In this article, we study a data-driven real-time machine learning method for end-to-end wireless systems for the Internet of Things (IoT). For a two-way communication link between two IoT devices, we propose an efficient learning algorithm that can train the autoencoder-based transmitter and receiver in each device without needing to know the channel between two devices. To this end, we adopt the conditional generative adversarial network (cGAN) that can learn an output distribution of the channel for a given conditioning signal. Our proposed training method consists of the link update stage and the self-update stage. In the link update stage, two devices transmit the training data and update their own receiver and the cGAN simultaneously. Subsequently, in the self-update stage, the two devices train their transmitters at the same time for the given receivers and cGANs. Our proposed real-time training method is updated without the knowledge of the channel models nor information feedback for training. Finally, we demonstrate that the proposed training method achieves significant performance gains over conventional schemes in various practical communication scenarios.

This work develops a joint design of user association and time allocation for wireless powered communication networks. A harvest-then-transmit protocol is applied with base stations (BSs) transfer wireless energy to users in the first downlink phase. Then, the users utilize the harvested energy for their information transmission to the BS in the subsequent uplink phase. In this configuration, we employ a general$\alpha $–fair utility to maximize the network throughput. In particular, the maximization of sum-rate, proportional fairness and minimum rate are investigated individually. We introduce a new message-passing based framework to provide an efficient distributed solution for the user association and optimize the time allocation between the downlink and uplink phase. To achieve this joint goal, each user selects a BS in a distributed manner to maximize the$\alpha $–fair utility. After identifying the user association, the time allocation is determined by an efficient line search technique. Simulation results show that the proposed algorithm outperforms existing approaches.

In this work, we study a scenario where a distant central monitor covertly wiretaps the communication between a pair of suspicious users via several single-antenna full-duplex spoofing relays and a cooperative jammer for wireless surveillance. Under an adaptive transmission policy where the data rate of the suspicious users is determined based on the channel condition at the receiver, the spoofing relays intercept and forward manipulated information to control the data rate of the suspicious users for effective eavesdropping. We first propose an inter-relay interference suppression method to eliminate undesirable signals at the spoofing relays. Then, we provide a joint optimization technique for relay weights and jamming power to maximize the eavesdropping rate by a two-layer semi-definite relaxation approach. Simulation results show that the proposed solution outperforms other practical baseline schemes.

For a self-sustaining wireless communication system in the Internet-of-Things (IoT) networks, energy harvesting (EH) can be implemented at each user node as a constant renewable power supply source. Hence, an investigation into the use of wireless-powered communication network (WPCN) protocols to facilitate communication between an access point (AP) and multiple mobile users (MUs) is presented in this article. The AP has multiple antennas and operates in the full-duplex (FD) mode. The MUs, on the other hand, have single antennas and works in the half-duplex (HD) mode. Each MU communicating with the FD-AP is assigned to one of two groups, based on the time allocation and channel access for either uplink (UL) or downlink (DL) communication. The channel assignment, time resource, and power resource allocations are optimized to maximize the UL weighted sum rate. The sum-rate optimization problem is found to be nonconvex. Therefore, an iterative algorithm is investigated to optimize the UL weighted sum rate of the proposed FD-WPCN system. Next, the proposed FD-WPCN algorithm is modified for HD-WPCN-enabled communication between the AP and multiple MUs. Extensive simulations are conducted to verify the proposed algorithm for FD-WPCN and compare its performance with the HD-WPCN counterpart. From the simulation results, FD-WPCN outperformed HD-WPCN at a low AP transmit signal-to-noise ratio (SNR) region. The opposite behavior is observed for high AP transmit SNR due to increasing residual self-interference at the FD-AP.

This paper studies the spectral/energy efficiency (SE/EE) of a heterogeneous network with the backhaul enabled by low-resolution analog-to-digital converters (ADCs) quantized full-duplex massive multiple-input multiple-output (MIMO) over Rician channels. Backhaul communication is completed over two phases. During the first phase, the macro-cell (MC) base station (BS) deploys massive receive antennas and a few transmit antennas; the small-cell (SC) BSs employ large-scale receive antennas and a single transmit antenna. For the second phase, the roles of the transmit and receive antennas are switched. Due to the low-resolution ADCs, we account for quantization noise (QN). We characterize the joint impact of the number of antennas, self-interference, SC-to-SC interference, QN, and Rician K-factor. For the first phase, the SE is enhanced with the massive receive antennas and the loss due to QN is limited. For the second phase, the desired signal and QN have the same order. Therefore, the SE saturates with the massive transmit antennas. As the Rician K-factor increases, the SE converges. Power scaling laws are derived to demonstrate that the transmit power can be scaled down proportionally to the massive antennas. We investigate the EE/SE trade-offs. The envelope of the EE/SE region grows with increase in the Rician K-factor.

Massive MIMO is one of the salient techniques for achieving high spectral efficiency in the next-generation wireless networks. Recently, a combined strategy of the massive MIMO and the artificial noise (AN), namely, AN assisted massive (ANAM) MIMO has been investigated for security enhancement. However, most of the recent studies have been built upon the assumption of perfect channel state information (CSI) at the eavesdropper (ED), the results of which may be too pessimistic in terms of security because there exists no ED-friendly downlink training from the base station in the practical ANAM systems. In this paper, we provide more sophisticated analysis on the secrecy performance of the ANAM systems assuming that the CSI of the ED channels are unknown to both the base station and the ED or partially known to the ED. We measure the secrecy in terms of the leakage rate to the ED (or the secrecy rate to the legitimate users) and characterize their upper and lower bounds in the high signal-to-noise ratio regime. Our analytical result is represented by a single compact expression as a function of the number of ED antennas, the dimensionality of signal space, and the channel coherence time, and thus offers useful insights that help us fully exploit the secrecy potential of the ANAM systems. Finally, several useful observations are made from the numerical examples.

In this paper, we consider a legitimate proactive eavesdropping scenario where a central monitor tries to intercept the information exchanged between a pair of suspicious entities through amplify-and-forward full- duplex relays and a cooperative jammer. Specifically, the eavesdropping relays simultaneously listen to the suspicious transmitter and forward the eavesdropped information to the central monitor. At the same time, the jammer broadcasts the jamming signal to maintain the suspicious data rate below the channel capacity of the central monitor so that the eavesdropped information can be successfully decoded by the central monitor. In this system, we jointly design the relay precoders at the eavesdropping relays and the transmit covariance matrix at the jammer to maximize the eavesdropping rate by a two-layer semi-definite relaxation approach. Simulation results verify the efficiency of our proposed solution and show considerable performance gains over conventional schemes.

In this work, we investigate a wireless powered communication network (WPCN) where multiple eavesdroppers attempt to intercept the information between a hybrid access-point (H-AP) and an energy harvesting (EH) user. During the first energy transfer (ET) phase, the EH user and an EH cooperative jammer harvest energy from the transmitted signals of the H- AP. Then, in the next information transfer (IT) phase, the user sends confidential information to the H-AP while the jammer broadcasts artificial noises to the eavesdroppers by utilizing their previously harvested energy. We particularly consider optimization of the time allocation between the ET and the IT phases by which the secrecy rate is maximized. To cut down a computational burden, a low-complexity closed-form solution of the time allocation factor with some interesting behaviors will be proposed by a worst-case approximation. Through simulation results, we evaluate the performance of our proposed scheme and show that a performance gain compared to conventional schemes becomes clearer with the increased number of eavesdroppers.

In this paper, we consider a legitimate proactive eavesdropping scenario where a distant central monitor covertly wiretaps the communication between a pair of suspicious users via several multi-antenna full-duplex spoofing relays and a multi-antenna cooperative jammer. Assuming an adaptive transmission policy at the suspicious users, the spoofing relays not only intercept but also forward the manipulated information to control the data rate of the suspicious users in collaboration with the jammer. We provide a technique which jointly optimizes the receive combining vector at the central monitor, the precoders at the relays, and the transmit covariance matrix at the jammer for maximizing the eavesdropping rate. To reveal some fundamental properties of the optimal operation, we first study a single-relay system. It is shown that when the central monitor experiences a poor eavesdropping channel link, the spoofing relay and the jammer should transmit destructive signals and jamming signals, respectively. In this case, the suspicious users are forced to decrease their data rate, while the intercepted information can be successfully decoded by the central monitor. On the other hand, when the eavesdropping channel condition is favorable, the spoofing relay forwards constructive signals to further increase the data rate at the suspicious users in a way that more information can be intercepted from the suspicious users. We then formulate a general eavesdropping rate maximization problem for multiple relays and present a semi-definite relaxation approach. A low-complexity design is also proposed based on our analysis for the single-relay system. Simulation results verify the efficiency of the proposed solutions compared to other baseline schemes in various practical setups.

In this paper, we consider a proactive eavesdropping scenario, where a central monitor tries to intercept the information exchanged between a pair of suspicious entities through amplify-and-forward full-duplex relays and a cooperative jammer. Specifically, the eavesdropping relays simultaneously listen to the suspicious transmitter and forward the eavesdropped information to the central monitor. At the same time, the jammer broadcasts jamming signals to maintain the data rate of the suspicious users below the channel capacity of the central monitor so that the eavesdropped information can be successfully decoded by the central monitor. In this system, we jointly design the receive combining vector at the central monitor, the relay precoders at the eavesdropping relays and the transmit covariance matrix at the jammer to maximize the eavesdropping rate. First, we examine the case of a single eavesdropping relay equipped with a single antenna and provide some useful insights. Also, an effective two-layer optimization method is proposed to obtain the globally optimal solution. Then, we study a general case of multiple eavesdropping relays with multiple antennas, and solve a semi-definite relaxation problem. Numerical results verify the efficiency of our proposed solutions for both single and multiple relay cases and show considerable performance gains over conventional schemes.

When implementing single radio frequency (RF) chain multi-user (MU) millimeter-wave (mmWave) systems, an RF beamforming algorithm with a short beam training overhead is essential. In this paper, we propose a new MU RF beamforming algorithm based on the conventional RF beam training method in IEEE 802.11ad. Then, we investigate its asymptotic behavior for a large number of users scenario. We show that the proposed scheme approaches the optimal full search scheme with much reduced beam training latency as the number of users grows. Our simulation results demonstrate that a performance gain of the proposed method over the full search method is about 35% in practical MU mmWave environments in terms of the effective data rate.

In this paper, we consider a wireless powered communication network with an energy harvesting (EH) jammer where eavesdroppers try to wiretap the communication between users and a hybrid access-point (H-AP). In our system, the H-AP first transmits an energy signal to recharge the batteries of the EH users and the EH jammer in the energy transfer (ET) phase. Then, in the subsequent information transfer (IT) phase, each user sends information to the H-AP in a time division multiple access manner, while the jammer generates jamming signals to interfere the eavesdroppers. We adopt two different secrecy performance measurements according to the level of channel state information (CSI) of the eavesdroppers. First, with a single user, we maximize the secrecy rate by optimizing the time allocation between the ET and the IT phase when perfect CSI of the eavesdroppers is available at all nodes. In contrast, when the instantaneous CSI of the eavesdroppers is not available at legitimate nodes, we analyze and minimize the secrecy outage probability. We also extend the single user analysis to a more general multi-user situation with an additional consideration of the transmit power allocation at the jammer. Finally, we evaluate the performance of our proposed solutions through simulations and demonstrate that a performance gain compared to conventional schemes becomes more pronounced with the increased number of eavesdroppers and users.

In this paper, we study a joint spatial division multiplexing (JSDM) beamforming scheme, which enables large-scale spatial multiplexing gains for massive multi-input multi-output downlink systems. In contrast to the conventional JSDM, which employs a block diagonalization method as a pre-beamformer, we aim to maximize sum-rate by applying minimum-mean-squared error (MMSE) approaches when designing a pre-beamformer and a multi-user precoder sequentially. First, to suppress inter-group interference, we design the pre-beamformer, which minimizes an upper bound of the sum mean-squared-error in the large-scale array regime. Then, to mitigate same-group interference, we present the multi-user precoder based on the weighted MMSE (WMMSE) optimization method, which requires the same channel state information overhead as the conventional JSDM. Also, in order to reduce the computational complexity, we compute deterministic equivalents of the WMMSE beamforming parameters to generate the beamformers by employing asymptotic results of large system analysis. Through simulation results, we confirm that the proposed two-step beamforming methods bring substantial performance gains in terms of sum-rate over the conventional JSDM schemes especially in a low and medium signal-to-noise ratio regime with comparable complexity.

In this paper, we study multi-user multi-input multi-output cognitive wireless powered communication networks (WPCN), in which a secondary WPCN shares spectrum with a primary wireless information transfer system. A typical WPCN consists of two different phases. In the first downlink phase, a hybrid access point (H-AP) transfers energy to charge users, and then in the subsequent uplink phase, the users send information by using the harvested energy to the H-AP. We consider two different cognitive WPCN protocols depending on the cooperation level between the primary transmitter and the secondary H-AP. For both cases, we formulate sum throughput maximization problems by taking the interference leakage to the primary network into consideration. The problems are generally non-convex due to coupled variables in the WPCN. To tackle this issue, we first convert the problems into equivalent convex forms, and then identify the global optimal solutions by applying the proposed iterative optimization algorithms. Finally, the simulation results demonstrate that the proposed algorithms outperform conventional schemes.

This paper investigates multi-user multi-input multi- output cognitive wireless powered communication networks (WPCN), in which a secondary WPCN shares spectrum with a primary wireless information transfer system. A typical WPCN consists of two different phases. In the first downlink phase, a hybrid access point (H-AP) transfers energy to charge users, and then in the subsequent uplink phase, the users send information by using the harvested energy to the H-AP. We consider underlay cognitive WPCN without cooperation between the primary transmitter and the secondary H-AP. In this case, we formulate sum throughput maximization problem by taking the interference leakage to the primary network into consideration. The problem is generally non-convex due to coupled variables in the WPCN. To tackle this issue, we first convert the problem into equivalent convex form, and then identify the global optimal solution by applying the proposed iterative optimization algorithm. Finally, simulation results demonstrate that the proposed algorithm outperforms conventional schemes.

In this work, we consider a wireless powered communication network (WPCN) with an energy harvesting (EH) jammer where an eavesdropper tries to wiretap the communication between a user and a hybrid access-point (H-AP). In our system, the H-AP first transmits an energy signal to recharge the batteries of the EH user and the EH jammer in the energy transfer (ET) phase. Then, in the subsequent information transfer (IT) phase, the user sends its information signal to the H-AP, while the jammer generates the jamming signal to interfere the eavesdropper utilizing the harvested energy in the ET phase. Assuming only the channel distribution information (CDI) of the eavesdropper is available at the legitimate nodes, we analyze and minimize the secrecy outage probability by optimizing the time allocation between the two phases. To reduce the complexity, we also provide a simple closed-form solution, and the simulation results verify that its performance approaches the optimum.

In this paper, we present a new beamforming design at the relay in AF two-way relaying systems where a relay node with Nr antennas serves two source nodes equipped with a single antenna. In this system, we design low complexity relay beamforming which minimizes the mean squared error (MSE). To this end, unlike conventional designs based on perfect self-interference cancellation at each source whose computational effort grows with an order of O(N6r), we determine the level of SIC in an MSE optimization problem, thereby obtaining a new insightful closed-form solution with complexity of O(N2r). It is also shown that the channel estimation overhead can be reduced by our methods. Finally, simulation results demonstrate that the proposed design method achieves the minimum MSE with reduced complexity.

In this paper, we study a joint spatial division multiplexing (JSDM) beamforming scheme which enables large-scale spatial multiplexing gains for massive MIMO downlink systems. In contrast to the conventional JSDM which employs a block diagonalization (BD) method as a pre-beamformer, we aim to maximize sum-rate by applying minimum-mean-squared error (MMSE) approaches when designing a pre-beamformer and a multi-user precoder sequentially. First, to suppress inter-group interference, we design the pre-beamformer which minimizes an upper bound of the sum mean-squared-error in the large-scale array regime. Then, to mitigate same-group interference, we present the multi-user precoder based on the weighted MMSE (WMMSE) optimization method, which requires the same channel state information overhead as the conventional JSDM. Through simulation results, we confirm that the proposed two-step beamforming method brings substantial performance gains in terms of sum-rate over the conventional JSDM schemes especially in low to medium signal-to-noise ratio (SNR) regime.

This letter studies a joint design of fronthaul and radio access links for a cloud radio access network (C-RAN) with wireless fronthauling, where a baseband unit (BBU) controls a number of remote radio heads (RRHs) via wireless fronthaul links to communicate with user equipments. We first review a basic approach based on a single cell concept, whereby the RRHs operate as decode-and-forward (DF) relays. Then, a cooperative transmission from the RRHs based on decompress-and-forward (DCF) relaying is proposed, which is a standard concept in C-RAN. For both strategies, a problem of jointly optimizing the BBU and RRH operations is tackled with the goal of maximizing the weighted sum-rate subject to the BBU and per-RRH power constraints. For each formulated problem, an iterative algorithm is derived that achieves a sequence of monotonically nondecreasing objective values at each iteration. It is confirmed via numerical results that the DCF-based cooperative scheme significantly outperforms the DF-based single-cell approach.

In this paper, we provide a comprehensive survey on designs and analyses of various relay-destination transceiving schemes, such as zero-forcing (ZF), minimum mean squared error (MMSE), and maximum information rate (MIR) criteria, in multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems. In the first part of the paper, we suggest a new framework for the transceiver designs utilizing a decomposable property of the error covariance matrix to give a general insight on the system and make the analysis more tractable. Then, in the second part of the paper, we provide an in-depth analysis on their diversity performance. Our analysis embraces two different scenarios, namely, the diversity-multiplexing tradeoff (DMT) and the diversity-rate tradeoff (DRT). First, we derive compact closed-form expressions for the DMT through tight upper and lower bounds. Then, we observe that while our DMT analysis accurately predicts performance of the ZF and MIR schemes, the MMSE-based designs exhibit a complicated rate-dependent behavior and, thus, are very unpredictable via DMT for finite rate cases. Thus, second, we highlight this interesting observation and characterize the diversity of the MMSE schemes at all finite rates. This leads to closed-form expressions for the DRT which reveals relationship between diversity, spectral efficiency, and the number of antennas at each node. The DRT analysis compliments our work on DMT, and thus, the paper provides a complete understanding on the diversity of MIMO AF relaying systems.

This paper studies precoder designs for simultaneous wireless information and power transfer (SWIPT) in multi-input multi-output (MIMO) channels, where a transmitter sends information to information decoding (ID) users while satisfying the minimum energy requirement of energy harvesting users. In contrast to the previous designs focused only on maximum information rate (MIR), we propose a more general and simpler solution using the weighted minimum mean squared error (WMMSE) criterion. To solve the SWIPT-WMMSE problem which is generally non-convex, we suggest two different design schemes, separate and joint designs. Interestingly, it is shown that the joint design achieves optimal performance with a single initial point and a few iterations, while the separate design needs a large number of iterations and initial points to approach the optimum. Based on the observation, we propose a simple closed-form solution, which is shown to achieve near optimal performance with reduced complexity. The derived solution can be adopted in various pragmatic applications of MIMO communications, such as the MMSE, quality-of-service, equal error designs, as well as the MIR by adjusting the weight matrix. We also confirm that our design strategies are a great use for managing co-channel interference in multiple ID-user scenarios. Finally, simulation results demonstrate the efficiency of the proposed MIMO-SWIPT framework.

In this paper, we present a power allocation method for a distributed antenna system (DAS) to maximize energy efficiency (EE), which is defined as the ratio of the transmission rate to the total consumed power. Different from conventional EE maximization schemes that require iterative numerical methods, we derive the optimal solution as a closed form by solving Karush-Kuhn-Tucker conditions. The obtained closed-form expression is applicable to DAS with an arbitrary number of distributed antenna (DA) ports and general per-DA port power constraints and is also guaranteed to be globally optimum. Then, we provide several interesting observations on the proposed EE maximizing power allocation scheme. Based on these results, we propose a simplified practical power allocation method that employs the DA port selection and computes the power level in a distributed manner. Through Monte Carlo simulations, we show that the proposed optimal power allocation method produces the EE identical to exhaustive search with significantly reduced computational complexity. In addition, it is shown that the proposed simplified power allocation method based on the DA port selection exhibits little performance loss compared to the optimal algorithm with a remarkable reduction in the system overhead.

In this paper, we provide new precoding schemes which jointly optimize the source and relay precoders in multiple-input multiple-output amplify-and-forward relaying systems with minimum mean-squared error decision feedback equalizer (DFE) at the destination node. Instead of conventional schemes which resort to an iterative method, we propose simple precoding schemes based on a closed-form solution. To this end, we first extend the decomposable property of the error covariance matrix for a linear receiver to relaying systems with DFE receivers. Then, we suggest two closed-form solutions which successively identify the source and the relay precoders. To improve the performance, a mode selection which adaptively chooses one of the two closed-form precoding schemes according to the channel conditions is introduced. Then, we propose a simple eigenvalue based mode selection algorithm, and analyze its selection probability behavior for Rayleigh fading channels. Simulation results demonstrate that the performance of the proposed method is almost identical to the iterative solution with much reduced complexity.

In this paper, we propose new relay transceiver designs based on the minimum mean square error (MMSE) criterion for amplify-and-forward multiple-input-multiple-output (MIMO) relaying systems with direct link. Since each antenna element is equipped with its own power amplifier, a norm power constraint, which restricts the transmit power with the expected norm of the transmit signal vector, is not suitable for practical systems. Therefore, we consider a shaping constraint (SC), which imposes a limit on the shape of the transmit covariance matrix. The SC includes several power constraints such as the peak power constraint and the per-antenna power constraint as special cases. To this end, we first derive the optimal structure of the MMSE relay transceiver under the SC. Then, by introducing an upper bound of the mean square error, we provide closed-form relay transceiver solutions. Due to limited bandwidth of the feedback channel, perfect channel knowledge at the transmitter may not be feasible. Thus, we also propose a quantized relay transceiver design based on Grassmannian codebooks for a limited-feedback scenario. From simulation results, it is confirmed that the proposed relay transceiver techniques demonstrate a significant performance improvement compared with conventional schemes.

In this paper, we propose a new relay transceiver design based on the minimum mean-squared error criterion for non-regenerative multiple-input multiple-output relaying systems with direct link. Since norm power constraint at the relay node does not restrict the output power at each antenna element in designing the relay transceiver, we consider maximum eigenvalue constraint (MVC) which imposes a limit on the peak power of the output. To this end, we first derive the optimal structure of the relay transceiver under the MVC. Then, by introducing an upper bound of the mean-squared error which makes the problem tractable, we provide a closed-form relay transceiver design with the MVC. From simulation results, it is confirmed that the proposed relay transceiver technique demonstrates a significant performance improvement compared to conventional schemes.

This paper investigates the diversity order of the minimum mean squared error (MMSE) based optimal transceivers in multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems. While the diversity-multiplexing tradeoff (DMT) analysis accurately predicts the behavior of the MMSE receiver for the positive multiplexing gain, it turned out that the performance is very unpredictable via DMT for the case of fixed rates, because MMSE strategies exhibit a complicated rate dependent behavior. In this paper, we establish the diversity-rate tradeoff performance of MIMO AF relaying systems with the MMSE transceivers as a closed-form for all fixed rates, thereby providing a complete characterization of the diversity order together with the earlier work on DMT.

In this paper, we propose a new beamforming technique that maximizes the end-to-end signal-to-noise ratio (SNR) for amplify-and-forward multiple-input-multiple-output cooperative relaying systems with direct link between thesource and the destination. Instead of conventional schemes resorting to an iterative method, such as a gradient ascentalgorithm, our scheme provides a simple closed-form solution for source-relay joint beamformer designs. To this end, wefirst derive a new expression of the end-to-end SNR for the cooperative relaying systems and its lower bound, which isgiven as the harmonic mean of two individual SNRs. Then, a new beamforming scheme, which adaptively optimizes one of the two SNRs depending on the channel condition, is proposed. In addition, we perform a diversity order analysis of the proposed scheme and show that our scheme achieves a full diversity order of relaying systems with direct link. It is confirmed by simulation results that the proposed technique obtains almost identical performance to the gradient ascent algorithm with much reduced complexity, and our analytical work accurately predicts the numerical results.

In this paper, we consider multipoint-to-multipoint multi-input multi-output relay systems where multiple source-destination pairs simultaneously communicate through a single multiple antenna relay. In this system configuration, we optimize two metrics when designing the source, relay and destination filters. The first one is sum mean-squared-error (MSE) and the second one is maximum pairwise MSE. These two problems are shown to be non-convex, and thus it is quite complex to find an analytical solution. To address this issue, we first introduce the sum MSE minimization scheme based on global channel state information (CSI) at all nodes. Then, a method which reduces complexity and CSI requirements is proposed by utilizing error covariance decomposition and MSE duality between broadcast channel and multiple access channel. Second, the pairwise MSE balancing algorithms are developed to guarantee fairness for all pairs. Similar to the case of the sum MSE minimization problem, we simplify the original pairwise MSE balancing problem to a second-order cone programming problem which can be solved using standard optimization tools. Through numerical simulations, we confirm the effectiveness of our proposed schemes.

In this paper, we consider multipoint-to-multipoint multi-input multi-output relay systems where multiple source-destination pairs simultaneously communicate through a single multiple antenna relay. In this system configuration, we optimize sum mean-squared-error (MSE). This problem is shown to be non-convex, and thus it is quite complex to find an analytical solution. To address this issue, we first introduce the sum MSE minimization scheme based on global channel state information (CSI) at all nodes. Then, a method which reduces complexity and CSI requirements is proposed by utilizing error covariance decomposition and MSE duality between broadcast channel and multiple access channel. Through numerical simulations, we confirm the effectiveness of our proposed schemes.

In this paper, we present a power allocation method for a distributed antenna system (DAS) to maximize energy efficiency (EE) which is defined as the ratio of the transmission rate to the total consumed power. Different from conventional EE maximization schemes which require iterative numerical methods, we derive the optimal solution as closed form by solving Karush-Kuhn-Tucker conditions. The obtained closed form expression is applicable to DAS with an arbitrary number of distributed antenna (DA) ports and general per-DA port power constraints, and is also guaranteed to be globally optimum. Through Monte Carlo simulations, we show that the proposed power allocation method produces the optimal average EE identical to exhaustive search with significantly reduced computational complexity. In addition, we demonstrate that DAS is more beneficial in terms of EE compared to conventional antenna systems.

In this paper, we provide a new design scheme which jointly optimizes the source and relay precoders in multiple-input multiple-output amplify-and-forward relaying systems with minimum mean-squared error (MMSE) decision feedback equalizer (DFE) at the destination node. Instead of conventional optimal designs which require an iterative method, we propose a simple and near optimal closed-form scheme. First, we extend the decomposable property of the error covariance matrix based on linear MMSE receiver to our case. Next, we suggest a new scheme which jointly finds the source and relay precoders with a closed-form solution. Simulation results demonstrate that the performance of the proposed method is less than 1 dB away from the optimal solution with much reduced complexity.

In this paper, we propose a new beamforming technique for signal-to-noise ratio maximization in nonregenerative multiple-input multiple-output cooperative relaying systems where a non-negligible direct link between the source and the destination exists. Instead of conventional optimal schemes resorting to an iterative method such as a gradient ascent algorithm, we provide a simple closed form solution for source-relay joint beamformer designs. To this end, we apply the error decomposition property which allows us to separate the problem into two phases. Then, we propose a new beamforming scheme which adaptively aligns the transmit signal to each phase depending on the channel condition. From simulation results, we confirm that the proposed technique obtains the near-optimal performance.

In this paper, we study a filter design which maximizes the weighted sum rate (WSR) in multi-user multi-relay systems equipped with multiple antennas at each node and account for the direct links between the base station and the mobile users. Since this problem is generally non-convex, it is quite complicated to analytically find a solution. Hence, we transform the WSR maximization problem to an equivalent weighted sum mean-squared-error (WSMSE) minimization problem which is more amenable. Then, we identify the filters at the base station and the relays for minimizing the WSMSE with a proper weight and propose an alternating computation algorithm which guarantees a local optimum solution. Through simulations, we confirm the effectiveness of our proposed scheme.

In this paper, we consider multipoint-to-multipoint multi-input multi-output relay systems where multiple sourcedestination pairs simultaneously communicate through a single multiple antenna relay. In this system configuration, we minimize the maximum pairwise mean-squared-error (MSE) to guarantee fairness for all pairs. This problem is non-convex, and thus it is quite complex to find an analytical solution. In order to simplify this problem, we apply error covariance decomposition approach and broadcast channel to multiple access channel MSE duality, and then a pairwise MSE balancing scheme which utilizes global channel state information (CSI) is proposed. In order to reduce the complexity and CSI requirements, a new method is developed. Through numerical simulations, we confirm the effectiveness of our proposed schemes.

In this paper, we present the diversity-multiplexing tradeoff (DMT) analysis for minimum mean squared error (MMSE) based amplify-and-forward cooperative multiple antenna half-duplex relaying systems where a non-negligible direct link exists between the source and the destination. First, we evaluate an upperbound of the DMT which offers a theoretical limit of the system and show that the upperbound is actually achievable by existing optimal and suboptimal designs for the relay amplifying matrix. Thereby, we establish the optimal DMT for the MMSE-based cooperative relaying system. Our analysis also illustrate the optimality of the conventional relay matrix designs in terms of the DMT and leads to several interesting observations. Finally, numerical simulations demonstrate the accuracy of our analysis.

A relay selection method is one of popular approaches to overcome fading effects in wireless relay channel due to its simplicity. However, previous works were concentrated on the case of analog network coding systems. In this paper, we consider a relay selection scheme in two-way relaying systems with physical network coding. Since conventional schemes based on analog network coding does not provide effective performance in physical network coded systems, we propose new selection criteria which maximize the minimum distance at the multiple access phase to achieve full diversity. Moreover, through asymptotic error rate analysis, it is confirmed that the proposed scheme is able to attain full diversity. Simulations results are also provided to verify the analysis of the proposed scheme.

In this paper, we study a power allocation technique for Tomlinson-Harashima precoding (THP) in multi- user multiple input single output (MISO) downlink systems. In contrast to previous approaches, a mutual information based method is exploited for maximizing the sum rate of zero-forcing THP systems. Then, we propose a simple power allocation algorithm which assigns proper power level for modulo operated users. Simulation results show that the proposed scheme outperforms a conventional water-filling method, and achieves near optimal performance with much reduced complexity.

In this paper, we investigate minimum mean squared error (MMSE) based amplify-and-forward cooperative multiple antenna relaying systems where a non-negligible direct link exists between the source and the destination. First, we provide a new design strategy for optimizing the relay amplifying matrix. Instead of conventional optimal design approaches resorting to an iterative gradient method, we propose a near optimal closed-form solution which provides an insight. As relay systems with a direct link incur a non-convex problem in general, we exploit the decomposable property of the error covariance matrix and a relaxation technique imposing a structural constraint on the problem. Next, we study the error performance limit of the proposed scheme using diversity-multiplexing tradeoff analysis, which leads to several interesting observations on MMSE-based cooperative relaying systems. Finally, through numerical simulations, we confirm that the proposed solution shows the performance very close to the optimum with much reduced complexity and the analysis closely matches with simulation results.

In this paper, we investigate the minimum mean squared error based relay transceiver design in amplify-and-forward multiple antenna relay systems in the presence of direct link. Instead of the conventional optimal design which requires iterative methods, we propose a simple and near optimal closed-form solution. The proposed method exploits the decomposable property of the error covariance matrix to simplify the problem. Then, we impose a structural constraint on the non-convex problem to attain a simple closed-form solution. Through numerical simulations, we confirm that the proposed solution has almost no performance loss compared to the optimal iterative design with much reduced complexity.

In this paper, we propose a general framework to quantify the average error probability of the minimum mean squared error based precoding schemes in amplify-and-forward relay networks where all nodes are equipped with multiple antennas. Especially, we investigate spatial multiplexing schemes which transmit multiple data streams simultaneously. Due to difficulty in finding an exact expression of the average error rate, we exploit the high signal-to-noise-ratio (SNR) based approach which allows a simple and accurate characterization of the performance. Then, we derive new closed form expressions for bit error rate performance of both the optimal source-relay joint precoding schemes and the optimal relay only precoding schemes in terms of a coding gain as well as a diversity gain. Taking a different pathloss in each hop into consideration, we evaluate the performance in a generalized environment. Through our analysis, we discuss several interesting observations and provide a helpful guideline for designing MMSE-based relaying systems. Monte-Carlo simulations show that our analytical work accurately predicts numerical results.

In this letter, we investigate the diversity performance of coded beamforming schemes in AF multiple antenna relay systems for frequency selective channels. To extract available multipath diversity, we utilize orthogonal frequency division multiplexing combined with bit-interleaved coded modulation. The pairwise error probability is analyzed based on the correlated fading assumption, and the theoretical evaluation of the maximum achievable diversity order is presented. From the analysis, a proper code construction criterion is provided which achieves the full diversity with the minimum code memory. Our analysis also demonstrates that the subcarrier mapping (or pairing) operations at the relay have no impact on the diversity order. Simulations confirm that our analysis is accurate and matches well with the simulation results.

In this paper, we propose a general framework to investigate the average bit error rate (BER) performance of minimum mean square error (MMSE) based transceiver designs in amplify-and-forward relaying systems where all nodes are equipped with multiple antennas. Especially, we consider spatial multiplexing relaying schemes which transmit independent data streams simultaneously, which include the single stream beamforming design as a special case. Due to difficulty in finding a closed form expression of the average BER, we focus on the high signal-to-noise-ratio (SNR) analysis which generates simple analytical expressions. Then we derive new closed form expressions for the high-SNR performance of relay schemes under different design criteria, quantifying the performance in terms of a diversity gain and a coding gain. Monte-Carlo simulations show that our analytic work predicts accurately the diversity and coding gain.

In this paper, we propose a new design strategy based on the minimum mean-squared error (MMSE) in closed-loop non-regenerative multiple-input multiple-output relaying systems. Instead of conventional singular value decomposition based methods, we address the problem for joint MMSE design in a different approach using the Wiener filter solution which leads to simple derivations of the optimal MMSE designs. First, allowing the channel state information (CSI) at the source, we provide a new closed form solution for a source-relay-destination joint MMSE design by extending existing relay-destination joint MMSE designs. Second, for the limited feedback scenario, we address a codebook design criteria for the multiple streams preceding design with respect to the MMSE criterion. From our design strategy, we observe that compared to conventional non-regenerative relaying systems, the source or the destination only needs to know the CSI corresponding to its own link such as the source-to-relay or the relay-to-destination in view of the MMSE. Simulation results show that the proposed design gives about 7.5 dB gains at a bit error rate of 10-4over existing relay-destination joint MMSE schemes and we can get close to the optimal unquantized schemes with only a few feedback bits.

In this paper, as a extended structure of the existing relay-destination joint minimum mean square error (MMSE) design, we propose a new source-relay-destination joint MMSE design strategy allowing the channel state information (CSI) additionally at the source node. Instead of conventional singular value decomposition based methods, we address the problem for joint MMSE design in a different approach using the Wiener filter solution which leads to the simple derivation of the optimal MMSE design. From our design strategy, we also observe that compared to conventional non-regenerative relaying systems, the source or the destination only needs to know the CSI corresponding to its own link such as the source-to-relay or the relay-to-destination for minimizing the mean square error. Furthermore, numerical results show that the proposed design gives about 7.5 dB gains at a bit error rate (BER) of 10-4over existing relay-destination joint MMSE schemes.