This paper examines radio resource allocation in a full-duplex (FD) reconfigurable intelligent surface (RIS)-assisted wireless-powered (WP) industrial internet-of-Things (IIoT) communication network. The system model includes an FD access point (FD-AP) that communicates with FD energy harvesting (EH) mobile users (MUs), referred to as an FD-FD RIS-assisted WP-IIoT network. The FD-AP is equipped with two sets of multiple antennas: one set for downlink (DL) energy beamforming and another for uplink (UL) information signal reception. The FD-MUs have one antenna for DL energy signal reception and another for UL information transmission. This paper addresses the UL sum-rate maximization problem for the FD-FD RIS-assisted WP-IIoT system by jointly optimizing the RIS phase shift and power resources. Additionally, this paper presents two benchmarks as specific cases of the FD-FD RIS-assisted WP-IIoT system model, namely, (i) FD-HD RIS-assisted WP-IIoT network: FD AP and half-duplex (HD) two MUs groups, and (ii) HD-HD RIS-assisted WP-IIoT network: HD AP and HD MUs. The numerical results demonstrate that the FD-FD system outperforms both benchmarks in the low transmit power regime. Also, compared to the baseline non-RIS-assisted WP-IIoT network, the RIS-assisted WP-IIoT network achieved a significant UL sum-rate gain.

This paper investigates the sum spectral efficiency (SE) and total energy efficiency (EE) of the active reconfigurable intelligent surface (aRIS)-assisted cell-free (CF) massive multiple-input multiple-output (mMIMO) over temporal and spatially correlated channels. Multiple aRISs are deployed between numerous access points (APs) and mobile users to enhance the signals. The active reflective elements (REs) amplify and vary the signal phase. The continuously evolving channel creates a situation, where the channel differs during training and data transmission. We characterize the joint impact of multi-user interference (MUI), pilot contamination (PC), channel aging (CA), and active RIS noise amplification (RNA). The desired signal is enhanced as the reflected signal amplitude and REs per aRIS increase. However, the PC, MUI, CA, and RNA also grow– constraining the SE. Also, the network power consumption increases. An alternating optimization framework based on the weighted minimum mean square error and fractional programming is proposed to optimize the transmit power and reflection coefficients (RCs) with the objective of maximizing the sum SE. It is demonstrated that the number of APs and REs can be reduced by deploying aRISs. The proposed power and RC optimization algorithms considerably improves the sum SE. The trade-off analysis between the total EE and sum SE shows that the envelope of the operating region of the CF mMIMO is expanded by deploying multiple aRISs.

This paper investigates a full-duplex (FD) reconfigurable intelligent surface (RIS)-assisted wireless powered communication network (WPCN) in which FD multi-user (FD-MUs) industrial internet-of-things (IIoT) sensor devices with energy harvesting (EH) capabilities communicate with an FD hybrid-access point (FD-AP). The FD-AP with dual-set of multiple antennas use a set of antennas to beamform energy in downlink (DL) transmission and the other set of antennas to receive information signals in uplink (UL) transmission from the dual-set of single antenna FD-MUs. The FD-MUs use one single antenna to receive energy signals, while the other single antenna is used to transmit information. For comparison, two special cases of the FD-FD RIS-assisted WPCN IIoT network are considered. The first scenario considers an FD-HD (half-duplex) RIS-assisted WPCN IIoT network made up of a FD-AP and HD-MUs while the second comprises an HD-HD RIS-assisted WPCN IIoT network consisting of HD-AP and HD-MUs. We investigate the sum-rate performance of the FD-FD system with random IRS phase shifts and compare it to FD-HD and HD-HD system models. It is shown from simulation results that the FD-FD system outperforms the two special cases in the low transmit power regime.

This paper analyzes the spectral efficiency (SE) of an active reconfigurable intelligent surface (RIS)-aided cell-free (CF) massive multiple-input multiple-out (mMIMO). The aggregated channel estimate is derived and the achievable SE is obtained in closed-form by assuming imperfect channel state information. It is shown that the sum SE increases with the number of access points (APs) and reflecting elements (REs). The noise amplification due to active REs escalates the pilot contamination and impairs the sum SE. The active RIS offers higher sum SE than the passive RIS in the extreme scenarios of completely blocked and completely unblocked direct AP-user links.

This paper considers a full-duplex (FD) massive multiple-input multiple-output (mMIMO) system, where both the base station (BS) and user equipment (UE) are equipped with massive transmit antennas. Unlike conventional multi-user linear precoding that treats interference as noise, we integrate ratesplitting multiple access (RSMA), known for better interference management, and its power control policy with FD mMIMO for both uplink and downlink transmission. Assuming imperfect channel state information, closed-form expressions are derived for the achievable sum-rate for the proposed model. Numerical results show that the FD-RSMA demonstrates improved downlink and uplink achievable rates than the conventional multi-user linear precoding scheme.

Symbiotic radio networks (SRN) have gained traction for efficient spectrum usage in wireless communication Internet-of- Things networks (IoTNs) applications. Furthermore, the efficient use of energy resources under energy-efficient communication is rising in IoTNs to satisfy and attain the United Nations' sustainable development goals on sustainable and renewable energy usage. Hence, this work focuses on energy and spectrum efficient usage through renewable radio frequency (RF) energy harvesting (EH) backscatter (BC) communication (BackCom) and SRN between a secondary network sensor-equipped EH intelligent reflective surface BC and a primary network base station to multiple user equipment using multiple access communication. This work focuses on resource allocation optimization to maximize the system energy-efficiency quality-of-service for the SRN. The superiority of the proposed scheme over existing benchmark schemes is also presented in this work.

In this paper, we explore the potential of rate-splitting multiple access (RSMA) in a cell-free (CF) massive multiple-input multiple-output (MIMO) system integrated with low-resolution analog-to-digital converters (ADCs). Both the access points (APs) and the user equipment (UEs) deploy low-resolution ADCs. Thus, quantization noise (QN) limits the system’s performance. The limited coherence interval and the large number of users result in pilot contamination. This arises since multiple users may share the same pilot sequence in the uplink training. We investigate the spectral/energy efficiency (SE/EE) of an RSMA-enabled CF massive MIMO downlink transmission due to the robustness of RSMA against interference. We derive the closed-form SE expressions for the common and private streams which are shown to be exact when compared to Monte Carlo simulations. We optimize the combining weights of the common precoder to maximize the minimum user SE due to the common stream. It is shown that substantial SE gains and higher EE are achieved using the proposed algorithm in the presence of QN and imperfect channel state information. Our results emphasize that RSMA can be adopted to enhance the SE and EE while reducing the quantization bits.

This paper analyzes the spectral/energy efficiency (SE/EE) of a full-duplex (FD) cell-free (CF) massive multiple-input multiple-output (mMIMO) over Rician fading channels. Due to the FD radios, the access points (APs) suffer from self-interference (SI) and inter-AP interference (IAI) while the downlink (DL) users’ signals are corrupted by the uplink (UL) users’ transmissions. We consider the case, where low-resolution analog-to-digital converters (ADCs) are utilized at the APs and DL users, which introduces the quantization noise (QN). The combined effects of Rician$\kappa $-factor, residual SI/IAI, UL-to-DL interference, multi-user interference, and QN on the UL/DL SEs are characterized. The UL SE is degraded by the increase in DL power, whereas the growth in UL power deteriorates the DL SE. The effects of the residual SI/IAI and UL-to-DL interference are worsened by the low-resolution ADCs. We optimize the UL/DL transmit powers to maximize the overall sum SE of the network. It is observed that the proposed power allocation algorithm brings substantial sum SE gain. A trade-off analysis between the EE and SE, as a function of the ADCs’ resolution, shows that the entire envelope of the operating region of FD CF mMIMO is enhanced in Rician channels.

This brief presents a low-complexity I/Q (in-phase and quadrature components) imbalance calibration method for the transmitter using quadrature modulation. Impairments in analog quadrature modulator have a deleterious effect on the signal fidelity. Among the critical impairments, I/Q imbalance (gain and phase mismatches) deteriorates the residual sideband performance of the analog quadrature modulator degrading the error vector magnitude. Based on the theoretical mismatch analysis of the quadrature modulator, we propose a low-complexity I/Q imbalance extraction algorithm. After the parameter extraction, the transmitter is calibrated by imposing the counter imbalanced mismatch of the transmitter through the digital baseband. In comparison with existing I/Q imbalance calibration methods, the novelty of the proposed method lies in that: 1) only three spectrum measurements of the device-under-test are needed for extraction and calibration of gain and phase mismatches; 2) due to the blind nature of the calibration algorithm, the proposed approach can be readily applicable to an existing I/Q transmitter; 3) no extra hardware that degrades the calibration accuracy is required; and 4) due to the noniterative nature, the proposed method is faster and computationally more efficient than previously published methods.

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.

In this paper, we consider a decode-and-forward (DF) two-way relay (TWR) system in power line communication (PLC). The DF TWR employs physical- layer network coding (PNC). We derive analytic expressions for the average capacity and the outage probability of the system over a log-normal fading channel. Analytic results are verified through Monte Carlo simulations. From the results, the TWR is able to mitigate the half-duplex (HD) spectral efficiency loss incurred by one-way relaying. The impact of the impulsive noise on the system performance is also highlighted in the simulation results. It is shown that higher impulsive probability degrades system performance.

A study of a multi-hop decode-and-forward (DF) simultaneous wireless information and power transfer (SWIPT) sensor network system is presented in this work. In the studied system model, a source communicates with a destination through the aid of multi-hop relays which harvest energy from their received signals. We apply power splitting (PS) based SWIPT relaying protocols for the relays harvesting energy. Focused on DF relaying protocol, we aim to minimize the transmit power at the source under a set end-to-end throughput constraint by optimizing PS ratios at the relays. Based on convex optimization techniques, the globally optimal PS ratio solution is obtained as a closed-form solution. Numerical results demonstrate the efficacy of the proposed optimal design over the conventional fixed PS ratio scheme.

This article studies a multihop decode-and-forward (DF) simultaneous wireless information and power transfer (SWIPT) system where a source sends data to a destination with the aid of multihop relays which do not depend on an external energy source. To this end, we apply power splitting (PS)-based SWIPT relaying protocol so that the relays can harvest energy from the received signals from the previous hop to reliably forward the information of the source to the destination. We aim to solve two optimization problems relevant to our system model. First, we minimize the transmit power at the source under the individual quality-of-service (QoS) threshold constraints of the relays and the destination nodes by optimizing PS ratios at the relays. The second is to maximize the minimum system achievable rate by optimizing the PS ratio at each relay. Based on the convex optimization techniques, the globally optimal PS ratio solution is obtained in closed-form for both problems. By setting the QoS threshold constraint, the same for each node for the source transmit power problem, we discovered that either the minimum source transmit power or the maximum system throughput can be found using the same approach. Numerical results demonstrate the superiority of the proposed optimal SWIPT PS design over conventional fixed PS ratio schemes.

This brief presents a low-complexity I/Q (in-phase and quadrature components) imbalance calibration method for the transmitter using quadrature modulation. Impairments in analog quadrature modulator have a deleterious effect on the signal fidelity. Among the critical impairments, I/Q imbalance (gain and phase mismatches) deteriorates the residual sideband performance of the analog quadrature modulator degrading the error vector magnitude. Based on the theoretical mismatch analysis of the quadrature modulator, we propose a low-complexity I/Q imbalance extraction algorithm. After the parameter extraction, the transmitter is calibrated by imposing the counter imbalanced mismatch of the transmitter through the digital baseband. In comparison with existing I/Q imbalance calibration methods, the novelty of the proposed method lies in that: 1) only three spectrum measurements of the device-under-test are needed for extraction and calibration of gain and phase mismatches; 2) due to the blind nature of the calibration algorithm, the proposed approach can be readily applicable to an existing I/Q transmitter; 3) no extra hardware that degrades the calibration accuracy is required; and 4) due to the noniterative nature, the proposed method is faster and computationally more efficient than previously published methods.

Simultaneous wireless information and power transfer (SWIPT) is investigated in amplify-and- forward (AF) relay systems. Each relay node facilitates communication between a source node and a destination node. The relay nodes are equipped with radio frequency (RF) energy harvesters to supply power for retransmission of information signals from the source node to the destination node. In this paper, both power splitting (PS) ratio and adaptive power control are jointly optimized for optimal SWIPT multiple- relay systems performance. We demonstrate that the optimal power allocation strategy in joint optimization problem is to use full harvested power. We propose both an optimal centralized PS scheme and a distributed suboptimal scheme suitable for practical implementation. Simulation results demonstrate that the proposed schemes outperform naive PS schemes in terms of the average rate and the bit-error rate.

In this paper, we investigate simultaneous wireless information and power transfer (SWIPT) where a multi- antenna transmitter sends data and energy to single antenna receivers with a time switching (TS) circuit. In this system, a general joint TS protocol is introduced which includes conventional TS schemes as special cases. We aim to analyze the achievable rate region of the joint TS under energy harvesting constraint at the receivers by jointly optimizing the TS ratios and the transmit covariance matrices. To tackle non-convex rate region characterization problems, we first decouple the original problems into several subproblems with fixed auxiliary variables. Then, the globally optimal TS ratios and the transmit covariance matrices are computed via convex optimization techniques. Numerical examples verify the efficacy of the proposed joint TS over conventional methods.

In this paper, we investigate a wireless powered communication network (WPCN) protocol in which mobile stations (MS) with energy harvesting (EH) communicate with a full-duplex access point (FD- AP). The FD-AP is equipped with multiple antennas, while MSs have a single antenna and operate in half-duplex (HD) mode. The MSs are assigned two groups according to the time slot and their access channel state for either uplink or downlink communication with the FD-AP. Channel assignment, time resource allocation, and power allocation is jointly optimized for maximizing the sum-rate. An iterative algorithm based on the relationship between rate and minimum mean squared error (MMSE) is proposed to maximize the sum-rate by examining the Lagrangian problem. The proposed algorithm for FD-WPCN is compared to its HD counterpart. It is shown from simulation results that the proposed FD-WPCN scheme outperforms the HD mode when low transmit power is used although the FD-WPCN performance is degraded at high transmit power regime due to the presence of residual self- interference (RSI) at the FD-AP node.

This paper studies device-to-device wireless communications, where two energy-constrained Internet-of-Things (IoT) nodes, which do not have constant power supplies, wish to exchange their information with each other. Because of small form factor, the IoT nodes are normally equipped with simple energy storages, which might suffer from a high self-discharging effect. Therefore, the energy stored in each node would not be available after a few time duration. In this system, we investigate power splitting (PS)-based energy exchange methods by exploiting radio frequency (RF) wireless energy transfer techniques, and propose a new concept called wireless information and power exchange (WIPE). In this WIPE protocol, each node operates either in a transmit mode and a receive mode at each time slot. First, a transmit node sends the information signal to a receive node which utilizes a PS circuit for information decoding and energy harvesting. Then, the harvested energy of the receive node is stored in the energy storage. At the consecutive time slot, two nodes switch their operations, i.e., the receive node in the previous time slot now operates in a transmit mode which transfers RF signals by using the harvested energy. This procedure continues by changing the operations of two nodes at each time slot. For the proposed WIPE protocol, we provide two different PS ratio optimization schemes which maximize the weighted sum throughput performance according to the level of channel state information (CSI) knowledge. For the ideal full CSI case where the CSI for all time slots is known in advance, the globally optimal PS algorithm is presented by applying convex optimization techniques. Also, for a practical scenario where only the causal CSI is available, we propose an efficient PS optimization method which achieves performance almost identical to the ideal full CSI case. Simulation results verify that the WIPE protocol with the proposed PS optimization techniques performs better than conventional schemes.

This paper considers multiple-input single-output simultaneous wireless information and power transfer (SWIPT) broadcast channels (BCs) where a multi-antenna transmitter serves single antenna receivers each equipped with a time switching (TS) circuit for information decoding (ID) and energy harvesting (EH). To be specific, we study a scheme which jointly determines the time durations allocated for the ID and the EH modes at each receiver and the transmit covariance matrices at the transmitter. Then, we present a general joint TS protocol for the SWIPT BC which includes conventional TS schemes as special cases. In order to fully characterize the performance of the proposed joint TS systems, the achievable rate region is analyzed under EH constraint at the receivers. By applying the rate profile methods, we identify the optimal TS ratios and the optimal transmit covariance matrices which achieve the boundary points of the rate region. Then, the boundary points are obtained by solving the average transmit power minimization problems with individual rate constraints at the receivers. To solve these non-convex problems, the original problems are decoupled into subproblems with fixed auxiliary variables. Then, the globally optimal TS ratios and the transmit covariance matrices are computed by finding the optimal auxiliary variables via convex optimization techniques. Numerical results demonstrate that the proposed joint TS scheme outperforms conventional TS methods.

This paper considers point-to-point wireless communications where an energy-constrained node, which has insufficient energy for data transmission, wants to exchange messages with a node with enough energy. In this system, we study power splitting (PS) based energy cooperation methods by exploiting wireless energy transfer techniques and propose a new concept called sustainable wireless information and power exchange (SWIPE). In this SWIPE protocol, the node which has sufficient energy first transmits the information signal to the energy-constrained node. Then, the received signal at the energy-constrained node is utilized for both information decoding and energy harvesting via a PS circuit. At the consecutive time slot, by using the harvested energy, the energy- constrained node is now able to send a signal to the other node which employs a similar PS technique. This procedure continues by switching the operations of two nodes at each time slot. For the proposed SWIPE protocol, we present the optimal PS ratio computation algorithm in order to maximize the weighted sum throughput performance. Simulation results confirm the efficacy of the proposed SWIPE protocol over conventional schemes.

Heterogeneous networks (HetNets) which involves densifying a high powered macro cell (MC) with a number of low powered small cells (SCs), has been identified as key technology for 5G communication. This technology requires that MC is connected to SCs with high speed fiber optic cable for control and coordination. However connecting fiber links to all cells is expensive, labor intensive and less flexible. This paper proposes HetNet topology where massive MIMO with full-duplex (FD) provides wireless backhaul link for SCs. Communication is achieved in two phases. In the first phase, we assume cells in the HetNet are equipped with massive receive antennas and single transmit antennas whereas in the second phase a circulator switches massive antenna receivers into transmitters and single antenna transmitters into receivers. We derive accurate approximations for uplink/downlink (UL/DL) rate under the assumption of imperfect channel state information. Our results indicate that the strength of loop interference (LI) and SC-to-SC interference which occur due to FD operation depends largely on the number of SCs. By increasing the number of SCs, achievable rates also increase but requires more antennas to overcome the deleterious effects of LI and SC-to-SC interference.

This paper studies multi-user wireless powered communication networks, where energy constrained users scavenge energy of the radio frequency signals radiated from a hybrid access point (H-AP). The energy is then utilized for the users' uplink information transmission to the H-AP in time division multiple access mode. In this system, we aim to maximize the uplink sum rate performance by jointly optimizing energy and time resource allocation for multiple users. To this end, we first derive the optimal downlink energy transmission policy at the HAP. Based on this result, analytical resource allocation solutions are obtained. Simulation results confirm that the proposed algorithms offer significant sum rate performance gain over conventional schemes.

In simultaneous wireless information and power transfer (SWIPT) systems, dedicated energy signals only convey wireless energy, but not information. For this reason, the energy-carring signals in the SWIPT can be pre- determined in advance and is shared among communication nodes. By exploiting this nature, this paper designs the optimal transmit beamforming vectors for the multiple-input single-output SWIPT interference channel with signal cooperation (IFC-SC), where the energy- carrying signal waveforms are known to transmitters and receivers. Specifically, we aim to identify the optimal tradeoff between the information rate and the harvested energy. To this end, an information rate maximization problem is formulated under minimum required harvested energy constraint, which is non-convex in general. To solve the problem, a new parameterization technique is introduced, and we can decouple the original problem into two subproblems, which yields closed-form beamforming solutions by addressing the line search method for the parameter. Simulation results confirms that the proposed optimal IFC-SC beamforming vectors outperform conventional SWIPT IFC systems.

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.

This paper studies multiuser wireless powered communication networks, where energy constrained users charge their energy storages by scavenging energy of the radio frequency signals radiated from a hybrid access point (H-AP). The energy is then utilized for the users' uplink information transmission to the H-AP in time division multiple access mode. In this system, we aim to maximize the uplink sum rate performance by jointly optimizing energy and time resource allocation for multiple users in both infinite capacity and finite capacity energy storage cases. First, when the users are equipped with the infinite capacity energy storages, we derive the optimal downlink energy transmission policy at the H-AP. Based on this result, analytical resource allocation solutions are obtained. Next, we propose the optimal energy and time allocation algorithm for the case where each user has finite capacity energy storage. Simulation results confirm that the proposed algorithms offer about 30% average sum rate performance gain over conventional schemes.

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.

This paper investigates simultaneous wireless information and power transfer in multiple-input single-output interference channels, and designs transmit beamforming vectors which achieves the optimal tradeoff between the information rate and the harvested energy. To this end, the problem for maximizing the information rate is formulated with minimum required harvested energy constraint. In order to solve this nonconvex problem, we introduce parameterization techniques for characterizing the achievable rate- energy (R-E) region. As a result, the original problem is separated into two subproblems, for which closed- form solutions are obtained by addressing the line search method. Finally, we provide numerical examples for the achievable R-E region through simulations.

In this paper, we focus on maximizing weighted sum energy efficiency (EE) for a multi-cell multi-user channel. In order to solve this non-convex problem, we first decompose the original problem into a sequence of parallel subproblems which can be optimized separately. For each subproblem, a base station employs dirty paper coding to maximize the EE for users within the cell while regulating interference induced to other cells. Since each subproblem can be transformed to a convex multiple-access channel problem, the proposed method provide a closed-form power allocation. Then, based on the optimal covariance matrix, a locally optimal solution is obtained to maximize the sum EE. Finally, simulation results show that our algorithm based on the non-linear precoding achieves close to 20 percent gain than the conventional linear precoding method.

We address a new robust optimization problem in a multiuser multiple-input single-output broadcasting system with simultaneous wireless information and power transmission. Assuming that perfect channel- state information (CSI) for all channels is not available at the BS, the uncertainty of the CSI is modeled by an norm-bounded uncertainty set. To optimally design transmit beamforming weights and receive power splitting, an average total transmit power minimization problem is investigated subject to the individual harvested power constraint and the received signal-to-interference-plus-noise ratio constraint at each user. The original design problem is reformulated to a relaxed semidefinite program, and then two different approaches based on convex programming are proposed, which can be solved efficiently by the interior point algorithm. Interestingly, we show that the semidefinite relaxation (SDR) is tight. Numerical results are provided to validate the robustness of the proposed algorithms.

In this paper, we investigate a multiuser downlink distributed antenna system with simultaneous wireless information and power transmission under the assumption of imperfect channel state information at the distributed antenna (DA) port. To optimally design robust transmit beamforming vectors and receive power splitting factors, our design objective is to maximize the average worst-case signal-to-interference-plus-noise ratio while simultaneously achieving the individual energy harvesting (EH) constraint for each user and the per-DA port power constraint. We solve this non- convex problem by reformulating it into a two-stage problem. Simulation results are shown to validate the robustness and effectiveness of the proposed algorithms.

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.

This paper investigates the optimal transmit beamforming designs for simultaneous wireless information and power transfer (SWIPT) in multiple-input single-output interference channels (IFC). Based on cooperation level among transmitters and receivsers, we classify the SWIPT IFC systems into two categories. First, we consider the IFC with partial cooperation, where only channel state information (CSI) is available at transmitters and receivers, but not the signal waveform. Second, we examine the IFC with signal cooperation, where both the CSI and the signal waveforms are known to transmitters and receivers. Then, for the both scenarios, we identify the Pareto boundary of the achievable rate-energy (R-E) region which characterizes the optimal tradeoff between the information rate and the harvested energy. To this end, the problems for maximizing the information rate are formulated with minimum required harvested energy constraint. To solve these non-convex problems, we introduce parameterization techniques for characterizing the R-E region. As a result, the original problem is separated into two subproblems, for which closed-form solutions are obtained by addressing the line search method. Finally, we provide numerical examples for the Pareto boundary of the R-E region through simulations.

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 propose new precoding methods for two-way multiple input multiple output physical network coding (PNC) systems which employ the modulo operation. In our work, the transmit and receive filters are determined to maximize the minimum distance of the received constellations assuming global channel state information. The precoding operations are separately optimized for the multiple access (MA) and the broadcast stages, and the optimal precoding is obtained by applying a semidefinite relaxation method. Especially, we prove that for the system with linear detection the modulo operation for the PNC achieves optimality with the derived precoding for the MA stage in terms of the minimum distance. Also, we present a closed-form solution for the optimal filter designs for two special cases. For computing solutions, we transform our max min problem into a simple maximization problem by imposing additional constraints. Also, we propose a suboptimal non-iterative precoding scheme whose performance is within 1 dB at a bit error rate (BER) of 10-4compared to the optimum iterative method with much reduced complexity. Finally, the simulation results show that the proposed systems achieve 2-3 dB gains at a BER of 10-4compared to the optimal amplify-and-forward systems.

In this paper, we study K-user multiple-input multiple-output (MIMO) interference channels (IC) in the presence of antenna correlations. Although interference alignment (IA) achieves the maximum multiplexing gain, i.e., degrees of freedom (DOF), the actual performance is degraded due to ill-conditioned channels caused by the antenna correlations. To enhance the overall system performance, we thus consider a transmission mode selection scheme which adaptively determines the number of data streams at each transmitter-receiver pair in a distributed fashion using local channel state information (CSI). A filter update process is exploited in order to estimate the performance regarding each transmission mode successively by considering the actual channel conditions as well as signal-to-noise ratio (SNR). Simulation results show that our mode selection scheme enhances the sum rate performance compared to the conventional full data stream transmissions in spatially correlated MIMO IC.

In this paper, we propose an accurate link performance abstraction technique for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing systems with maximum likelihood (ML) receiver. The performance of ML detection (MLD) is estimated by using capacity bounds of two simple linear receivers. To this end, we give a simple parametrization to compute the desired per-stream signal-to-noise ratio (SNR) values, which can be applied for both vertically and horizontally coded MIMO systems. Based on the per-stream SNR estimates, the block error rate performance for each encoding block is finally obtained using the received-bit information rate metrics. From extensive simulations, we verify that the proposed method is accurate in the MIMO-MLD link evaluation with very low computational complexity.

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.

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 study single cell multi-user downlink distributed antenna systems (DAS) where antenna ports are geographically separated in a cell. First, we derive an expression of the ergodic sum rate for the DAS in the presence of pathloss. Then, we propose a transmission selection scheme based on the derived expressions which does not require channel state information at the transmitter. Utilizing the knowledge of distance information from a user to each distributed antenna (DA) port, we consider the optimization of pairings of DA ports and users to maximize the system performance. Based on the ergodic sum rate expressions, the proposed scheme chooses the best mode maximizing the ergodic sum rate among mode candidates. In our proposed scheme, the number of mode candidates are greatly reduced compared to that of ideal mode selection. In addition, we analyze the signal to noise ratio cross-over point for different modes using the sum rate expressions. Through Monte Carlo simulations, we show the accuracy of our derivations for the ergodic sum rate. Moreover, simulation results with the pathloss modeling confirm that the proposed scheme produces the average sum rate identical to the ideal mode selection with significantly reduced candidates.

Link adaptation allows a communication system to adapt its transmission modes according to channel conditions. Although a maximum likelihood (ML) receiver for multiple-input multiple-output (MIMO) systems provides optimal performance, estimating its link performance has been a difficult problem. In this paper, we propose a new link performance abstraction technique for MIMO orthogonal frequency-division multiplexing systems with the ML receiver. The performance of ML detection (MLD) is estimated by employing capacity bounds of two simple linear receivers. Then, we give a simple parametrization to compute the desired per-stream signal-to-noise ratio (SNR) values, which can be applied for both vertically and horizontally coded MIMO systems. Based on the derived per-stream SNR estimates, the block error rate is obtained using the received-bit information rate metrics. We also examine the effect of imperfect channel estimation as well as spatial correlations among antennas. Finally, extensive simulation results show that the proposed method provides superior estimation accuracy in the MIMO-MLD link evaluation with very low computational complexity.

In this paper, we propose precoding methods for multiple input multiple output physical network coding systems, which employ the modulo operation. In our work, the transmit and receive filters are determined to maximize the minimum distance on the received constellations. Especially, to address non-concavity of the given problems, we change our problem into a concave one which can be optimized by an iterative method. Also, we propose a suboptimal non-iterative scheme whose performance is very close to the optimum iterative method. In our derivations, we prove that the modulo operation achieves the optimality in terms of the minimum distance. Finally, it is confirmed from the simulation results that the proposed systems outperform conventional schemes in terms of the error performance.

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 develop linear precoding methods for cognitive radio (CR) multi-user multiple-input multiple-output (MU-MIMO) broadcast systems where unlicensed secondary users (SUs) simultaneously use the same spectrum of the licensed primary user (PU). When the zero-forcing block diagonalization (ZF-BD) precoder is extended to the CR network, a noise enhancement problem occurs. Therefore, we propose a regularized BD precoder based on the minimum mean-square error (MMSE) criteria subject to zero interference constraint for the PU. As a result, the proposed MMSE-BD scheme improves the signal-to-interference-plus-noise ratio at each SU's receiver compared to the ZF-BD based method. Simulation results demonstrate that the proposed algorithm outperforms the ZF based technique by more than 5 dB at the sum-rate 10 bps/Hz for CR MU-MIMO downlink systems.

This paper investigates the achievable rate region of two-way amplify-and-forward (AF) relaying systems with multiple relays, where all nodes are equipped with multiple antennas. First, we find linear processing filters to optimize the weighted sum-rate for the two-way channels with sum power constraints. The proposed algorithm achieves the maximum weighted sum-rate by deriving the gradient expressions and iteratively applying the gradient descent method. Consequently, the proposed scheme outperforms the conventional methods in terms of the weighted sum-rate. Also, the achievable rate region is obtained by adjusting the weights in the proposed algorithm. It is observed from the ergodic rate region that channel reciprocity can improve the achievable sum-rate in two-way relay systems unlike one-way channels.

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 consider a multipoint-to-multipoint transmission system which employs a single relay in wireless networks where all source, destination and relay nodes are equipped with multiple antennas. For amplify-and-forward relay systems, we propose new linear processing strategies for maximizing the sum rate performance by applying a blockwise relaying method combined with convex optimization techniques. To reduce a computational complexity, we first consider a zero-forcing based relay only optimization scheme, which generate a closed-form solution in a non-iterative fashion. In order to further improve the sum rate at low signal-to-noise ratio regimes, we additionally design an enhanced relay filter by exploiting the blockwise relaying method based on a minimum mean-square error criterion. Simulation results show that the proposed relay design strategies outperform the existing conventional schemes in terms of the sum rate.

In this paper, we present a linear precoder design for cognitive radio (CR) multi-user multiple-input multiple-output (MU-MIMO) downlink systems where unlicensed secondary users (SUs) can simultaneously utilize the same spectrum used by a licensed primary user (PU). Although a zero-forcing block diagonalization (ZF-BD) precoder is extended to the CR network with the PU, a transmit power boost problem occurs. Therefore, we propose a regularized BD precoder method based on the minimum mean-squared error (MMSE) criteria subject to the interference power constraint under a predetermined threshold for the PU. As a result, the proposed CR-MMSE-BD scheme improves the signal-to-interference-plus-noise ratio at each SU's receiver, compared to the ZF-BD based method. The simulation results demonstrate that the proposed algorithm outperforms the ZF based technique for CR MU-MIMO downlink systems.

In multiuser multiple-input multiple-output (MIMO) downlink systems, orthogonal space division multiplexing (OSDM) techniques have been studied to approach the optimum performance of dirty paper coding with low complexity. Assuming a large number of users in the multiuser system, a proper user scheduling is needed to utilize the OSDM. In addition, the performance of the chosen users can be maximized by properly configuring the numbers of data streams, or the transmission modes. In this paper, we propose a joint user and mode selection algorithm which approaches the performance of the exhaustive search with significantly lower complexity. To this end we first decompose the sum rate into the sum of the individual rates, and derive an upper bound of each individual rate. By utilizing the obtained upper bound, the user and mode subset is determined to maximize the sum rate. Comparing with other conventional low-complexity schemes, the proposed scheme requires much lower complexity especially when the number of users is large. For example, our method achieves a complexity reduction of 92% compared to the conventional scheme when the number of users is 25. Simulation results show that our method achieves more than 95% of the sum rate of the exhaustive search.

In this paper, we analyze asymptotic ergodic capacity of multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems with channel state information (CSI) at the relay. By exploiting the asymptotic results for eigenvalue distributions, we derive the ergodic capacity in various asymptotic antenna regimes as a closed-form expression with arbitrary system parameters. The analyzed results demonstrate that increasing the number of source antennas causes the capacity shrink phenomenon which is analogous to the channel hardening effect in multi-user MIMO systems. Although we assume asymptotically large antennas to obtain the closed-form expressions, simulation results show that our derived expressions are surprisingly accurate even with the moderate number of antennas, and thus can serve for analyzing practical MIMO relay networks.

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 letter, we analyze asymptotic ergodic capacity of MIMO amplify-and-forward (AF) relaying systems which employ linear processing at the relay. By exploiting the asymptotic results for eigenvalue distributions, we derive the ergodic capacity in various asymptotic antenna regimes as a closed-form expression with arbitrary system parameters. The analyzed results demonstrate that increasing the number of source antennas causes the capacity shrink phenomenon which is analogous to the channel hardening effect in multi-user MIMO systems. Although we assume asymptotically large antennas to obtain the closed-form expressions, simulation results show that our derived expressions are surprisingly accurate even with the moderate number of antennas, and thus can serve for analyzing practical MIMO relay networks.

This paper considers both one-way and two-way relaying systems with multiple relays between two terminal nodes where all nodes have multiple-input multiple-output (MIMO) antennas. We propose a unified algorithm which computes the optimal linear transceivers jointly at the source node and the relay nodes for amplify-and-forward (AF) protocols. First, optimization designs based on the sum-rate and the mean-square error (MSE) criteria are formulated for the two-way AF relaying channel. Due to non-convexity of the given problems, the proposed schemes iteratively identify local-optimal source and relay filters by deriving the gradients of the cost functions for a gradient descent algorithm. Then, the proposed algorithm can optimize a one-way multiple relay system as a special case of the two-way channel. Finally, we prove the global optimality of the maximum sum-rate scheme under an asymptotically large antenna assumption. From simulation results, it is confirmed that the proposed methods yield the near optimum result for the MIMO multiple relay channel even with a moderate number of antennas. Consequently, we show that the proposed algorithm outperforms conventional schemes in terms of the sum-rate and the error performance for both one-way and two-way protocols.

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.

This paper studies linear precoding and decoding schemes for K-user interference channel systems. It was shown by Cadambe and Jafar that the interference alignment (IA) algorithm achieves a theoretical bound on degrees of freedom (DOF) for interference channel systems. Based on this, we first introduce a non-iterative solution for the precoding and decoding scheme. To this end, we determine the orthonormal basis vectors of each user's precoding matrix to achieve the maximum DOF, then we optimize precoding matrices in the IA method according to two different decoding schemes with respect to individual rate. Second, an iterative processing algorithm is proposed which maximizes the weighted sum rate. Deriving the gradient of the weighted sum rate and applying the gradient descent method, the proposed scheme identifies a local-optimal solution iteratively. Simulation results show that the proposed iterative algorithm outperforms other existing methods in terms of sum rate. Also, we exhibit that the proposed non-iterative method approaches a local optimal solution at high signal-to-noise ratio with reduced complexity.

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.

In this paper, we propose a linear preceding and decoding scheme maximizing the sum rate of abuser interference channel systems where each node has multiple antennas. With an iterative approach, the preceding matrices are identified by deriving the gradient of the sum rate and applying the gradient descent method. Due to non-convexity of the formulated problem, the proposed precoder cannot guarantee the global optimal solution, and a locally maximized sum rate can be found by the proposed precoding scheme. Then, we obtain the single-symbol decodable receiver from the modified minimum mean-squared error filter. From simulation results, we exhibit a local optimal sum rate of the interference channel systems with the proposed method. Also, we demonstrate that the proposed algorithm outperforms other existing methods in terms of the sum rate.

It was shown by Cadambe and Jafar that the interference alignment (IA) algorithm achieves the theoretical bound on degrees of freedom (DOF) for interference channel systems. However, since this method addresses the precoder design problem from the DOF point of view, some optimization processes are additionally needed in order to improve the sum rate performance. In this paper, based on the IA method, we propose a two-stage optimization of the precoding and decoding matrices in the interference channels. Simulation results show that the proposed method significantly improves the sum rate of the conventional IA scheme while maintaining the optimality of the DOF.

In this paper, we consider a relay system in multiple-input multiple-output (MIMO) multi-user channels where a single MIMO relay is engaged in communication between multiple source-destination terminal pairs. We propose two amplify-and-forward (AF) relaying schemes which maximize the sum-rate for the interference channel with multiple source-destinations. First, we introduce an iterative scheme which provides a local optimal solution. The proposed scheme iteratively searches an optimum relay matrix by deriving the gradient of the sum-rate and applying the gradient descent algorithm. Next, in order to reduce the computational complexity of the iterative scheme, we propose a block diagonalization (BD) method which utilizes the minimum mean-square error (MMSE) criterion with singular value decomposition (SVD) based rate maximization. Simulation results show that the proposed iterative scheme achieves a near-optimal sum-rate for the given channel model, and the MMSE based BD with the rate maximization approaches the local optimal sum-rate at high signal-to-noise ratio (SNR) regime.

Adaptive modulation and coding (AMC) is a powerful technique to enhance the link performance by adjusting the transmission power, channel coding rates and modulation levels according to channel state information. In order to efficiently utilize the AMC scheme, an accurate signal-to-noise ratio (SNR) value is normally required for determining the AMC level. In this paper, we propose a simple method to represent the SNR values for maximum likelihood (ML) detector in multi-input multi-output (MIMO) systems. By analyzing the relation between the upper bound and the lower bound of the ML detector performance, we introduce an efficient way to determine the SNR for the ML receiver. Based on the proposed SNR representation, an AMC scheme for single antenna systems can be extended to MIMO systems with ML detector. From computer simulations, we confirm that the proposed SNR representation allows us to achieve almost the same system throughput as the optimum AMC systems in frequency selective channels with reduced complexity.

This paper considers two-way relaying systems with a multiple-input multiple-output (MIMO) relay between two MIMO terminal nodes. The two-way relaying protocol can enhance the spectral efficiency compared with the one-way protocol by compensating the loss from half-duplex signaling. In this paper, we propose an iterative scheme to find a relay weighting matrix maximizing the sum-rate for two-way relay channels. Due to the non-convexity of the given problem, the proposed scheme iteratively identifies a local optimal solution by deriving the gradient of the sum-rate and applying the gradient descent algorithm. Simulation results show that the proposed iterative scheme with provable convergence achieves a near-optimal sum- rate for the two-way MIMO relay channels. Also, we show that the proposed scheme with a few iterations still outperforms the conventional schemes.

This paper considers amplify-and-forward (AF) relaying systems with multiple relay nodes between the source and the destination node, where all nodes are equipped with multiple antennas. Using multiple relay nodes to transmit a message, a distributed diversity gain can be obtained. In this paper, we address the optimization problem of relay weighting matrices which minimizes the mean-square-error (MSE). For general relaying systems which have an arbitrary number of relay nodes, the given problem has a non-convex cost function. Thus, we propose an iterative scheme which identifies a local optimal relay precoder by deriving the gradient of the MSE and applying the gradient descent algorithm. Simulation results show that the proposed iterative scheme outperforms the conventional schemes for multiple MIMO relay systems with a small number of iterations in terms of both the MSE and the bit error rate.

In this paper, we develop a minimum mean-squared error (MMSE) based block diagonalization (BD) algorithm for multiuser multi-input multi-output (MIMO) broadcast systems where each user has more than one antenna in the presence of other cell interference (OCI). Unlike the conventional BD based multiuser MIMO transmission schemes which suffer from the noise enhancement problem as eliminating all multi-user interference (MUI) completely, the proposed scheme attempts to suppress the MUI with a consideration of the OCI plus noise and employs an additional residual interference suppression process based on an MMSE criterion. As a result, the proposed scheme improves the signal-to-interference-plus-noise ratio (SINR) at each user's receiver compared to conventional BD based schemes. Simulation results demonstrate that the sum rate performance of the proposed algorithm is always better than that of the conventional BD based algorithms for various OCI configurations.

Adaptive modulation and coding (AMC) is a powerful technique to enhance the link performance by adjusting the transmission power, channel coding rates and modulation levels according to channel state information. In order to efficiently utilize the AMC scheme, an accurate signal-to-noise ratio (SNR) value is normally required for determining the AMC level. In this paper, we propose a simple method to represent the SNR values for maximum likelihood (ML) detector in multi-input multi-output (MIMO) systems. By analyzing the relation between the upper bound and the lower bound of the ML detector performance, we introduce an efficient way to determine the SNR for the ML receiver. Based on the proposed SNR representation, an AMC scheme for single antenna systems can be extended to MIMO systems with ML detector. From computer simulations, we confirm that the proposed SNR representation allows us to achieve almost the same system throughput as the optimum AMC systems in frequency selective channels with reduced complexity.

In this paper, we investigate the transceiver design for coded multiple-input multiple-output (MIMO) systems assuming channel knowledge at both transmitter and receiver. First we derive an expression of the diversity order of singular value decomposition (SVD) based systems with arbitrary channel coding configurations. Motivated by this analysis, we propose a blockwise design based on uniform channel decomposition (UCD) which utilizes a successive interference cancellation (SIC) receiver. To eliminate error propagation inherent in the SIC structure, the proposed scheme applies the UCD precoder for a pair of subchannels to achieve single-symbol decodable maximum likelihood detection (MLD) instead of the SIC receiver. From the analysis, we demonstrate that the proposed scheme has an enhanced diversity order compared to the SVD scheme by exploiting the feature of the UCD. Also, in the presence of imperfect channel knowledge at the transmitter, we describe an appropriate receive filter design for the proposed scheme. The simulation results show that the proposed transceiver technique outperforms both the SVD scheme and the conventional UCD by about 6 dB in 4 by 4 MIMO systems at the spectral efficiency of 12 bps/Hz.

When channel state information (CSI) is available at both transmit and receive sides, singular value decomposition (SVD) converts the MIMO channel into parallel subchannels. It is well-known that the diversity gain of the SVD scheme is limited by the subchannel gain with the smallest singular value. The SVD scheme can be combined with error correcting codes to compensate for the performance loss due to the smallest subchannel gain. In this paper, we provide the analysis of the diversity order for coded SVD schemes with arbitrary system configurations. When utilizing channel coding of code rate Rcfor systems which transmit N streams with Nttransmit and Nrreceive antennas, the maximum diversity order of the coded SVD schemes is derived as (Nt- lceilN . Rcrceil +1)(Nr- lceilN . Rcrceil +1). This analysis result shows that there is a tradeoff of the code rate and the diversity order in the coded SVD scheme and provides an insight for code design.

In this paper, we investigate spatial multiplexing schemes for closed-loop multiple-input multiple-output (MIMO) systems. The performance of the singular value decomposition (SVD) scheme is limited by the smallest singular value. When all the subchannels are utilized, uniform channel decomposition (UCD) was recently proposed to obtain a performance gain by making subchannels have equal gains. The UCD requires a successive interference cancellation (SIC) receiver, and thus it suffers from the error propagation inherent in the SIC receiver. We propose the blockwise UCD (BL-UCD) scheme which increases the minimum subchannel gain by pairing two singular values. The proposed scheme allows single-symbol decodable maximum-likelihood detection (MLD) instead of the SIC receiver. The simulation results demonstrate that the proposed BL-UCD scheme outperforms the SVD scheme and the conventional UCD at full spatial multiplexing for four transmit antennas and four receive antennas by 8 dB and 5 dB, respectively.

In this paper, we propose a new transmit diversity technique for multiple-input multiple-output (MIMO) systems to improve the link level performance of open-loop systems over flat fading channels. By cyclically applying a predetermined set of precoding weight vectors, artificially induced fluctuation is created to achieve additional diversity gain in flat fading channels. To design the set of the precoding vectors, we exploit the knowledge on the distribution of near optimum precoding vectors observed in a beamforming scheme based on the rotation transformations. Simulation results demonstrate that the proposed open-loop diversity scheme with an arbitrary number of transmit antennas achieves a full diversity gain with computational complexity comparable to a single-input single-output (SISO) system.