The distributed network architecture allows cell-free massive MIMO(mMIMO) with multiple ways to combine uplink signals. The decision feedback scheme uses the detected signal of the distributed combiner to estimate the equivalent channel at the central processing unit (CPU), and iteratively updates the symbols using the estimated channel state information (CSI). The performance of this algorithm greatly depends on the accuracy of initial signal detection. In this paper, we first propose a pilot-based signal combining (PC) scheme at the CPU to improve the estimation accuracy of the symbols. We use pilot signals instead of detected signal to estimate the equivalent channel at the CPU. The estimated data symbols is then used as the training input in the decision feedback scheme, enabling iterative refinement of the equivalent CSI. Simulation results show that the proposed PC scheme can significantly reduce the system bit error rate compared to the decision feedback scheme with lower computational complexity and less decoding latency, albeit with slightly increase fronthaul signaling load. Furthermore, continuing the iterative process with the decision feedback scheme after initial PC further reduces the bit error rate, albeit with added decoding latency and computational complexity similar to the standard decision feedback scheme.

The non-independent and identically distributed (non-IID) data distribution in federated learning (FL) poses significant challenges to the training performance of FL models. To tackle this problem, we propose an novel framework called Federated Learning with Manifold Mixup of Prototype (FedMP) which takes advantage of both prototype learning and manifold mixup. Prototype learning ensures the effectiveness of the training results but also, in conjunction with manifold mixup, further enhances the generalization ability of the FL model. We also design a mixup matrix to regulate the training process and propose a strategy to redistribute the matrix weights. Additionally, to enhance the reliability of prototypes in the latent space, we introduce a conditional invertible generative network (cINN) to reconstruct the obtained prototypes. These reconstructed prototypes, in turn, participates in the training process to improve the model performance. We conduct experiments on two real-word datasets for the validation of the proposed FedMP framework. Experimental results show that FedMP outperforms other baselines on both training performance and communication costs.

In order to meet the requirement of high spectrum efficiency of MIMO systems, the number of antennas has been greatly increased to support simultaneous communication of multiple users, and higher order modulation is expected to be employed in the system at the same time, which make signal detection a difficult task. However, most traditional algorithms reply on the channel state information (CSI) accuracy get by channel estimation at receivers. DeepSIC, developed in the existing literature, is a promising framework that introduces data-driven deep learning methods into iterative soft interference cancellation (SIC) algorithms that can address challenges of unknown CSIs and improved performance. In this paper, a signal detection algorithm is designed for MIMO systems under high-order modulation when CSI is unknown, called ResLight-DeepSIC. ResLight-DeepSIC is based on DeepSIC, introducing the idea of residual network (ResNet), and achieves betterdetection performance and lower complexity with lightweight network. Link-level simulation shows that the improved algorithm has a gain of about 1 dB on the symbol error rate (SER), and reduces complexity by about 37% and 63% under 16 QAM and 64 QAM modulation, respectively. Therefore, the ResLight-DeepSIC proposed in this article has advantages in both performance and complexity with large multiple stream transmission and high order modulation.

Massive connectivity and limited energy are main challenges for the beyond 5G (B5G)-enabled massive Internet of Things (IoT) to maintain diversified Qualify of Service (QoS) of the huge number of IoT device users. Motivated by these challenges, this article studies the performance of cooperative simultaneous wireless information and power transfer (SWIPT) nonorthogonal multiple access (NOMA) for massive IoT systems. Under the practical assumption, residual hardware impairments (RHIs) and channel estimation errors (CEEs) are taken into account. The communication between the base station (BS) and two NOMA IoT device users is realized through a direct link and the assistance of multiple relays with finite energy storage capability that can harvest energy from the BS. Aiming at improving the system performance, an optimal relay is selected among K relays by using the partial relay selection (PRS) protocol to forward the received signal to the two NOMA IoT device users, namely, the far user (FU) and near user (NU). To evaluate the system performance, exact analytical expressions for the outage probability (OP) are derived in closed form. In order to get a better understanding of the overall system performance, we further undertake diversity order analyses by deriving asymptotic expressions for the OP in the high signal-to-noise ratio (SNR) regime. In addition, we also investigate the energy efficiency (EE) of the considered system, which is a crucial performance metric in massive IoT systems so that the impact of key system parameters on the performance can be quantified. Finally, the optimal power allocation scheme to maximize the sum rate of the considered system in the high SNR regime is also designed. Numerical results have shown that: 1) hardware impairment parameter has a deleterious effect on system performance while the channel estimation parameter is always beneficial to the OP; 2) the expected performance improvements obtained by the user of PRS protocol are enhanced by increasing the number of relays; and 3) the proposed power allocation scheme can optimize the sum-rate performance of the considered system.

Cell-free massive multiple-input multiple-output (MIMO) system is a promising architecture for next generation wireless systems by deploying a very large number of distributed access points (APs), which simultaneously serve a smaller number of user equipments (UEs) over the same time-frequency resources. It guarantees uniformly good service at high spectral efficiency with simple linear precoding techniques and max-min power control. In this article, we propose a new joint maximum-ratio and zero-forcing (JMRZF) precoding scheme, where part of APs are combined to perform centralized zero-forcing (ZF), while other APs apply simple maximum-ratio transmission (MRT). Our proposed precoder offers an adaptable trade-off between the spectral efficiency and front-haul signalling overhead. A corresponding AP subset selection scheme is also proposed which is based on large-scale fading coefficients. A closed-form expression for the achievable spectral efficiency of our proposed scheme is derived, which represents a generalized result including both fully distributed MRT and fully centralized ZF cases. Based on this closed-form expression, max-min power control is formulated and solved via the second order cone and first order methods. The former can obtain the global optimal solution, but its computational complexity is very high. On the other hand, the latter technique is sub-optimal, yet, it has very low computational complexity. Hence, it is suitable for large-scale cell-free massive MIMO systems with hundreds or thousands of APs and users. Numerical results show that our proposed JMRZF scheme can substantially outperform the local precoding schemes, even when a small part of APs are combined to deploy ZF and is implementable even when each AP has very few antennas. In addition, it is shown that our max-min power controls improves the spectral efficiency significantly, compared to the uniform power control scheme.

Vector perturbation (VP) precoding which utilizes a scaled Gaussian vector to minimize the effective transmit power is proved can obtain better diversity compared with linear precoding techniques. In this paper, we apply VP precoding in wireless MIMO wiretap channels to obtain practical physical layer security which aims at maximizing eavesdropper's error probability. The proposed scheme can also avoid performance loss introduced by artificial noise (AN) based secure schemes. New limit of perturbation vector is developed to guarantee practical secrecy and a new sphere decoder is given to meet such limitation. Furthermore, a modified VP scheme is proposed to reduce the complexity introduced by sphere decoder. Simulation results show that the proposed scheme could also achieve practical secrecy as AN based schemes, and better performance is obtained at the intended user with proposed scheme at the cost of computation complexity.

In this paper, we focus on a downlink cellular network, where multiple UAVs serve as aerial basestations to provide wireless connectivity to ground users through frequency division multi-access (FDMA) scheme. The UAVs are exclusively powered by a wireless charging station located on the ground following save-then-transmit protocol. In such a cellular network joint optimization for user association, resource allocation and basesation placement is investigated to maximize the downlink sum rate. The problem is formulated as a mixed integer optimization problem and is thus challenging to solve. We propose an efficient solution based on alternate optimization by iteratively solving one of the three subproblems at a time and an algorithm based on penalty method and successive convex optimization to binarize the association indicators. Numerical result shows that the downlink sum rate cannot be always enhanced by deploying more UAVs due to non-negligible tradeoff between energy/communication sources and co-channel interference.

This paper investigates the rate-energy (R-E) region of simultaneous wireless information and power transfer (SWIPT) systems for multi-user interference channels under the nonlinear energy harvesting (EH) model, where multiple transmitting users simultaneously broadcast signals to multiple receiving users. In order to achieve green communication design, we aim to characterize the tradeoff between the energy transfer and ergodic capacity and furthermore explore the influence of interference intensity on the considered system. Specifically, considering both time switching (TS) and power splitting (PS) receiver architectures, we formulated an optimization problem to derive the boundaries of R-E regions. As the optimization problem is non-convex and the employ of the nonlinear EH model makes it more difficult, we first apply efficient variable substitutions and Lagrangian duality method to transform it into equivalent convex problem, and then employ a low-complexity algorithm to obtain the optimal allocation scheme. Compared with the systems under traditional linear EH model, the R-E regions of the considered system is superior to reflect the features of the practical EH circuits. Due to the multi-user interference channels and the limitations of practical circuit environment, the system also shows different R-E tradeoff performance with different interference intensities.

The performance of coordinated multi‐point (CoMP) transmission system depends heavily on the quality of information exchange via backhaul links. However, the limited capacity of backhaul leads to quantisation error and delay of shared channel state information. In this study, the authors propose a novel hybrid CoMP transmission strategy to mitigate the impacts of the backhaul delay for data sharing and switch the transmission modes adaptively based on the current arrivals of the shared user data. Furthermore, they present analytical expressions for the average sum rate in an interference alignment network, in which the combining effects of quantisation from limited capacity and connection uncertainty introduced by finite delay are considered. With the analytical results, they evaluate the sum rate performance under limited backhaul for the conventional CoMP transmission modes and the proposed strategy. The simulation results demonstrate that the proposed strategy functions better on overcoming the impacts of capacity limited backhaul than the conventional ones.

We consider a multi-pair two-way massive multiple-input multiple-out (MIMO) relaying system over Rician fading channels, where multi-pair users exchange their information via the amplify-and-forward (AF) relaying equipped with large number of antenna arrays. Hardware impairments at the relay and imperfect channel state information (CSI) are taken into account. More specifically, we derive a new linear minimum mean- square error (MMSE) channel estimator for the proposed system. It is demonstrated that normalized mean square error (NMSE) is a constant when the pilot power grows to infinity. Moreover, the asymptotic spectral efficiency with maximum ratio processing is presented in closed-form and the power scaling laws are analyzed. Simulation results indicates that massive MIMO is capable of compensating the loss caused by hardware impairments, estimation error and Rician fading.

The new short-length single-direction frame structure for ultra-dense small cells (SCs) in the next- generation communication systems allows the dynamic time division duplex implemented by flexible transmit direction selection in each frame. Meanwhile, asymmetric uplink (UL) or downlink (DL) modes will introduce more complex and diverse interference in the adjacent SCs. Instead of treating the interference as noise as the conventional schemes do, we utilize some of the interference properties and propose a rate- splitting (RS) strategy to split each message into a common part and a private part. The two parts are decoded using successive interference cancellation (SIC). To maximize the time-averaged sum rate, we design the transmit direction and the covariances of the private and common messages jointly. The problem is NP-hard, as it subjects to mixed Boolean variables, transmit power and SIC decodability constraints. This paper achieves the suboptimal solutions numerically by difference of concave programming and convex-relaxed linear programming. The results show that the proposed strategy brings gain in time-averaged sum rate compared to the conventional schemes using symmetric UL-DL transmission without RS for different users' locations and network sizes. And the results indicate that the proposed strategy improves the performance of the users at the cell boundary and is superior for dense SC networks.

In this paper, an asynchronous multi-user deep reinforcement learning scheme is developed to control the handover (HO) processes across multiple user equipments (UEs), in the goal of lowering the HO rate while ensuring certain system throughput. In this scheme, we use a deep neural network (DNN) as an HO controller learned by each UE via reinforcement learning in a collaborative fashion. Moreover, we use supervised learning in initializing the DNN controller before the execution of reinforcement learning to exploit what we already know with traditional HO schemes and to mitigate the negative effects of random exploration at the initial stage. Furthermore, we show that the adopted global-parameter-based framework enables us to train faster with more UEs, which could nicely address the scalability issue to support large systems. Finally, simulation results demonstrate that the proposed framework can achieve better performance than the state-of-art on-line schemes, in terms of HO rates.

In this paper, we focus on a typical cooperative communication system with one pair of source and destination, where a unmanned aerial vehicle (UAV) serves as a mobile relay while flying from a start location to an end location. With simultaneous wireless information and power transfer (SWIPT), the UAV's transmission capability is powered exclusively by radio signal transmitted from the source via time-sharing mechanism. In such a cooperative communication system, we study the end-to-end cooperative throughput maximization problem for amplify-and-forward (AF) protocol. The problem is decomposed into three subproblems for optimizing decision profile, power profile and trajectory, respectively. The first one is solved via standard linear programming techniques, the second one is solved via the dual decomposition while last one is solved via successive convex optimization, by which a lower bound is iteratively maximized. Then the end-to-end cooperative throughput maximization problem is solved by alternately solving the three subproblems. The numerical results show that the proposed optimal solution outperforms both static and naive mobile strategies.

This paper investigates beamforming design of joint transceiver in full-duplex wireless powered communication networks for throughput maximization, where a multi-antenna hybrid access point (H-AP) broadcasts wireless energy to two distributed dual- antenna users and the users cooperatively transmit information signals via their individually harvested energy. Furthermore, the users can recycle self- energy from their own transmitted signals. H-AP acts as a transceiver to transmit energy and receive information simultaneously and amplified-and-forward relaying channel is applied from users to the H-AP. In this system, we aim to maximize the throughput by jointly optimizing the energy and information beamforming vector of H-AP. As the problem is non- convex, we first apply zero forcing method to cancel the self-interference at H-AP and then employ a series of efficient variable substitutions and a low-complexity algorithm to obtain the global optimum. Simulation results demonstrate that the proposed scheme can effectively improve the achievable throughput in the WPCN.

In this paper, we focus on a cellular network with a energy-constrained unmanned aerial vehicle (UAV), which serves as a relay for all the users to improve their uplink rates via cooperative communication. Uplink resource allocation in terms of power and time allocation among users is investigated to optimize the uplink sum-rate. By leveraging the local search strategy, the sum-rate optimization problem is decomposed into two subproblems, i.e., energy allocation and time allocation. We derived the optimal solution for both amplify-and-forward (AF) and decode- and-forward (DF) protocols with in-depth analysis. Numerical results show that path loss exponent has non- trivial impact on the sum-rate while higher energy replenishment rate of the UAV relay brings little performance gain. In addition, location of the UAV is also non-negligible and the cellular network can significantly benefit from proper deployment of the UAV relay.

In this paper, we consider a multiuser downlink communication system, where ground users are served by a UAV base station flying on an aerial plane. For the sake of computational complexity and energy economy, we propose a polygonal-line trajectory for the UAV base station and each ground user is served one by one while the UAV base station is travelling along one of the line segments on the trajectory. With the polygonal- line trajectory, joint optimization for power control and trajectory design for the UAV base station is investigated to maximize total capacity of all the ground users. Such a problem is decomposed into three subproblems for single-user downlink power profile, transmission energy allocation and waypoints location selection, respectively, and solved via alternate optimization, with which one of the three subproblems is solved given solutions to the other two. Simulation results show that the proposed scheme with optimized power profile and trajectory for the UAV base station outperforms two baselines. We also show that trajectory design significantly impact the system performance and is indispensable in UAV-assisted communications.

Small cell networks (SCNs) have emerged as promising technologies to meet the data traffic demands for the future wireless communications. However, the benefits of SCNs are limited to their hard handovers between base stations (BSs). In addition, the interference is another challenging issue. To solve this problem, this study employs a cooperative transmission mechanism focusing on correlated Rician/Gamma fading channels with zero‐forcing receivers. The analytical expressions for the achievable sum rate, symbol error rate and outage probability are derived, which are applicable to arbitrary Rician factors, correlation coefficients, the number of antennas, and remain tight across entire signal‐to‐noise ratios (SNRs). Asymptotic analyses at the high and low SNR regimes are carried out in order to further reveal the insights of the model parameters on the system performance. Monte‐Carlo simulation results validate the correctness of their derivations. Numerical results indicate that the theoretical expressions provide sufficiently accurate approximation to simulated results.

In this paper, we propose a two-layer framework to learn the optimal handover (HO) controllers in possibly large-scale wireless systems supporting mobile Internet-of-Things users or traditional cellular users, where the user mobility patterns could be heterogeneous. In particular, our proposed framework first partitions the user equipments (UEs) with different mobility patterns into clusters, where the mobility patterns are similar in the same cluster. Then, within each cluster, an asynchronous multiuser deep reinforcement learning (RL) scheme is developed to control the HO processes across the UEs in each cluster, in the goal of lowering the HO rate while ensuring certain system throughput. In this scheme, we use a deep neural network (DNN) as an HO controller learned by each UE via RL in a collaborative fashion. Moreover, we use supervised learning in initializing the DNN controller before the execution of RL to exploit what we already know with traditional HO schemes and to mitigate the negative effects of random exploration at the initial stage. Furthermore, we show that the adopted global-parameter-based asynchronous framework enables us to train faster with more UEs, which could nicely address the scalability issue to support large systems. Finally, simulation results demonstrate that the proposed framework can achieve better performance than the state-of-art online schemes, in terms of HO rates.

In this paper, we investigate the energy efficiency (EE) of large-scale distributed multiple-input multiple-output (D-MIMO) systems. Firstly, we derive an analytical closed-form expression of the lower bound on the ergodic capacity for D-MIMO systems, and the asymptotic performance for the large-scale antenna arrays systems over K fading channels is proposed. Utilizing these results, we elaborate on the EE optimization problem with transmitted power constraint. To tackle this multi-objective optimization problem, we propose an one-dimension iterative search algorithm with low complexity to obtain the optimal number of receive antennas, transmitted power and achievable sum rate with optimum EE. Simulation results verify the performance gain of the proposed scheme along with the increasing number of transmit antennas.

In this paper, we focus on fundamental point-to-point wireless transmission with a reverse feedback channel for automatic repeat request (ARQ) and propose wireless energy replenishment (WER) for the transmitter with ACK or NACK signal sent back by the receiver. In such a case, transmission power control affects not only transmission reliability at the receiver but also WER performance at the transmitter and transmission sustainability. Hence, dynamic power control for the transmitter is investigated to optimize the expected number of transmitted bits in multiple timeslots and such a problem is modeled as a finite-horizon Markov decision process (MDP), which is further solved via the backward induction algorithm. We evaluate the transmission performance with impact of channel condition, WER performance, number of timeslots as well as modulation scheme and show that transmission with WER outperforms that without WER, especially for moderate channel condition.

In this paper, we investigate the energy efficiency (EE) of massive multiple-input multiple-output (MIMO) systems with linear maximum ratio combining (MRC) and zero-forcing (ZF) receivers. To be practical, the baseband power consumption with algorithm computational complexity (ACC) is taken into account. Utilizing this model, we maximize the global optimal number of receiver antenna and sum rate with optimal EE by fixed the number of users for different receivers, respectively. In parallel, the low complexity iterative algorithm is proposed to reap the optimal values. Simulation results indicate that the EE improves with the number of users for the two receivers.

Green telecommunication is becoming an important part in designing the wireless communication systems. Small Cell Network (SCN) is considered as one of the most promising techniques in the future cellular networks. In order to reduce the high power consumption caused by dense deployment of small base stations (BSs), we first propose a new decentralized precoding algorithm which aims to maximize the energy efficiency of the SCN and the suboptimal solution can be obtained by two times of iterations. For further consideration, when the quantity of UEs is low in the network, it is a waste of energy to open a BS to serve only a few UEs or provide a low data rate to the UEs. So we introduce a BS closing strategy, which takes advantage of the property of SCN that different BSs cover more overlapping areas. Simulation results show that the proposed decentralized precoding algorithm outperforms the traditional precoding algorithms such as BD precoding, and the sleep strategy does not only take linear time complexity but also improve the energy efficiency of the SCN obviously.

In this paper, we investigate the energy efficient optimization for non-regenerative multiple-input- multiple-output (MIMO) Two-Way Relay (TWR) network. Contrary to existing energy efficiency (EE) optimal precoding designs, we maximize the weighted sum per- source energy efficiencies (WSEE) subject to the maximum transmit power constraints of sources and relay, such that different EE requirements from the sources can be investigated. The resulting optimization problem is a non-convex sum of ratios problem. To address this issue, we first reformulate the objective as a more tractable parametric subtraction form by introducing some auxiliary variables. Then we develop an efficient block coordinate decent method to solve the equivalent problem with respect to the individual optimization variable. It is shown that the proposed iterative algorithm is guaranteed to converge.

Three-dimensional multiple-input multiple-output (3D MIMO) is a promising technology for the future wireless communication systems, since antenna tilt angle can reduce the intercell interference. In this paper, we consider 3D MIMO downlink analysis for a multicell multiuser scenario. Zero-forcing (ZF) precoding technique is applied at BS with perfect channel state information of all users in its cell. We derive the exact analytical expressions for downlink sum rate and outage probability for the multicell multiuser 3D MIMO system. Furthermore, we study the asymptotic system performance in the high signal-to-noise ratio (SNR) and large number of antennas regimes. The relationship between tilt angle and sum rate is given. By analyzing the effects of the tilt angle and distance between users and BS on outage probability, the optimal tilt angle and distance are determined to guarantee the outage probability performance.

In this paper, we provide a Gamma distribution to approximate composite Gamma-Gamma (Generalized-K or KG) distribution by using the moment matching method. Based on the approximate distribution, we propose a novel closed-form approximate upper bound of D-MIMO system. The proposed upper bound, which enable us to go further manipulations, only involves some simple functions. Starting from the approximate upper bound, we perform a high-SNR analysis and investigate the asymptotic behavior of the capacity in the following two cases: i) the number of receive antennas grows into infinity for the fixed average and total transmit power, and ii) the number of antennas at both ends grow large at a fixed ratio. It is demonstrated that the proposed approximate and the asymptotic upper bounds match accurately with the exact analytical expression.

Utilizing spatial dimensions to align interference, interference alignment (IA) techniques can greatly improve spatial multiplexing benefits in interference-limited multiple antenna systems. In this paper, we focus on the closed-form design of IA in the multi-cell multi-user interfering networks with a finite number of antennas at each node. To obtain the same degrees of freedom (DoF), existing IA schemes employ different antenna usages on the base station (BS) side and mobile station (MS) side, leading to different DoF gain over orthogonal schemes. For practical concerns, it is unrealistic to install a lot of antennas on a MS, but realizable to deploy a large number of antennas on a massive MIMO BS. Therefore, by flexibly balancing the antenna usage between the BS side and MS side, we propose an IA based antenna resources assignment scheme, which can achieve a tradeoff between the usage of antennas and the DoF gain over orthogonal schemes.

At present, the joint utilization of the elevation factor in three-dimension (3D) channel model and antenna tilt angle in 3D base station is rarely investigated. In this paper, we consider the uplink of a multicell multiuser multiple-input multiple-output (MU-MIMO) system with a 3D base station exploiting variable antenna tilt angles. To illustrate clearly, we model a tall building with several floors. Users are distributed horizontally and vertically according some rules. Due to the storey height, elevations from one BS to different floors also differ, i.e. elevation variation occurs. For such a scenario, we derive the expression of sum rate considering the elevation factor, and discuss the effects of the tilt angle and user distribution on the sum rate. Sum rate at high signal-to-noise ratio (SNR) and large number of base station antennas is also studied. Finally, we analyze the relationship between the sum rate and the user number. This work can be seen as a first attempt to analyze the sum rate performance for high-rise buildings and used as a reference for infrastructure.

The leakage-based precoding (LBP) schemes have been widely studied in multiuser multiple-input multiple-output (MIMO) downlink systems. In order to get a comprehensive understanding of the LBP schemes, we analyze the relationship between the LBP and the minimum mean square error (MMSE) precoding schemes. We also propose two enhanced leakage-based precoding (ELP) schemes with different water-filling (WF) methods in this paper. From our analysis and simulation results, we reveal the fact that the LBP schemes and the MMSE precoding schemes can achieve almost identical sum rate performance under the same power allocation (PA) method.

In conventional relay-assisted HARQ schemes, source is always in anidle state during the retransmission phase.In this paper, we proposed a relay-assisted HARQ scheme which makes use of the basic idea of network coding. We simply adopt a remapping modulation method to combine new codewords and the ones to be retransmittedas the network coding. Source will transmit the superposition symbols during retransmission phase. Thus a virtual MIMO (Multiple In Multiple Out) system can be created and diversity and multiplexing can be gained. A corresponding MMSE (Minimum Mean Square Error) MIMO receiver and a soft demodulation method are proposed to recover two data streams. The proposed scheme can enhance the reliability and at the same time, throughput can be also improved due to the double-amount retransmission. Simulation results show that proposed scheme can greatly balance the reliability and the efficiency.

The complex multiplication between data streams and codebook when precoding at the transmitter always needs a lot of computing units in hardware implementation. In this paper, we first propose a binary-based codebook, in which all elements in the precoding matrix are expressed in power of 2. The proposed method can reduce practical engineering implementation complexity significantly, since the multiplication between the data symbol and the element of the codebook matrix can be regarded as a simple binary shift of the transmission data. This approach can be applied in various existing codebook design methods and we also consider on the multi-user case. But the operation is bound to bring in some accuracy loss because we hardly obtain the optimal codebook right with expression of power of 2. Then we propose a novel dual-codebook scheme which is easy to implement and can make up the performance penalty. The simulation results reveal that the proposed scheme outperforms 3GPP R10 LTE-A DFT (discrete Fourier transform) codebook and ease the burden of implementation cost.

We propose decentralized relay coordination algorithms and corresponding channel state information (CSI) signaling concepts for weighted sum rate maximization, via linear downlink transceiver optimization in multiuser multi-relay MIMO network. Two decentralized algorithms are developed with the local CSI requirements at the base station and the relay nodes. In the first proposed algorithm, the generalized channel inversion precoding is utilized at the base station to avoid the second hop channel sharing requirements among the relay nodes. Further, decentralized transceiver optimization of the relay nodes and users are developed to maximize the weighted sum rate. For the second proposed approach, we provide a novel structure of the precoding matrix of the base station. Then decentralized joint BS, relay and user transceiver design is developed to further improve the performance. Moreover, CSI signaling and decentralized processing in TDD system are analyzed. Simulation results show the effectiveness of the decentralized relay coordination compared to the existing algorithms.

Far field wireless recharging based on microwave power transfer (MPT) will release mobile terminals from interruption due to finite battery storage. Wireless energy transfer (WET), which integrating MPT with wireless communications, is a promising technology to provide perpetual energy supplies to wireless networks. In this paper, we propose a novel power allocation algorithm for Multiuser MIMO (MU MIMO) systems with simultaneous wireless information and power transfer (SIPT). For the purpose of universal relevance, a K +L+1 node network is investigated, in which K receivers decode information and the other L receivers harvest energy from the signals broadcasted by the base station. The proposed integrated scheme, based on the well-known Block Diagonalization (BD) preceding method, can completely suppress the multiuser interference and perform an outer-bound which is characterized by the boundary of the rate-energy (R-E) region as well.

Energy efficiency is an important issue for the future network since the stemming requirements of the ubiquitous access and the limited battery of the mobile devices. In this paper, we investigate energy efficient transmission for two-way relay network. Theoretically, we derive the optimal transmission data rate, which minimizes the total energy consumption per information bit. The energy efficiency region for two-way relay systems is also investigated to illustrate the effects of relay locations on the energy efficiency of the system, and the optimal relay location is also found to maximize the energy efficiency. Numerical results are presented to demonstrate the tradeoff between energy efficiency and the spectral efficiency.

This paper studies limited feedback unitary precoding for MIMO spatial multiplexing systems with QR-SIC receiver and equal power allocation. An optimal codebook design criterion, which can design the optimal codebooks for various fading and spatial correlated channels with arbitrary antenna configurations, is proposed. However, due to the fact that the closed-form of the probability density function (p.d.f.) of the optimal precoding matrix is hard to obtain, the optimal codebook design criterion is difficult to be applied to the practical systems. Thus, a suboptimal codebook design criterion is given, which can be implemented in practice and is also applicable to any scenario. Sequentially, an iterative codebook design algorithm that converges to an optimum codebook is given. Simulation results demonstrate that the proposed scheme achieves better performance than the 3GPP R10 LTE-A codebooks.

A new selective transmission mode in a three-node relay system is proposed when interference cancellation (IC) is not applicable on receivers. According to the effective Signal-to-Noise-Ratio (SNR) of each link, the source determines whether to transmit new information in the second slot while the relay node is forwarding the information received during the first slot. By the proposed monitoring mechanism, we can improve the ergodic capacity of the whole system compared to conventional relay protocols without too much feed-back overhead. Moreover, we prove that under careful power control of each node, full spatial diversity and capacity gain will be achieved even when there is no interference cancellation processing at the destination node. Thus we can reduce the burden of the receiver significantly. Two methods with perfect IC are compared as a supplement to explore the flexibility when there is no complexity limit at receivers. Both Decode-and-Forward (DF) and Amplify-and-Forward (AF) modes are analyzed respectively.

The performance of a system, which uses singular value decomposition (SVD) over a multiple-input multiple-output (MIMO) channel, depends on the accuracy of the channel state information (CSI) at the transmitter and the receiver. And although, SVD-based transmission can be done without any feedback by utilizing the channel reciprocity in time-division duplex (TDD) systems, the CSI at the transmitter is always outdated in time-varying channels, especially in the high-speed mobility cases. As in such cases, a typical system employing conventional SVD-based transmission will suffer great degradation in both capacity and BER performance, due to the interference among the sub-channels. So, a more efficient SVD-based transmission strategy against high-speed mobility is proposed in this paper. Compared with other transmission schemes, the novel transmission scheme can achieve significant performance improvement with lower computation complexity. And the simulation results do indicate that the proposed scheme is more robust against the outdated CSI. Besides, the analysis of both signal to interference-plus-noise ratio (SINR) and computation complexity are provided.

In two-hop relay systems, time division duplex (TDD) is usually adopted to support asymmetric traffic and offer channel reciprocity. When a relay is in the amplify-and-forward (AF) mode, the reciprocity is only provided within each hop. The equivalent channel between a base station (BS) and a mobile station (MS) cannot be reciprocal due to the operation at the relay. In some cases, the BS needs the whole downlink channel information to do pre-processing. However, the needed information could just be acquired through feedback in the conventional methods. In this paper, a gain matrix design method is proposed to maintain the whole link reciprocity and avoid large amount of feedback. Simulation results show that the mean square error (MSE) between whole downlink and uplink channel in proposed method is much smaller than that in the conventional gain matrix design schemes. Besides, the proposed method can maintain complete link reciprocity without performance loss.

In this paper, we investigate the energy efficient relay selection scheme for two-way relay network. Two optimal joint relay selection and power minimization schemes are studied. One approach is to minimize the total transmit power, including the relay power and the transceiver power, subject to the signal to noise ratio (SNR) requirements on the two transceiver. And the other focuses on relay power minimization. Closed-form solutions are obtained and only few parameters need to be broadcast to all relays. Based on the close form solution, a new relay selection criterion is proposed, which simply relies on the relay channel coefficients. Simulation results are presented to show the merits of the proposed scheme.

In this paper, joint optimization of subcarrier pairing, relay selection and power allocation is formulated through a capacity maximization problem in orthogonal frequency division multiplexing (OFDM) relay systems, with fairness considerations and individual power constraint on each node. Because achieving the optimal solution is computationally demanding, which is resulted from the excessive possibilities of joint resource allocation, we propose a sub-optimal allocation method. The proposed scheme decouples the allocation procedures into two steps, which reduces the complexity significantly by avoiding the search for all possible subcarrier pairs. Moreover, simulation results reveal the effectiveness of the proposed algorithm in both Amplify-and-Forward (AF) and Decode-and-Forward (DF) relay systems.

Relay aided wireless transmission realizes extended coverage and increases capacity for wireless communication networks, especially for the TDD/FDD LTE-A system. The relay node processes the received signal from source under certain rules and forwards the signal to destination. Amplify-and-Forward (AF) and Decode-and-Forward (DF) are two of the conventional relay schemes commonly used and cited. Estimate-and-Forward is a well-know but much less studied approach. The basic idea is to forward an estimate version of original signal without hard decision. A soft symbol estimating approach by solving linear equation set structured with received symbol probabilities. This algorithm makes a least squares fit of the estimated symbol probabilities to a single shot noisy symbol a posteri probability (APP) model. In the simulation, we take frame error rate (FER) to demonstrate the proposed scheme outperforms existing relay schemes.

In this paper, we evaluate the existing transmission schemes in multi-cell environment, such as single-cell transmission with Inter-cell interference (ICI) as well as Collaborative Multi-Point transmission/reception (CoMP) technique in LTE-A, and propose an more effective solution to deal with the inter-cell interference. The proposed transmission structure takes advantage of the cooperation between base stations (BS), and combines both closed-loop and open-loop techniques. With the concept of Effective Channel, the classic Space Frequency Block Coding (SFBC) decode scheme can be used directly in our receiver for single layer transmission. Thus, we prove that the scenario of multiple base stations can employ SFBC conveniently while the performance is guaranteed. Analysis and simulation results show that our method outperforms conventional single cell transmission. Moreover, the proposed transmission scheme can obtain elegant performance enhancement compared with local precoding and global precoding of CoMP in terms of capacity, and doubly reduce the feedback overhead at the same time.

This paper focuses on transmit precoding for multiuser MIMO downlink systems. In multiuser MIMO systems, multiuser interference (MUI) and noise are two well-known factors with respect to the system's performance. Block diagonalization (BD) method is proposed to completely eliminate MUI by placing the intended users in the nullspace of all the unintended users. But the BD method imposes a condition on the relation between the number of transmit and receive antennas. In addition, BD method causes the noise enhancement due to not considering noise's influence. Thus, at low and medium signal-to-noise ratio (SNR) regime, the performance of the BD scheme is poor. In this paper, we propose a novel precoding approach for users with multiple antennas to overcome the above mentioned drawbacks of the BD method for multiuser MIMO precoding systems. Simulation results confirm that the proposed algorithm achieves performance improvement over the conventional BD scheme with low complexity. The effect of channel estimate errors on system performance is also studied.

This paper proposes a hybrid codebook design algorithm and a distributed codeword selection criterion for multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying system with power allocation and precoding. The proposed codebook design algorithm exploits a modified LIoyd algorithm and converges to a locally optimal codebook. Closed form solution for power allocation problem is derived in order to maximize the channel capacity. Based on the codebook design algorithm, we further propose a codeword selection criterion which allows base station and relay to independently choose optimal codewords. The criterion effectively decreases the feedback delay in MIMO AF relaying system. Simulation results show that the proposed scheme achieves elegant performance in terms of ergodic capacity with very limited bits of feedback.

Relay selection enhances the performance of the cooperative networks by selecting the links with higher capacity. Meanwhile link adaptation improves the spectral efficiency of wireless data-centric networks through adapting the modulation and coding schemes (MCS) to the current link condition. In this paper, relay selection is combined with link adaptation for distributed beamforming in a two-hop regenerative cooperative system. A novel signaling mechanism and related optimal algorithms are proposed for joint relay selection and link adaptation. In the proposed scheme, there is no need to feedback the relay selection results to each relay. Instead, by broadcasting the link adaptation results from the destination, each relay will automatically understand whether it is selected or not. The lower and upper bounds of the throughput of the proposed scheme are derived. The analysis and simulation results indicate that the proposed scheme provides synergistic gains compared to the pure relay selection and link adaptation schemes.

This paper proposes a codebook-based precoding method for multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying system. The proposed codeword selection criterion is a distributed codeword selection criterion which allows base station and relay to choose optimal precoding matrix independently. Therefore the feedback delay is decreased. Based on the proposed criterion, we further develop a codebook design criterion. It is shown that the design criterion is equivalent to packing subspaces in the Grassmannian manifold using the Fubini-Study distance. Numerical simulations also show that the proposed scheme achieves elegant performance in terms of ergodic capacity.

In a mobile relay system, the idle users can be formed as a cluster to support nearby active users. In order to reduce the complexity of the processing in the relay nodes and destination nodes, a novel transmit preprocessing method is proposed for the cluster based multi-user relay system. Block diagonalization (BD) algorithm is adopted twice in the proposed method to remove inter-cluster and intra-cluster interference simultaneously, and the relay nodes are just in simple amplify-and-forward (AF) mode. Compared to the conventional signal processing methods, the proposed method can achieve better tradeoff between sum capacity performance and processing complexity in the relay nodes.

In orthogonal frequency division multiplexing (OFDM) systems, some subcarriers are often retained as null subcarriers for easier filter implementation. In this case, the performance of conventional Discrete Fourier Transform (DFT)-based channel estimation will be degraded dramatically due to dispersive distortion of actual channel impulse response (CIR). To solve this problem, in the present paper, we analyze the effect of null subcarriers on channel estimation and propose a novel channel estimation scheme. The proposed scheme, whose basic principle is the joint iteration of correlation operation and interference cancellation in time domain, can hold most energy of actual CIR and suppress noise effectively. Finally, simulation results show that the proposed method outperforms Least Square (LS) channel estimator, conventional DFT-based channel estimator and IDFT-Zero-Forcing(ZF) channel estimatior, especially in low signal-to-noise ratio (SNR).

We consider relay selection technique in a cooperative cellular network where user terminals act as mobile relays to help the communications between base station (BS) and mobile station (MS). A novel relay selection scheme, called Joint Uplink and Downlink Relay Selection (JUDRS), is proposed in this paper. Specifically, we generalize JUDRS in two key aspects: (i) relay is selected jointly for uplink and downlink, so that the relay selection overhead can be reduced, and (ii) we consider to minimize the weighted total energy consumption of MS, relay and BS by taking into account channel quality and traffic load condition of uplink and downlink. Information theoretic analysis of the diversity-multiplexing tradeoff demonstrates that the proposed scheme achieves full spatial diversity in the quantity of cooperating terminals in this network. And numerical results are provided to further confirm a significant energy efficiency gain of the proposed algorithm comparing to the previous best worse channel selection and best harmonic mean selection algorithms.

An optimal multi-user MIMO linear precoding scheme based on particle swarm optimization is proposed in this paper. The proposed scheme aims to maximize the system capacity of multi-user MIMO system. This paper explores a simplified function to measure the optimal problem. With the adoption of particle swarm optimization algorithm, the optimal linear precoding vector could be easily searched according to the simplified function. The proposed scheme outperforms the multiuser MIMO linear precoding schemes based on channel inversion and channel block diagonalization methods.

In this paper the optimal threshold is proposed to derive channel impulse response on the multi-path taps and eliminate noise on the other taps. The choice of threshold, which is crucial for the accuracy of the estimator, is analyzed theoretically and the optimal threshold introducing the least MSE is derived. Simulation results show that the performance of our proposed channel estimation with the optimal threshold has significant improvement over the conventional channel estimation algorithm.

This paper focuses on transmit pre-coding for multiuser multi-input multi-output (MU-MIMO) downlink channels. Multi-user interference (MUI) and noise are main factors that affect the performance of MU-MIMO system. Besides, the system performance will degrade as the receive power on different antennas gets unbalanced. The Block-diagonalization (BD) algorithm eliminates the MUI completely. However, the number of transmit and receive antennas are strictly limited, and the mitigation of noise is not considered. In this paper, two novel methods are proposed to solve these problems. One is antenna balancing in which we evaluate the receive power of each antenna and discard the unbalanced ones. This method could also relax the constraint on the number of antennas and enable more data streams transmission. The other one is noise suppression in which we design the pre-coding matrices using equivalent channels with noise compensation. Simulation results reveal that the noise suppression method can achieve better performance than BD, especially at lower SNR scale and the antenna balancing method can outperform BD in a wider SNR range. The methods provide significant gain in capacity without increasing computational complexity and greater performance improvement can be acquired when the two proposed methods are combined.

A low-density parity-check (LDPC) coded adaptive modulation and coding (AMC) strategy is presented for orthogonal frequency division multiplexing (OFDM) systems. Since system performance is improved as the maximum iteration times for LDPC decoding increase, iteration times for decoding reflect channel quality. We first propose an AMC strategy to utilize the information of iteration times for decoding to adopt higher order modulation and coding schemes (MCS) than the conventional strategy, so as to improve system throughput. Since it may bring worse reliability, hybrid automatic repeat request (H-ARQ) is used in a second strategy. Simulation under typical urban channel is carried out, and the results show the proposed strategies can bring higher throughput, and the strategy with H- ARQ can improve throughput and guarantee reliable transmission simultaneously.

Link adaptation technique is applied in an amplify and forward (AF) - orthogonal frequency division multiplexing (OFDM) relaying system, and adaptive bit and power allocation (ABPA) is investigated for such system. ABPA problem is presented first, and the optimal solution is proposed with aid of Greedy algorithm. Because channel transfer functions for two hops are independent, which limits throughput of a conventional AF-OFDM system, we take sub-carrier coupling (SQ into account. Two solutions are proposed for the problem with ABPA and SC; the first adopts a concatenated method to realize SC and ABPA with two steps, and the second utilized a joint way to adjust SC and allocated bits and power. Numeral simulation results show that the proposed ABPA solution can improve throughput greatly while guaranteeing bit error rate (BER) requirement very well. When SC is involved, more improvement can be obtained; the joint solution outperforms the concatenated solution.

In codebook based precoding MIMO system, the precoding codebook affects the system performance remarkably. Consequently, it is a crucial technology to design the optimum codebook for precoding MIMO system. Codebook design is related to the channel fading, antenna number, spatial correlation etc. So specific distributed channel corresponds to respective optimum codebook. In this paper, in order to design the optimum codebooks for the precoding MIMO system, a universal unitary space vector quantization (USVQ) codebook design criterion is provided, which can design the optimum codebooks for various spatial correlated channels with arbitrary antenna configurations. The unitary space K-mean(USK) algorithm is also provided to generate the USVQ codebook, which is iterative and convergent. Simulations show that the capacities of the precoding MIMO schemes using the USVQ codebooks are very close to those of the ideal precoding cases and outperform those of the schemes using the traditional Grassmannian codebooks.

In this paper, we propose a non-unitary codebook based precoding scheme for multi-user MIMO (MU-MIMO) downlink transmission with limited feedback The proposed MU- MIMO scheme will perform scheduling and precoding just according to the limited feedback of the signal to interference and noise ratio (SINR) of each user to enhance the system capacity. A precoder codebook design method is related to Grassmannian line packing criterion. We group vectors from the Grassmannian codebook into precoding matrices according to the correlation coefficient of the vectors to suppress the multi-user co-channel interference (CCI). It terms as non-unitary precoding and outperforms the traditional single user MIMO system as well as the unitary codebook based MU-MIMO scheme with limited feedback and low complexity.

A new noise variance estimation algorithm is presented for a multiuser OFDM system. In this estimator , the noise variance is derived from the traditional channel estimation results and no additional system cost is needed. Its performance is analyzed theoretically. The computational complexity is small and its performance is robust to noise power. Simulation results show that under multi-path fading channel the proposed estimator can obtain accurate real time measurements of the noise variance.

Amplify and forward (AF) is an effective mode for relaying systems with ease for implementation. In a conventional orthogonal frequency division multiplexing (OFDM) based AF system, relay stations simply amplifies the received signals and forward them to the destination station. Due to the fact that channel transfer function for the first hop (source-relay) and the second hop (relay-destination) may vary a lot, system capacity is limited. This contribution introduces a method named sub-carrier coupling, which couples sub-carriers for the two hops in a certain rule to improve system capacity. Firstly, system with a single relay station and its capacity is discussed, and the coupling scheme to maximize the system capacity is proposed. Then system with multiple relay stations is investigated, and two solutions are proposed. The solution with sub-carrier coupling can bring to much higher capacity since it determines the sub-carrier coupling scheme and assigns relay stations to forward signal for all sub-carriers jointly. Numerical simulation is carried out to show the efficiency of the proposed solutions.

In this contribution, spatial coding diversity is combined with spatial multiplexing to get higher joint gains on ensuring both low error rate and high spectrum efficiency. A general mathematical model of joint spatial coding and multiplexing (JSCM) is proposed and analyzed. Optimal criteria and a suboptimal iterative algorithm on the design of JSCM are studied. Performance of JSCM is proved by simulations from various aspects.

This paper investigates a spatial multiplexing MIMO scheme with beamforming for downlink transmission. The proposed scheme combines spatial multiplexing MIMO technique with beamforming, which has the advantages of both techniques. The proposed scheme utilizes the uplink direction of arrival (DOA) to perform downlink beamforming. It is able to transmit parallel data streams as well as providing beamforming gain and improve the system performance significantly. The proposed scheme provides better BER performance than the traditional spatial multiplexing and beamforming techniques under the same simulation environment.

Generalized distributed antenna is one of the most promising architectures likely to be used in next generation mobile communication systems. In this paper, based on the architecture, multi-user co-channel interference in Doppler spread estimation is analyzed and several useful conclusions are obtained. Moreover, in order to combat this interference, a novel ACF-based multi-user joint Doppler spread estimation (M- JDSE) algorithm is proposed, taking advantage of centralized signal processing characteristic in generalized distributed antenna systems. Both theoretical analysis and simulation results demonstrate the significant performance improvement of proposed M-JDSE algorithm in multi-user environments.

Abstract B3G–TDD uplink in China's FuTURE project is introduced in the paper. By taking advantage of MIMO–OFDM and special design for the TDD frame, peak data rate of 100 Mbps can be achieved. The system is required to support service in both indoor and outdoor environments, and guarantee high data rate communication even with mobility up to 250 kmph. Detail theoretical analysis was carried out to give the principle of designing frame structure for the system under different environments. In order to reduce the influence of Doppler Effect, adaptive frame structure is proposed for the uplink. By special design on the frame for different environments, the channel information can be tracked accurately with low overhead, which ensures the system performance. Through simulation based on the platform of Future Technologies for Universal Radio Enviroment (FuTURE) project, bit error rate (BER) can achieve lower than 10−6 when Eb/N0 is 3 dB for various mobility case in both indoor and outdoor environments, which satisfies the requirement of FuTURE project. By employing it into B3G–TDD uplink, robustness to Doppler Effect is strengthened greatly. Copyright © 2007 John Wiley & Sons, Ltd.

Large progress has been made in the research and realization of the ldquoB3Grdquo (Beyond 3G) TDD mode demonstration system in ldquoB3Grdquo TDD group of Chinese FuTURE (Future Technologies for Universal Radio Environments) project, which is introduced in this paper. Since the ldquoB3Grdquo demonstration system aims at evaluating the radio transmit technologies such as MIMO, OFDM etc. to bear a high data rate up to 100 Mbps, the previous results presented in several literatures coming from the FuTURE project are focusing on the high data rate services transmission. However, services with low data rate such as voice services etc. should also be transmitted in the ldquoB3Grdquo system, which has a relatively smaller bandwidth. In this paper the technologies for voice service are introduced and the performance is analyzed in the whole-link demonstration system, since voice service is a basic service in the mobile communication systems.

According to the features of TD-SCDMA system, a novel multi-antenna pre-processing model and algorithm is proposed. Meanwhile, the more precise uplink channel estimation and downlink channel prediction are put forward for TD-SCDMA system to improve the performance of basic multi-antenna pre-processing algorithm. Simulation results show that: by using the proposed multi-antenna pre-processing technology, the capacity and performance of TD-SCDMA system is significantly improved. Meanwhile, the improved multi-antenna pre-processing algorithm performs better than the basic algorithm under fast varying channel condition.

In this contribution, some important issues toward B3G (beyond 3G) mobile communication systems are analyzed, including the developing tendency, promising technologies, and demonstration system construction. Advanced technologies for B3G application are introduced comprehensively from physical layer techniques to network layer strategies. The B3G demonstration system developed in WTI (wireless technology innovation) lab is termed as TD-MC-CDMA system. Technical scheme and simulation results of TD-MC-CDMA demonstration system are presented. Discussions for the prediction of next generation mobile communication systems are given.

In this contribution. we propose a novel space-frequency block coded adaptive modulated OFDM (SFBC-AOFDM) scheme to provide high data rate and high spectrum efficiency, this scheme is very effective to combat last lading anyway. Its robustness to frequency-selective fading could be adjusted by changing the SFBC coding size and adaptation unit. In this scheme, we extend the application of adaptive modulation into a MIMO-OFDM system in a simple way. Furthermore, a novel SFBC detection algorithm is proposed to reduce complexity for high order QAM employments. We simulate for SFBC-AOFDM with various MIMO settings and analyse the performance of both BCR and transmission efficiency.

The practical DOA estimation method for uniform circular smart antenna (UCSA) is considered. DOA estimation with unitary root-MUSIC algorithm, which exploits a real-valued eigendecomposition, greatly reduces its computational complexity. However, its application is limited to the uniform linear smart antenna (ULSA). In this contribution, we propose a novel signal converter through which the low cost unitary root-MUSIC algorithm can be exploited for uniform circular smart antenna. The converter is easy to implement by IFFT transformation and real-valued weighting. Simulation results show this method is feasible to provide high resolution and high capacity.

Multi-antenna OFDM system calls the consideration of coding across antennas and OFDM tones. Derived from the design criteria for space-time block codes (STBC), the coding scheme termed space-frequency block codes (SFBC) is conceived to achieve the maximum diversity order for a given number of transmit and receive antennas. In this contribution, a practical space-frequency block coded OFDM scheme (SFBC-OFDM) is proposed for fast fading broadband channels. Besides, this novel scheme is rather flexible to combat the frequency-selective fading by decreasing the coding size. Simulation and analysis show that our scheme outperforms the STBC-OFDM scheme in the scenario with high vehicle speed and large delay spread when the number of subcarriers in the OFDM system is large.