they considered two simpler resource allocation schemes, subspace selection scheme and user selection scheme. The two optimisation problems for the subspace and user selection schemes can be rewritten as a unified problem involving set selection and power allocation. By relaxing the combinatorial variables, they obtain an optimal joint set selection and power allocation solution, which can be directly applied to the original problem in most cases. To further reduce the complexity of the algorithm, they also develop a preselection technique for the user and received‐signal subspace on each subcarrier. Through simulations, they discuss the impact of different parameters on the EE for the two schemes and show that the proposed suboptimal algorithm can achieve a close performance to the optimal algorithm.

In this study, the authors investigate the resource allocation (RA) problem for the downlink orthogonal frequency division multiplexing based non‐orthogonal multiple access (OFDM‐NOMA) system. The RA problem is decomposed into two subproblems of subcarrier allocation (SA) and power allocation (PA). For the SA, a user grouping based greedy algorithm is proposed under the assumption that power is uniformly distributed among all the selected users. For the PA, the authors propose the iterative water‐filling and specific user rate maximising criterion with minimum rate constraints (iterative WF + SURMC‐MRC) scheme to jointly consider the PA problem among the selected users on one subcarrier and the PA problem among subcarriers. The simulation results show that the spectral efficiency performance of the proposed iterative WF + SURMC‐MRC scheme outperforms those of the (non‐iterative) WF + SURMC‐MRC scheme and the uniform distribution (UD) + SURMC‐MRC scheme. Moreover, the iterative WF + SURMC‐MRC scheme has advantages in resisting against the user overloading compared with the (non‐iterative) WF + SURMC‐MRC scheme.

In this study, the authors investigate the power allocation (PA) problem and spectral efficiency (SE) analysis for the single antenna downlink non‐orthogonal multiple access (NOMA) system under the sum rate maximising criteria with minimum rate constraints (SRMC‐MRC). For the PA problem, they propose the duality scheme for SRMC‐MRC which is considered as the optimal solution for the PA problem on one orthogonal subband in the single antenna NOMA system. They propose the specific user rate maximising criteria with minimum rate constraints (SURMC‐MRC) scheme to decrease the computational complexity of SRMC‐MRC. The PA problem on one subband under SURMC‐MRC is proved to be equivalent to SRMC‐MRC. Numerical results show that both the SE and fairness performance for SURMC‐MRC can strictly approach to those of the duality scheme in the whole signal‐to‐noise ratio (SNR) region. They prove that NOMA under SRMC‐MRC can obtain SE performance advantage in the high SNR region but accompany with some disadvantages in the low SNR region over the orthogonal multiple access system. This conclusion is verified through numerical results under different parameter conditions.

This paper investigates the resource allocation (RA) problem for the downlink multiple input multiple output-based non-orthogonal multiple access (MIMO-NOMA) system, which is usually solved through a beamforming (BF) process and a user selection (US) process. In this paper, we propose the multiple-user channel state information (CSI)-based singular value decomposition (MU-CSI-SVD) BF scheme and the minimization of power (Min-Power) US scheme. Under perfect CSI scenarios, the proposed MU-CSI-SVD achieves near optimal sum rate performance with the high-complexity BF scheme while has the same level computational complexity as the low-complexity BF scheme. For imperfect CSI scenarios, the proposed MU-CSI-SVD also achieves better outage probability performance but requires the same level computational complexity as the existing low-complexity BF scheme. Moreover, MU-CSI-SVD is helpful to decrease the computational complexity for solving the Min-Power US problem. Compared with existing US schemes, the proposed Min-Power scheme can achieve larger sum rate or lower outage probability with limited computational complexity increment. Therefore, in this paper, we develop a complete RA scheme for 5G MIMO-NOMA systems, which has excellent performance while with low computational complexity for both perfect and imperfect CSI scenarios.

This article is focused on secure relay beamformer design with a correlated channel model in the relay-eavesdropper network. In this network, a single-antenna source-destination pair transmits secure information with the help of an amplify-and-forward (AF) relay equipped with multiple antennas, and the legitimate and eavesdropping channels are correlated. The relay cannot obtain the instantaneous channel state information (CSI) of the eavesdropper, and has only the knowledge of correlation information between the legitimate and eavesdropping channels. Depending on this information, we derive the conditional distribution of the eavesdropping channel. Two beamformers at the relay are studied for the approximate ergodic secrecy rate: (1) the generalized match-and-forward (GMF) beamformer to maximize the legitimate channel rate, and (2) the general-rank beamformer (GRBF). In addition, one lower-bound-maximizing (LBM) beamformer at the relay is discussed for maximizing the lower bound of the ergodic secrecy rate. We find that the GMF beamformer is the optimal rank-one beamformer, that the GRBF is the iteratively optimal beamformer, and that the performance of the LBM beamformer for the ergodic secrecy rate gets close to that of the GRBF for the approximate secrecy rate. It can also be observed that when the relay has lower power or the channel gain of the second hop is low, the performance of the GMF beamformer surpasses that of the GRBF. Numerical results are presented to illustrate the beamformers’ performance.

The performance of multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems can be significantly improved by using efficient resource allocation schemes. There are a lot of resource allocation schemes to maximize the system capacity. However, under a practical circumstance of employing a suboptimal MIMO detector, optimizing for maximum capacity may not be proper. In this paper, we investigate resource allocation schemes to minimize the bit error rate (BER) for various suboptimal detectors, including the zero forcing (ZF) detector, the successive interference cancellation (SIC) detector, the lattice reduction (LR) based ZF detector, and the LR based SIC detector. For the ZF and SIC detectors, we study the subcarrier allocation among users and power allocation over subcarriers and antennas. The optimal algorithm is investigated and a suboptimal scheme with low complexity is proposed for each detector. For the LR based ZF and SIC detectors, we propose suboptimal schemes with allocating power equally over antennas. Simulation results confirm that the proposed scheme improves the BER performance for each detector.

In this article, the authors focus on a correlated channel model for secure relay beamforming in the relayeavesdropper network. In this network, a single-antenna sourcedestination pair transmits secure information with the help of a amplify-and-forward (AF) relay equipped with multiple antennas. The relay cannot obtain the instantaneous channel state information (CSI) of the eavesdropper. The relay only have the knowledge of correlation information between the legitimate and eavesdropping channels. Depending on this information, we derived the conditional distribution of the eavesdropping channel. Three beamformers at the relay are studied: the zero-forcing (ZF) beamformer, the generalized match-forward (GMF) beamformer and the general-rank beamformer (GRBF). The authors found that the ZF beamformer is invalid in this system, and the GMF beamformer is the optimal rank-1 beamformer, and the GRBF is the iteratively optimal beamformer. Numerical results are presented to illustrate three beamformers' performance, and the impacts of different parameters, especially the channel correlation, on the system performance are analyzed.

In this paper, we investigate the resource allocation problem for the downlink non-orthogonal multiple access (NOMA) system with imperfect channel state information (CSI). We first derive closed-form expressions for the outage probabilities with and without the estimated instantaneous channel fading coefficient for each user. Upper bounds on both of the probability expressions above are proposed. Based on the outage probability bounds, we propose the power allocation scheme which is combined with a user selection step to minimize the maximum of the outage probability bounds of all the users. Simulation results show that the maximum outage probability can be significantly decreased by exploiting the priori knowledge of the estimated instantaneous channel fading coefficient for each user.

In this paper, we investigate energy-efficient resource management for downlink OFDMA systems with feedback channel capacity constraints. Compared with previous works, quantized channel state information (CSI) is studied by using rate-distortion theory since it can establish an information-theoretic lower bound on the capacity of the feedback channel. Based on the quantized CSI, an effective resource allocation algorithm is proposed to maximize the system energy efficiency employing the generalized fractional programming theory and the Lagrange dual decomposition method. Numerical results show that our proposed algorithm can nearly achieve the optimal solution and imply that the energy efficiency with a limited feedback rate could be close to that with perfect CSI.

Radio resource allocation for multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems is an important issue to improve overall system performance. Although the achievable rate has been adopted for a performance indicator in most resource allocation schemes, it may not be practical if a nonideal receiver including a suboptimal detector is used instead of optimal one. Under this practical circumstance, we study the subcarrier and power allocation to minimize the average bit error rate (BER) subject to a total power constraint. Different allocation algorithms are proposed for various MIMO detectors such as the maximum likelihood (ML) detector, linear detectors and the successive interference cancellation (SIC) detector. We also propose suboptimal algorithms to reduce the complexity. Based on the simulation results, we can confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity.

Most previous researches on the rate analysis of the power allocation (PA) schemes in two-way decode-and- forward (DF) relay systems typically focus on maximizing the instantaneous objective rates. However, the ergodic rate analysis of the optimized rates is not well considered. In this paper, we investigate the ergodic rates of the PA schemes in a two-way DF relay system, where the physical-layer network coding (PNC) protocol is adopted. Specifically, under a total power constraint, we consider three heuristic PA schemes, in which the optimization objectives are: 1) maximizing the sum rate; 2) maximizing the sum rate with an additional rate fairness constraint; and 3) maximizing the minor rate of the two directions of the system. The cumulative distribution functions (CDFs) of the equivalent system SNR are approximately obtained and the analytical expressions for the calculations of the ergodic rates are theoretically derived. Numerical results show that the derived analytical rates are converged to the simulated results in high SNR regions.

In this paper, we investigate the power allocation (PA) schemes in a two-way relay system, where the relay adopts physical layer network coding (PNC) based on decode-and-forward (DF) protocol. The objective is to determine the optimal power allocation (OPA) scheme at both the source nodes and at the relay that minimizes the end-to-end symbol error probability (SEP) performance under a total power constraint. The perfect channel state information (CSI) is assumed to be available at both the source nodes and at the relay. Since numerical methods (e.g., exhaustive search) are required to find the solution of the OPA scheme, which might be infeasible for practical systems, based on upper and lower bounds on the optimal solution, we propose a near optimal power allocation (NOPA) scheme. The asymptotic SEP expression of the proposed NOPA scheme is also derived. By both the analytical and simulated results, it is shown that the proposed NOPA scheme provides the asymptotic SNR gains of about 1.76dB and 2.22dB over two well-known schemes in high SNR. Furthermore, simulation results show that the performance of proposed NOPA scheme is quite close to that of the OPA scheme.

In this study, the authors examine the power allocation (PA) in a two‐way relay system, where the relay adopts physical layer network coding based on decode‐and‐forward protocol. In the PA, the optimisation objective is to minimise the end‐to‐end symbol error probability (SEP) under a total power constraint. Since the optimal power allocation (OPA) scheme requires numerical methods (for exhaustive search) to find the solution, which might be infeasible for practical systems, the authors propose a near optimal power allocation (NOPA) scheme that has a closed‐form solution by studying the properties of the OPA scheme. The asymptotic SEP expression of the proposed NOPA scheme is also derived. Simulation results show that the performance of proposed NOPA scheme is quite close to that of the OPA scheme. Furthermore, it is shown that the NOPA scheme can provide asymptotic SNR gains of 1.76 dB and 2.22 dB over two well‐known schemes.

In this paper, we study the impact of outdated channel state information (CSI) on the error rate performance in multiple-antenna two-way decode-and-forward (DF) relay systems, where physical-layer network coding (PNC) is adopted. We consider two variations of relay selection, namely, single best relay selection (S-RS) and multiple successfully-participated relay selection (MSP-RS). Under perfect and outdated CSI assumptions, closed-form expressions for the end-to-end system symbol error probability (SEP) are derived for the S-RS scheme, along with the asymptotic SEP expressions in high SNR regions for the MSP-RS scheme. By both analytical and simulation results, it is clearly shown that a full cooperative diversity gain can be achieved with perfect CSI. The results also manifest that the S-RS scheme can achieve only the transmit diversity gain with outdated CSI. On the other hand, the MSP-RS scheme can achieve a full cooperative diversity gain even if the CSI is outdated at the expense of high complexity.

In this paper, we consider the collaborative use of amplify-and-forward relays to form a beamforming system and provide physical layer security for a wireless network with multiple eavesdroppers. In this paper, we investigate the relay transmit power minimization under a secrecy rate constraint via secure beamforming. To minimize the relay transmit power, we design an approximate relay power minimization (RPM) beam-forming scheme, in which an iterative algorithm combining the semidefinite relaxation (SDR) technology and the gradient-based method is devised by studying the convexity of the RPM problem. By relaxing the constraints of the RPM problem, we propose a virtual eavesdropper based RPM (VE-RPM) beamforming scheme, which transforms the multivariate RPM problem into a problem of a single variable, and thus obtain an analytical solution. Our proposed beamforming designs can work well even if the number of eavesdroppers is larger than that of relays, while the existing schemes, e.g., the null-space beamforming approaches, can not work under this condition. Simulation results are presented to demonstrate the performance improvement with the RPM beamforming schemes. It is also showed that the virtual eavesdropper approaches significantly reduce the complexity with acceptable performance degradation.

With careful calculation of signal forwarding weights, relay nodes can be used to work collaboratively to enhance downlink transmission performance by forming a virtual multiple-input multiple-output beamforming system. Although collaborative relay beamforming schemes for single user have been widely investigated for cellular systems in previous literatures, there are few studies on the relay beamforming for multiusers. In this paper, we study the collaborative downlink signal transmission with multiple amplify-and-forward relay nodes for multiusers in cellular systems. We propose two new algorithms to determine the beamforming weights with the same objective of minimizing power consumption of the relay nodes. In the first algorithm, we aim to guarantee the received signal-to-noise ratio at multiusers for the relay beamforming with orthogonal channels. We prove that the solution obtained by a semidefinite relaxation technology is optimal. In the second algorithm, we propose an iterative algorithm that jointly selects the base station antennas and optimizes the relay beamforming weights to reach the target signal-to-interference-and-noise ratio at multiusers with nonorthogonal channels. Numerical results validate our theoretical analysis and demonstrate that the proposed optimal schemes can effectively reduce the relay power consumption compared with several other beamforming approaches.

In a multicell scenario, two competitive beamforming design schemes are proposed to maximise the worst signal‐to‐interference‐plus‐noise ratio (SINR) in each cell for downlink transmissions. The first design adopts interference control. The authors use different interference control weighting factors to suppress the inter‐cell interference effectively as each cell may experience different level of inter‐cell interference. The other design is based on power control, where the authors can adjust the power of each base station to improve the system performance. Both the two improved designs keep the distributive nature of the competitive design as well as improve the worst SINR of the system. The existence of Nash equilibrium of the proposed designs is proved and the system overhead is analysed for the comparison with other distributive algorithms. Simulation results show that both the proposed competitive designs have improved performances, and the competitive design with power control outperforms that with the interference control as the transmission power increases.

This study considers successive orthogonal beamforming (SOBF) for multicell downlink transmissions. A group of base stations (BSs) are in cooperation for effective downlink transmissions to cell‐edge users, which is usually referred to as cooperative multi‐point. As the number of cell‐edge users is small and varying, conventional beamforming schemes, for example, zero‐forcing beamforming (ZFBF), are not suitable for the multicell scenario. In the SOBF scheme considered here, the beamforming vectors are found in a successive manner when a new user comes in, so that the beamforming vectors of the existing users remain unchanged. With limited channel state information at the group of BSs, a new successive beam allocation (SBA) scheme is proposed for SOBF. In SBA, the candidate beams are broadcasted to all the users through downlink before the index of the best beam is sent back to the BS by each user. The sum rate performance of a system with two users is studied analytically. The numerical results are presented to show that the proposed SOBF with SBA outperforms ZFBF with conventional feedback strategy.

Recent studies suggest that relay communications can be a major application to extend the range of wireless communications by forwarding the signal from the sender to the receiver. Although fixed or robust distributed relay schemes for single receiver have been previously investigated, the distributed relay beamforming (DRBF) for multiple receivers is studied here. The authors propose an algorithm to design the DRBF weights for maximising the worst received signal‐to‐noise ratio subject to two different types of relay power constraints, which are the total relay power constraints and individual relay power constraints. The authors also prove that the proposed algorithm with relay power constraints results in a quadratic programming optimisation problem, which can be optimally solved by using semidefinite relaxation technology. The simulation results demonstrate an effective gain of the proposed optimal scheme over other intuition schemes.

ABSTRACT With the reformation of spectrum policy and the development of cognitive radio, secondary users will be allowed to access spectrums licensed to primary users. Spectrum auctions can facilitate this secondary spectrum access in a market‐driven way. To design an efficient auction framework, we first study the supply and demand pressures and the competitive equilibrium of the secondary spectrum market, considering the spectrum reusability. In well‐designed auctions, competition among participants should lead to the competitive equilibrium according to the traditional economic point of view. Then, a discriminatory price spectrum double auction framework is proposed for this market. In this framework, rational participants compete with each other by using bidding prices, and their profits are guaranteed to be non‐negative. A near‐optimal heuristic algorithm is also proposed to solve the auction clearing problem of the proposed framework efficiently. Experimental results verify the efficiency of the proposed auction clearing algorithm and demonstrate that competition among secondary users and primary users can lead to the competitive equilibrium during auction iterations using the proposed auction framework. Copyright © 2011 John Wiley & Sons, Ltd.

Recently collaborative relay systems have been studied to increase the spectral efficiency and extend the range of wireless communications. In this paper, we consider the collaborative relay beamforming (CRBF) for multiuser systems. In the proposed method, we select base station (BS) antennas for each user and optimize their CRBF weights under two different types of power constraints, which are the total relay power constraint and individual relay power constraints, by exploiting the notion of the maximization of the worst-case received signal-to-interference-and-noise ratio (SINR). The optimization problem of the CRBF weights can be efficiently solved using a semidefinite relaxation (SDR) technique.We derive an iterative CRBF scheme to jointly select the BS antennas and optimize the CRBF weights to maximize the worst SINR among all users. Simulation results validate our theoretical analysis and demonstrate the tradeoffs between the number of BS antennas and the number of relays in the CRBF system.

This paper studies the coordinated multicell downlink transmission to cope with the severe inter-cell interference (ICI) in future cellular systems. We propose an iterative scheme to jointly optimize the base station (BS) and relay beamforming weights to maximize the worst-case signal-to-interference-and-noise ratio (SINR) with perfect channel state information (CSI), under two different types of BS and relay power constraints, respectively, which are the total power constraints and individual power constraints. Using the semidefinite relaxation (SDR) technology, the optimization problems for BS and relay beamforming weights can be converted into semidefinite programming (SDP) problems, which can be effectively solved by interior-point methods. Simulation results demonstrate that the proposed iterative scheme can achieve near-optimal performance within a few iterations and provide a good tradeoff between performance and cost (i.e. the number of BS antennas and relays) in the multicell systems.

The performance of downlink transmissions can be improved by using relays that can form a distributed virtual multiple-input multiple-output (MIMO) beamforming system. In this paper, we study a collaborative downlink transmission scheme for a cellular system which consists of a base station (BS), multiple amplify-and-forward (AF) relay nodes, and multiple users. We propose a new algorithm to determine the signal forwarding weights for both transmit power and signal phase with an objective of minimizing power consumption of the relay nodes while guaranteeing the receive signal-to-noise ratio (SNR) at multiple users for the collaborative relay beamforming. We prove that the beamforming solution obtained by a semidefinite relaxation (SDR) technique is optimal with the proposed algorithm. Numerical results validate our theoretical analysis and demonstrate that the proposed optimal scheme can effectively reduce the power consumption of relay nodes compared with other beamforming approaches.

In the future cellular communication systems, multiple relay nodes can be used for distributed virtual multiple-input multiple-output (MIMO) beamforming to improve the performance of downlink transmissions. In this paper, we study a distributed relay scheme in cellular systems which consists of a base station (BS), multiple amplify-and-forward (AF) relay nodes, and multiple users. We propose an optimal distributed relay beamforming scheme that maximizes the worst-case received signal-to-noise ratio (SNR) under two different types of power constraints, which are the total relay transmit power constraint and individual relay transmit power constraints. We show that the distributed relay beamforming solution for multiusers can be obtained optimally by solving second-order cone programming (SOCP) problems. Numerical results validate our theoretical analysis and demonstrate an effective gain of the proposed scheme over other conventional schemes.

Application of network coding in wireless communications has enabled the development of physical layer network coding (PLNC). Applying the principle of PLNC to wireless cooperative networks for spectral efficiency improvement has recently received tremendous attention from the research community. The best relay selection is extensively investigated in the literature for PLNC cooperative networks with multiple relays. However, the authors study the problem of signal beamforming and relay selection for a cooperative bi-directional relay network using PLNC and consider signal beamforming and relay selection for (i) multiple relays each equipped with single antenna and (ii) multiple relays with multiple antennas on uncoded amplify-and-forward scheme for PLNC transmission. The authors derive the optimal design criteria and provide low-complexity sub-optimal solutions for relay selection and beamforming to minimise the symbol error probability.

In this paper, we derive user selection criteria based on the error probability for an actually employed detector for multiuser multiple-input multiple-output (MIMO) systems. We propose a low complexity sequential user selection scheme when a lattice reduction (LR) based MIMO detector is used. We also analyze the diversity gain for combinatorial user selection approaches with a given LR-based detector. From simulation results, we can confirm that the proposed sequential user selection approach can provide a comparable performance to the combinatorial ones with much lower complexity.

We investigate the maximum outage throughput for Orthogonal Frequency Division Multiple Access (OFDMA) systems in the presence of feedback channel capacity constraints. We attempt to establish an information-theoretic lower bound on the capacity of feedback channel and build the corresponding test channel that achieves this lower bound. Based on the derived test channel, we formulate the outage throughput maximization problem with the quantized CSI. Since the optimal solutions require an exponential time complexity, we propose a low complexity suboptimal approach that separately performs subcarrier and power allocation. Numerical results show that the proposed suboptimal approach can achieve a near optimal performance, and the outage throughput with a limited feedback of CSI can be close to that with perfect CSI by exploiting correlation properties of downlink CSI for quantization.

This paper attempts to address the effectiveness of physical-layer network coding (PNC) on the capacity improvement for multi-hop multicast in random wireless ad hoc networks (WAHNs). While it can be shown that there is a capacity gain by PNC, we can prove that the per session throughput capacity with PNC is θ (nR(n))-1), where n is the total number of nodes, R(n) is the communication range, and each multicast session consists of a constant number of sinks. The result implies that PNC cannot improve the capacity order of multicast in random WAHNs, which is different from the intuition that PNC may improve the capacity order as it allows simultaneous signal reception and combination.

In this paper, we propose a resource allocation scheme to maximize users' minimum rate with a guaranteed outage probability for Orthogonal Frequency Division Multiple Access (OFDMA) systems with imperfect CSI. To avoid the system degradation caused by the noisy and outdated CSI, we consider the minimum mean square error (MMSE) channel prediction scheme at the base station (BS). We derive the parameter, namely, the equivalent channel gain, which is determined by the requirement of the outage probability and the channel estimates at the BS. With this parameter, we can maximizes users' minimum rates under a transmit power constraint and given outage probabilities. To reduce the complexity, we propose a two-step suboptimal approach that separately performs subcarrier and power allocation. Simulation results show that the performance of the resource allocation scheme is robust against channel estimation errors and feedback delays in OFDMA systems.

Lattice reduction (LR) based detectors has been investigated for multiple input multiple output (MIMO) systems. For most LR aided detectors, it is assumed that the channel matrix is a square or tall matrix. However, practically there are many cases that the channel matrix is fat which is referred to as the underdetermined/rank-deficient MIMO system. In this paper, we employ the pre-voting cancellation approach and propose the LR-based detectors for underdetermined MIMO systems. It can be shown that the proposed detectors can exploit a full receive diversity. Furthermore, the pre-voting vector selection criteria for the proposed detectors are taken into account to improve performance further.

Abstract The performance of wireless networks is limited by multiple access interference (MAI) in the traditional communication approach where the interfered signals of the concurrent transmissions are treated as noise. In this paper, we treat the interfered signals from a new perspective on the basis of additive electromagnetic (EM) waves and propose a network coding based interference cancelation (NCIC) scheme. In the proposed scheme, adjacent nodes can transmit simultaneously with careful scheduling; therefore, network performance will not be limited by the MAI. Additionally we design a space segmentation method for general wireless ad hoc networks, which organizes network into clusters with regular shapes (e.g., square and hexagon) to reduce the number of relay nodes. The segmentation method works with the scheduling scheme and can help achieve better scalability and reduced complexity. We derive accurate analytic models for the probability of connectivity between two adjacent cluster heads which is important for successful information relay. We proved that with the proposed NCIC scheme, the transmission efficiency can be improved by at least 50% for general wireless networks as compared to the traditional interference avoidance schemes. Numeric results also show the space segmentation is feasible and effective. Finally we propose and discuss a method to implement the NCIC scheme in a practical orthogonal frequency division multiplexing (OFDM) communications networks. Copyright © 2009 John Wiley & Sons, Ltd.

Based on the result of Gupta and Kumar's seminal work, it has been proven that the scheme which allows multi-packet reception (MPR) can improve the throughput capacity by Theta(logn), while the improvement of network coding (NC) scheme is only upper bounded by a constant. On the development of NC, however, the most recently proposed schemes, physical- layer network coding (PNC) and analog network coding (ANC), advanced the innovation of increasing network capacity. They embrace the interference and allow simultaneous reception. Motivated by these two new approaches, in this paper, we study their throughput order. The results of our paper are as follows. The upper bound of the throughput order with the PNC/ANC scheme is Theta(radiclog n/n) log n which is the same as the MPR scheme. The throughput lower bound of the PNC/ANC scheme is Theta(1/radicn log n ), which is the same as the traditional NC schemes. Moreover, both the upper bound and the lower bound can be achieved. The throughput varies with the locations of the nodes between these two bounds.