In this paper, we propose a novel, energy-efficient directional modulation scheme to enhance the physical-layer security of wireless communication systems. The proposed analytical method designs a uniform linear array (ULA) in the spatial frequency domain, allowing for arbitrary distortion of the constellation pattern. In the secure directions, the design ensures low bit error rates (BERs), while in unsecure angles, it enforces a threshold BER to disrupt potential eavesdroppers. The proposed scheme is not only simple to design but also provides flexible trade-off between the mainlobe and sidelobes, ensuring efficient energy consumption. Furthermore, we show that the new scheme has low computational complexity when optimizing antenna weightings, and while we only consider 4- and 16-QAM in this paper, the proposed method can be generalized to higher order QAM modulation schemes. Numerical results validate the effectiveness of the design in achieving the desired BER thresholds and energy efficiency, demonstrating its suitability for real-world applications.

In this work, we propose a joint security approach based on physical layer security (PhySec) and noisy ciphertext to improve the secrecy rate of a relay network with cooperative jamming via two trusted relays. While the secrecy capacity has been considered as the maximum limit for a perfect secrecy at the physical layer, we demonstrate that the consideration of error- prone ciphertext in encryption and its interaction with PhySec allows us to transmit above the PhySec capacity without any leakage. By formulating and solving a non-convex encryption- aided secrecy rate maximization problem, it is shown that beyond PhySec capacity performances can be achieved even in a simple jamming scenario in which the two jammers just send independent jamming signals. The optimal encryption-aware power allocation and the secrecy rate maximization solution are also established in the case of common jamming signals to further increase the secrecy rate. Numerical results are finally provided to demonstrate the superiority of the proposed joint security framework over traditional PhySec.

In traditional physical layer security paradigm, no leakage of confidential information to the eavesdropper is tolerated regardless of whether the message is encrypted or not. This will result in an achievable secure transmission rate that is significantly smaller than the channel capacity. This article presents a novel approach that allows treatment of physical layer security in conjunction with encryption to achieve a flexible trade-off of system resources. We propose a novel framework to model the interplay between secured transmission rate and error probability in error prone ciphertexts. To this end, we use the concept of rate-equivocation region to establish such a connection. To clearly describe the application of our framework, we consider the case of 4-node Gaussian wiretap channel. For such a channel, we characterize the rate-equivocation region in different scenarios, and then use it to study the achievable rate of encryption-aware physical layer security. The obtained results show that, for a fixed transmission power, the prior knowledge of encryption can significantly increase the secured transmission rate. In addition, encryption-aware physical layer security can achieve a target transmission rate at a reduced transmission power compared to the conventional encryption-agnostic physical layer security.

In this paper, we investigate a trellis-coded space shift keying modulation scheme, called trellis-coded space-time shift keying (TC-STSK), which combines trellis-coded modulation with space shift keying. By analyzing the rank criterion using a graph theoretic approach, we maximize the number of unique differences between pairwise codewords as the code design goal. We discuss the code design principles for achieving diversity, and propose a design algorithm that is mostly suitable for rate-1/n codes, where n is the number of the code output bits. We then propose a diversity adaptation mechanism by selecting only the codewords with desired diversity, and use it to design higher rate codes that achieve full diversity. We also provide the code designs and a modified soft Viterbi decoder for such schemes. Simulation results show that the proposed scheme can achieve diversity orders expected from the theoretical analysis, and that increasing the number of shift registers and transmit antennas improves the performance of the TC-STSK scheme. The results also show that TC-STSK outperforms a space-time trellis code with the same bit rate and the number of shift registers.

We derive the asymptotic ergodic secrecy sum rate (ESSR) of block diagonalization precoding for physical-layer security in downlink multi-user wireless networks that use artificial noise. First, we derive the ESSR of the system. Then, we derive the power allocation and the asymptotic ESSR as the number of antennas increases. After, we derive an approximate expression for the optimum ratio of the number of transmit antennas to the number of receive antennas (Ψ). We then introduce the user dropping factor (UDF) as a means to derive the optimum number of users in the system under different scenarios and then derive the asymptotic optimum UDF, which gives the optimum number of scheduled users. We also study the effect of imperfect channel state information and derive a closed-form ESSR. Simulation results show that these precoders outperform channel inversion (CI) and regularized CI schemes in terms of the ESSR at all SNRs. We also show that as the number of receive antennas of each user increases, the asymptotic ESSR gap also increases.

We derive the asymptotic secrecy sum-rate of block diagonalization (BD) precoding for physical layer security in downlink multi-user wireless networks using artificial noise (AN). We first derive the secrecy sum-rate assuming that the channel of the eavesdropper is not known at the transmitter and then the asymptotic secrecy sum-rate is derived. The optimum power allocation for asymptotic secrecy sum-rate is derived after that. Simulation results show that the proposed precoders outperform channel inversion (CI) and regularized channel inversion (RCI) schemes in terms of the secrecy sum-rate at all SNRs. We also show that as the number of receive antennas of each user increases, the sum-rate gap between the proposed scheme and existing methods increases.

This paper presents a novel compressive sensing (CS) framework for recording of electrically evoked brain dopamine levels using fast-scan cyclic voltammetry (FSCV) at a carbon-fiber microelectrode (CFM). This approach utilizes the discrete cosine transform (DCT) as the sparsifying domain for the background-subtracted faradaic (dopamine) currents, along with the block sparse Bayesian learning (BSBL) algorithm for signal reconstruction. Furthermore, basic FSCV processing steps such as background current averaging and in situ background current subtraction in each FSCV scan can be directly performed with compressed measurements. The effectiveness of the approach is demonstrated using previously recorded dopamine concentration changes from the dorsal striatum of an anesthetized laboratory rat that are evoked via electrical stimulation of the medial forebrain bundle (MFB). Specifically, the proposed framework can reconstruct the brain dopamine dynamics and their associated cyclic voltammograms with a high degree of fidelity (correlation coefficients of >0.97) for a compression ratio, CR, value as high as ~5.

This paper investigates the energy efficiency of communication channels subject to additive Gaussian mixture interference in the low-power regime. This channel is widely used to capture the asynchronism in heterogeneous cellular networks. In particular, we characterize the low-signal-to-noise-ratio (low-SNR) metrics of minimum energy per bit or capacity per unit cost and the wideband slope of the spectral-efficiency curve. Instead of directly maximizing the mutual information or determining the optimal input, we make use of the characterization that the first derivative of the capacity with respect to SNR at SNR= 0 can be determined from the Kullback-Leibler divergence without identifying the optimal input. We also identify the wideband slope of spectral efficiency in closed-form by relying on the discreteness in amplitude of the capacity-achieving input. The characterization of these fundamental energy efficiency metrics allows us to find the signaling strategies that are optimally efficient in the low-SNR regime and obtain an analytical confirmation of the earlier information-theoretic findings.

We study the application of spatial modulation (SM) in overlay cognitive radio (CR) networks, in which the primary and secondary networks work concurrently over the same spectrum band. We assume that the direct link between the primary transmitter and receiver is not available, i.e. broken, and that the CR transmitter assists the primary network as a relay to amplify-and-forward the transmitted symbols of the primary. SM is used in the secondary to split the transmission space into two amplitude-phase modulation (APM) and spatial domains. In the proposed scheme, the secondary transmitter retransmits the primary symbols in APM domain, while its own information is transmitted by the index of transmitting antenna, similar to space shift keying, without causing any interference to the primary receiver. We analyze the performance of the optimal detectors at both the primary and secondary receivers for the case of phase shift keying modulation in terms of the average symbol error rate (ASER). We also study the asymptotic behavior of the ASER at both the primary and secondary at high signal-to-noise ratios. Simulation results show that the SM can be effectively used in overlay CR systems.

This paper presents a comprehensive performance analysis of full-duplex multiuser relay networks employing opportunistic scheduling with noisy and compressive feedback. Specifically, two feedback techniques based on compressive sensing (CS) theory are introduced and their effect on the system performance is analyzed. The problem of joint user identity and signal-to-noise ratio (SNR) estimation at the base-station is casted as a block sparse signal recovery problem in CS. Using existing CS block recovery algorithms, the identity of the strong users is obtained and their corresponding SNRs are estimated using the best linear unbiased estimator (BLUE). To minimize the effect of feedback noise on the estimated SNRs, a backoff strategy that optimally backsoff on the noisy estimated SNRs is introduced, and the error covariance matrix of the noise after CS recovery is derived. Finally, closed-form expressions for the end-to-end SNRs of the system are derived. Numerical results show that the proposed techniques drastically reduce the feedback air-time and achieve a rate close to that obtained by scheduling techniques that require dedicated error-free feedback from all network users. Key findings of this paper suggest that the choice of half-duplex or full-duplex SNR feedback is dependent on the channel coherence interval, and on low coherence intervals, full-duplex feedback is superior to the interference-free half-duplex feedback.

In this paper, the performance of suboptimal detection of spatial modulation (SM) based on the so-called maximum ratio combining (MRC) is investigated. In this detection scheme, in contrast to maximum likelihood (ML) detection, transmit antenna index and amplitude-phase modulation(APM) symbols are detected separately in two stages. Therefore, the detection complexity of SM can be significantly reduced. We analyze the instantaneous and average symbol error rate (SER) of such a detection scheme and compare it with that of the optimal ML detection. Also, we propose an adaptive space modulation scheme to minimize the SER of MRC detection by utilizing the channel state information. Finally, the problem of constellation breakdown of SM in the presence of the MRC detection for the special case of the phase-shift keying (PSK)-modulated SM is investigated. The derived analytical results are further validated using extensive simulations.

A layered spatial modulation (LSM) scheme is proposed for the downlink of multiuser wireless communication systems. The proposed scheme falls in the class of the well-known point-to-point SM as it employs only one antenna in each transmission interval. However, it is designed based on assigning different sets of transmit antennas, rather than single antenna elements, to transmit different symbols of each user. We first study the error performance of the proposed LSM. In order to improve the overall error performance of the system, we employ a graphical approach to adaptively allocate antennas to different users. We also propose some techniques to increase the spectral efficiency of LSM. Extending the proposed method to the generalized LSM, we also compare the maximum transmission rate of the proposed scheme with that of the existing SM-based multiuser schemes, and show that this technique can significantly improve the spectral efficiency of the SM-based multiuser communications.

Abstract We propose two novel clustered linear precoding schemes applicable to network multi‐input multi‐output systems using only partial channel state information to enhance the sum‐rate of the system. Using a channel model that decomposes a multi‐input multi‐output channel matrix into transmit and receive steering vectors and assuming that only transmit steering vectors are available at the base transmit stations, we, first, propose a regularized channel inversion precoding scheme to enhance the sum‐rate assuming only single‐antenna users are available in the system. Next, because of the limitation of regularized channel inversion to handle users with multiple receive antennas, a novel block diagonalization method is proposed. We construct the precoding matrices that jointly eliminate inter‐cell interference and maximize the sum‐rate for a given input covariance matrix. Assuming total power constraint and per‐base‐station power constraints, optimal power allocation schemes are further developed to optimize the sum‐rate. We analytically show that the sum‐rate increases linearly with the number of users when only single‐antenna users are present in the system. Numerical results show that at low signal‐to‐noise ratios, the block diagonalization precoding outperforms the regularized channel inversion in terms of the bit error rate; while at high signal‐to‐noise ratios, the regularized channel inversion provides a better performance. Copyright © 2016 John Wiley & Sons, Ltd.

Conventional amplitude-phase modulations (APMs) are designed such that the minimum Euclidean distance between constellation points is maximized. Unlike these modulations, the error performance of spatial modulation (SM) is not only a function of the Euclidean distances but also the energy of each symbol, i.e. constellation point. Therefore, conventional APM schemes that are designed solely based on the notion of Euclidean distance are not necessarily suitable for SM transmission. In this paper, the constellation design for SM is investigated and it is shown that, by a proper constellation design, a significant performance gain is obtained compared to the well-known phase shift keying (PSK) or quadrature amplitude modulation (QAM). It is shown that in many cases multi-ring star-QAM is a suitable constellation for SM. However, when the number of transmit antennas is large, the numerically derived constellation converges to the conventional phase shift keying (PSK) constellation, especially at small number of receive antennas.

We study the feasibility of cognitive radio (CR) communication in the presence of a K-user multi-input multi-output (MIMO) interference channel as the primary network. Assuming that the primary interference network has unused spatial degrees of freedom (DoFs) , we first investigate the sufficient condition on the number of antennas at the secondary transmitter under which the secondary system can communicate while causing no interference to the primary receivers. We show that, to maximize the benefit, the secondary transmitter should have at least the same number of antennas as the spatial DoFs of the primary system. We then derive the secondary precoding and decoding matrices to have zero interference leakage into the primary network while the signal-to-interference plus noise ratio (SINR) at the secondary receiver is maximized. As the success of the secondary communication depends on the availability of unused DoFs, we then propose a fast sensing method based on the eigenvalue analysis of the received signal covariance matrix to determine the availability of unused DoFs or equivalently spatial holes. Since the proposed fast sensing method cannot identify the indices of inactive primary streams, we also provide a fine sensing method based on the generalized likelihood ratio test (GLRT) to decide the absence of individual primary streams. Simulation results show that the proposed CR sensing and transmission scheme can, in practice, provide a significant throughput while causing no interference to the primary receivers, and that the sensing detects the spatial holes of the primary network with high detection probability.

The problem of joint precoder design for the source and relay nodes of a cooperative cognitive radio (CR) system is investigated. We consider a non-regenerative relaying secondary CR system with underlay spectrum sharing methodology with the primary users. Based on an expression for the achievable throughput of secondary system, we develop an optimization problem to maximize the throughput subject to power constraints at the secondary source and relay, and an interference power constraint at the primary due to secondary source and relay transmission. First, we derive the structure of each of the relay and source precoding matrices separately assuming the other is known. Then, we propose an iterative technique to jointly design the source and relay precoding matrices. The results are also extended to the case where the direct source-destination link is available. Through simulation, we demonstrate the effectiveness of our proposed approach in improving the achievable throughput, and compare its performance with that of numerical optimization, source only precoding, relay only precoding, and a naive amplify-and-forward method.

Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. Generally, relay selection algorithms require channel state information (CSI) feedback from all cooperating relays to make a selection decision. This requirement poses two important challenges, which are often neglected in the literature. Firstly, the fed back channel information is usually corrupted by additive noise. Secondly, CSI feedback generates a great deal of feedback overhead (air-time) that could result in significant performance hits. In this paper, we propose a compressive sensing (CS) based relay selection algorithm that reduces the feedback overhead of relay networks under the assumption of noisy feedback channels. The proposed algorithm exploits CS to first obtain the identity of a set of relays with favorable channel conditions. Following that, the CSI of the identified relays is estimated using least squares estimation without any additional feedback. Both single and multiple relay selection cases are considered. After deriving closed-form expressions for the asymptotic end-to-end SNR at the destination and the feedback load for different relaying protocols, we show that CS-based selection drastically reduces the feedback load and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback.

Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. However, for relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. In this paper, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the "strong" relays with limited feedback. Following that, the CSI of the selected relays is estimated using linear minimum mean square error estimation. To minimize the effect of noise on the fed back CSI, we introduce a back-off strategy that optimally backs-off on the noisy estimated CSI. For a fixed group size, we provide closed form expressions for the scaling law of the maximum equivalent SNR for both Decode and Forward (DF) and Amplify and Forward (AF) cases. Numerical results show that the proposed algorithm drastically reduces the feedback air-time and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback channels.

This paper investigates linear precoding designs for a cooperative amplify-and-forward (AF) network with a multi-antenna relay having complete channel state information (CSI). The focus is on both orthogonal AF (OAF) and non-orthogonal AF (NAF) protocols. The precoders at the relay are derived based on the maximum ratio combining (MRC) scheme, followed by an optimal power amplification factor to maximize the end-to-end achievable rate. For OAF, it is a concave optimization problem and the closed-form solution can be obtained using Karush-Kuhn-Tucker (KKT) conditions. However, the optimization problem for NAF is non-convex and getting globally optimal solution in closed-form is more challenging. Our approach is to investigate the achievable rate in different sub-domains of the channel matrix to upper-bound the original problem by a convex optimization problem. It is then shown that the optimal solution to the power amplification factor of the original optimization problem can be obtained in closed-form. The optimal MRC-based relay precoding vector is then established. Numerical results reveal that the proposed system achieves significant end-to-end rate gains over the conventional dual-hop AF multi-antenna as well as cooperative AF single-antenna systems.

Opportunistic schedulers rely on the feedback of the channel state information of users in order to perform user selection and downlink scheduling. This feedback increases with the number of users, and can lead to inefficient use of network resources and scheduling delays. We tackle the problem of feedback design, and propose a novel class of nonorthogonal codes to feed back channel state information. Users with favorable channel conditions simultaneously transmit their channel state information via non-orthogonal beams to the base station. The proposed formulation allows the base station to identify the strong users via a simple correlation process. After deriving the minimum required code length and closed-form expressions for the feedback load and downlink capacity, we show that: the proposed algorithm reduces the feedback load while matching the achievable rate of full feedback algorithms operating over a noiseless feedback channel; and the proposed codes are superior to the Gaussian codes.

In multi-antenna broadcast networks, the base stations (BSs) rely on the channel state information (CSI) of the users to perform user scheduling and downlink transmission. However, in networks with large number of users, obtaining CSI from all users is arduous, if not impossible, in practice. This paper proposes channel feedback reduction techniques based on the theory of compressive sensing (CS), which permits the BS to obtain CSI with acceptable recovery guarantees under substantially reduced feedback overhead. Additionally, assuming noisy CS measurements at the BS, inexpensive ways for improving post-CS detection are explored. The proposed techniques are shown to reduce the feedback overhead, improve CS detection at the BS, and achieve a sum-rate close to that obtained by noiseless dedicated feedback channels.

Spatial modulation (SM) is a new transmission technique for multi-antenna systems in which the transmit antennas are used to modulate the signal. In this paper, the symbol error rate (SER) performance of SM is investigated. In SM, a signal domain modulation (i.e. amplitude-phase modulation) and an antenna domain modulation (i.e. space shift keying) are combined together to achieve a certain transmission rate while exploiting the properties of two independent modulation domains. A key question is the fine balance between the constellation sizes in the two domains when a constant rate is targeted. For a fixed rate, there are many ways to assign constellation vectors to the spatial and signal domains. In this paper, we investigate optimal constellation breakdown between space and signal domains. The analysis is based on the union bound of the error probability of SM with two typical APM schemes, i.e. phase-shift keying (PSK) and square quadrature amplitude modulation (S-QAM). It is shown that, at any transmission rate, there exists an optimal APM dimension in which the SER is minimized. Furthermore, a trade-off between the number of transmit antennas and the transmit power is introduced.

This paper investigates the achievable rate and ergodic capacity of a non-orthogonal amplify-and-forward (NAF) half-duplex multi-relay network where multiple relays exploit channel state information (CSI) to cooperate with a pair of source and destination. In the first step, for a given input covariance matrix at the source, we derive an optimal power allocation scheme among the relays via optimal instantaneous power amplification coefficients to maximize the achievable rate. Given the nature of broadcasting and receiving collisions in NAF, the considered problem in this step is non-convex. To overcome this drawback, we propose a novel method by evaluating the achievable rate in different sub-domains of the vector channels. It is then demonstrated that the globally optimal solution can be derived in closed-form. In the next step, we establish the ergodic channel capacity by jointly optimizing the input covariance matrix at the source and the power allocation among the relays. We show that this is a bi-level non-convex problem and solve it using Tammer decomposition method. This approach allows us to transform the original optimization problem into an equivalent master problem and a set of sub-problems having closed-form solutions derived in the first step. The channel capacity is then obtained using an iterative water-filling-based algorithm. Finally, we analyze the capacity-achieving input covariance matrix at the source in high and low signal-to-noise ratio (SNR) regimes. At sufficiently high SNRs, it is shown that the transmit power at the source should be equally distributed in all broadcasting and cooperative phases. On the other hand, in low SNR regions, the source should spend all its power in the broadcasting phase associated with a relay having the strongest cascaded source-relay and relay-destination channels.

In this paper, the problem of precoder design and node power allocation in a three node cooperative multiple-input multiple-output (MIMO) relay system is discussed. All the nodes are assumed to be equipped with multiple antennas and the source and the relay nodes are subject to a total transmit power constraint. We first introduce an upper bound on the received mean square error (MSE), then we suggest suboptimal structures to the source and the relay precoders to minimize this bound. Unlike the previous works in this area, the proposed precoders are easy to calculate and does not involve in computationally costly iterative methods. Next, based on the precoder structures, it is shown that proper transmit power assignment to the source and relay nodes can further improve the system performance and the optimal power allocation for the special case of single symbol transmission is derived. Simulation results show significant improvement in the received mean square error (MSE) by applying the proposed precoding and node power allocation schemes. The node power allocation scheme is also shown to be most effective when the relay and destination nodes have different noise levels.

This paper addresses the problem of optimal power allocation among relaying nodes for a non-orthogonal amplify-and-forward (NAF) half-duplex relay network where multiple relays exploit channel state information (CSI) to cooperate with a pair of source and destination to maximize the source-destination mutual information (MI). In particular, assuming that the relays have complete CSI of all source-relay, source-destination, and relay-destination links, we investigate an optimal power sharing scheme via optimal power amplification coefficients at the relays. Given the nature of broadcasting and receiving collisions in NAF, the considered problem is non-convex. To overcome this drawback, we propose a novel method by evaluating the MI in different sub-domains of the vector channels. It is then demonstrated that the globally optimal solution can be obtained. In particular, the optimal solutions are derived in closed-form for the system under the total average power constraint (TAPC) and for the system under both TAPC and individual average power constraint (IAPC) at each relay. Numerical results are provided to quantify the significant gains offered by the proposed power sharing schemes over conventional schemes using either channel distribution information (CDI) or channel inversion (CI).

In this paper, we consider the problem of optimal distributed beamforming at the relay nodes of a cognitive radio (CR) network. We assume that the CR network is a cooperative relay network with amplify-and-forward (AF) relaying scheme and is composed of single-antenna source, relay and destination nodes. We further assume that the direct link between the secondary source and destination is absent. Based on these assumptions, we first formulate the signal-to-interference-plus-noise ratio (SINR) at the primary and the secondary destinations as a function of beamforming vector at the secondary relay nodes. We then develop an SINR maximization problem at the secondary destination subject to satisfying a minimum received SINR at the primary destination to guarantee a minimum quality-of-service (QoS) for the primary network. The proposed optimization problem is not generally convex and we relax it to a convex feasibility problem to be able to solve it numerically. Numerical results show that by using a simple bisection algorithm, we can efficiently find the solution to the constrained SINR maximization problem. We numerically study the performance of the proposed scheme in terms of the received SINR in several different scenarios. The proposed method enables a secondary network to use the licensed spectrum of a primary system while imposing a controlled interference and thereby guaranteeing a minimum QoS to the primary network.

In this paper, we study the problem of relay precoder design in a multi-antenna non-regenerative relay cognitive radio (CR) system assuming underlay spectrum sharing methodology with the primary users (PUs). An expression for the capacity of the secondary system is derived assuming fixed source covariance matrix. We then consider maximizing this capacity expression subject to a power constraint at the relay and an interference power constraint at the PU due to the secondary relay. We then derive the structure of the relay precoding up to a square matrix that should be chosen optimally. A constrained optimization problem is derived to find this square matrix to maximize the capacity equation. The solution to this optimization problem involves an exhaustive search and the complexity increases with the number of relay antennas. We, therefore, propose an alternative sub-optimal approach with significantly lower complexity to derive the structure of the relay precoding matrix. Through simulation, we compare the effectiveness of the optimal and the sub-optimal approaches to improve the achievable throughput of the CR system. It is shown that both approaches provide a significant improvement in the throughput of the system at different power and interference regimes.

In this paper, we investigate the channel regularization and vector perturbation techniques at the source and linear precoding at the relay to enhance the performance of a dual-hop amplify and-forward (AF) relay downlink system. At first, an optimal regularized channel inversion scheme via regularization parameter is proposed. The joint channel regularization and linear precoder design at the relay is then investigated using the mean-square-error (MSE) criterion. Since dealing directly with such a criterion is quite involved, we propose a simple iterative solution. Our simulation results show that the proposed solution significantly outperforms the conventional channel inversion method. To further improve the performance of the regularization scheme, we further incorporate vector perturbation into channel regularization using a sphere encoder at the source. Numerical results show that the bit-error-rate (BER) performance of the regularized perturbation technique outperforms other well-known precoder designs in dual-hop AF relay downlink systems.

This paper investigates the achievable rate and ergodic capacity of an orthogonal amplify-and-forward (OAF) half-duplex multiple-relay network with direct link where multiple relays use channel state information (CSI) to cooperate with the source and destination. The relays are subject to two types of power constraint: the total average power constraint (TAPC) and the individual average power constraint (IAPC). In the first step, by assuming a fixed input covariance matrix at the source, we derive an optimal power allocation (OPA) scheme among the relays via optimal instantaneous power amplification coefficients to maximize the achievable rate. The closed-form optimal solutions are obtained for the considered system under either the TAPC or both the TAPC and IAPC. Next, we derive the ergodic capacity by jointly optimizing the input covariance matrix and the power allocation at the relays. We show that this is a bi-level non-convex problem and solve this using Tammer decomposition method. This approach allows us to convert the original optimization problem to a master problem and a set of sub-problems that have closed-form solutions as obtained in the first step. The ergodic capacity is then obtained using an iterative water-filling-based algorithm.

This paper combines the idea of relay and antenna selection with that of partial channel state information (CSI) based precoding. We consider a non-regenerative two-hop relay network where all the nodes are equipped with multiple antennas. It is assumed that multiple relay nodes are available for cooperation and that the source and each individual relay have the full CSI of the source-relay channel. It is further assumed that each relay knows the spatial correlation matrix of relay-destination channel. The structure of the optimum precoders to minimize a tight lower-bound on the average received minimum mean square error (MMSE) at the source and the relays are then introduced. Using these precoders and based on a computationally efficient proposed method, the best relay and antenna subsets at the source and the relay are then selected to further minimize the MMSE. By simulation, we show that the proposed scheme provides a significant performance gain in terms of the bit error rate (BER).

We consider the analysis and design of space-time trellis codes (STTCs) for a cooperative relay channel operating in amplify-and- forward (AF) mode assuming the source and destination nodes are equipped with multiple antennas but the relay node has single antenna. We derive a pairwise error probability (PEP) expression for the performance of STTCs in this type of channels. A simple upper- bound on PEP is then derived and is maximized to find the optimum STTCs. We show that the designed STTCs based on the derived criterion achieve full diversity in the AF relay channels especially at high signal-to-noise-ratios (SNRs). The maximum achievable diversity in relay channels with single-antenna relay is bounded by min(M,N) where M and N are respectively the number of antennas in source and destination nodes. Simulation results confirm that the proposed codes achieve the maximum diversity and also provide an appealing coding gain.

The degrading effect of RF impairments on the performance of wireless communication systems is more pronounced in MIMO- OFDM transmission. Two of the most common impairments that significantly limit the performance of MIMO-OFDM transceivers are IQ-imbalance and phase noise. Low-complexity estimation and compensation techniques that can jointly remove the effect of these impairments are highly desirable. In this paper, we propose a simple joint estimation and compensation technique to estimate channel, phase noise and IQ-imbalance parameters in MIMO-OFDM systems under multipath slow fading channels. A subcarrier multiplexed preamble structure to estimate the channel and impairment parameters with minimum overhead is introduced and used in the estimation of IQ-imbalance parameters as well as the initial estimation of effective channel matrix including common phase error (CPE). We then use a novel tracking method based on the second order statistics of the inter-carrier interference (ICI) and noise to update the effective channel matrix throughout an OFDM frame. Simulation results for a variety of scenarios show that the proposed low-complexity estimation and compensation technique can efficiently improve the performance of MIMO-OFDM systems in terms of bit-error-rate (BER).

The application of a 2D IIR digital filter, having a broadband beam-shaped 2D passband, is investigated for beamforming in narrowband wireless communication systems. Specifically, their use for interference rejection in a carrier-modulated communication system is proposed. Monte-Carlo simulations of the bit-error-rate, as a function of the antenna-side signal-to-interference ratio for a 1 GHz BPSK-modulated source operating at 25 Mbps over a 32 element array, confirm a signal-to-noise-plus-interference ratio (SINR) system gain of 10 to 15 dB relative to the non-beamformed case. The proposed method allows a single broadband beamformer to operate over a wide frequency bandwidth containing multiple frequency-agile channels. This particular application is potentially well-suited for cognition-enabled base stations.

We address the problem of designing linear precoder and decoder for single symbol transmission in three node amplify-and-forward (AF) multi-input-multi- output (MIMO) relay systems where all the nodes are equipped with multiple antennas and the source and the relay nodes are subject to individual transmit power constraints. We first find the optimal decoder to maximize the average received signal-to-noise- ratio (SNR). Next, the source and the relay precoders are designed for maximizing a lower bound on the total SNR. Further, a decision criterion as to whether the relay node should participate in transmission is derived. Simulation results show significant improvement in the received SNR and bit error rate (BER) by applying the proposed precoding and decoding schemes. It is also shown that the computational complexity of the proposed scheme is much lower than other methods in the literature.

In this paper, we extend the results of [12] by proposing a joint polling and contention scheduling scheme that reduces the feedback load in orthogonal frequency division multiple access (OFDMA) systems employing adaptive modulation. This feedback reduction is achieved by grouping users into categories, and requesting feedback from users that belong to a certain category only. The feedback process comprises of two modes. The first mode is a polling only mode and the second mode consists of a contention stage followed by a polling stage. The contention stage is used to find the i-th category where the best user is likely to be found. All users belonging to that category are polled sequentially until an acceptable user with channel quality above a predefined threshold is found. Numerical results show that the proposed scheme reduces the feedback load and the guard-time without any loss in the spectral efficiency when compared to the optimal selective diversity with full feedback algorithm shown in [11]. We, further, derive closed-form expressions for the feedback load, average guard time and the spectral efficiency and show that the proposed scheme improves the system spectral efficiency, the feedback load and the average guard time when compared to the schemes proposed in [12].

The application of multi-input-multi-output (MIMO) technology in orthogonal frequency division multiplexing (OFDM) systems provides better spectral efficiency with high capacity gain. It also introduces significant complexity at the transceivers which can be partially reduced using homodyne or zero-IF receivers. However, those transceivers are very sensitive to imperfections of analog components at the RF front end and suffer severe performance degradation in the presence of RF impairments. Two of the most common impairments that significantly limit the performance of MIMO-OFDM transceivers are IQ-Imbalance and phase noise. In this paper, we propose a joint estimation and compensation technique to estimate channel, phase noise and IQ-Imbalance parameters in MIMO-OFDM systems under multipath slow fading channels. A subcarrier multiplexed preamble structure to estimate the channel and impairment parameters with minimum overhead is introduced and used in the estimation of IQ-Imbalance parameters as well as the initial estimation of effective channel matrix including common phase error (CPE). We then use a novel tracking method using pilot subcarriers to update the effective channel matrix throughout an OFDM frame. Simulation results for a variety of scenarios indicate that the proposed estimation and compensation technique efficiently improves the performance of MIMO-OFDM systems in terms of bit- error-rate (BER) as compared with the non- compensated case.

Multicell coordination increases the cell-edge users' throughput in cellular wireless communication if the inter-cell interference (ICI) is mitigated properly. In this paper, we use the null space concept to design precoders and decoders to remove ICI for cell-edge users in the downlink of a network MIMO system. We propose two novel methods that are able to eliminate ICI assuming no channel state information (CSI) is available at the basestations. Calculating signal-to-interference-ratio (SINR), we show that our proposed methods reaches to higher SINR in comparison to the block diagonalization (BD) with full CSI. By simulations, we show our methods outperform the BD method with full CSI in terms of BER since the SINR is higher for our proposed methods. We also show that to obtain most of sum-rate provided by coordination strategy, it is not necessary to have global coordination and having four cells coordinating with each other is enough to reach more than 85 percent of maximum achievable sum-rate.

This paper addresses the problem of design of practical communication strategies for multi-antenna amplify-and-forward and decode-and-forward relay systems. We show that simple linear techniques at source and destination in conjunction with maximum ratio combining can provide an optimal transmission strategy in terms of received SNR without imposing a huge computational load over the relay node(s). Besides, the structure of precoding matrices are very similar at source and relay nodes, which reduces the complexity as all nodes can play the role of source and relay nodes without changing their transmission structure. Numerical results show that the proposed transmission and reception techniques can improve the received SNR, and hence enhance the ergodic capacity.

This paper addresses the problem of optimal number of relays and relay selection and proposes a cooperative transmission scheme with an appealing multiplexing-diversity trade-off. We show that a distributed BLAST transmission in conjunction with successive nulling and cancellation at destination can achieve the optimal trade-off given that the relays are selected according to a specific criterion. Illustrative results indicate that the proposed method can increase the strength of relay networks in providing reliable communications.

This paper presents MIMO precoder designs for frequency-selective channels based on the transmit, receive and channel path correlation matrices. Optimal linear precoder structures are derived based on ergodic capacity criterion for three different scenarios: uncorrelated channel paths but equal spatial correlation matrices, uncorrelated channel paths but unequal spatial correlation matrices, and correlated channel paths. For channels with uncorrelated paths, the preceding structure is composed of a number of parallel precoders designed for frequency-flat fading channels. Simulation results show that the proposed precoders outperform others based only on spatial correlation in various propagation scenarios. Their achievable capacity is better in highly correlated (either spatial or path correlation) environments.

This paper presents a zero-forcing algorithm based on the partial channel knowledge to select the best users for transmission without causing interference to others in a broadcast MIMO system. The proposed scheme preserves the optimal achievable ergodic sum capacity of zero-forcing techniques in limit of large number of active users with significant reduction in complexity and feedback load for channel information updates. Both analytical and simulation results on its advantages in feedback load, complexity and achievable sum rate are presented in different scenarios.

This paper presents a MIMO preceding design for frequency-selective fading channels using the transmit and channel path correlation matrices. The effect of spatial and path correlation on the MIMO system capacity are investigated to develop the optimal linear precoder structures based on ergodic capacity criterion for uncorrelated and correlated channel paths. It is shown that in the uncorrelated case the precoder structure consists of a number of parallel precoders designed for frequency-flat fading channel paths. Performance evaluation by simulation in various MIMO channels shows that the proposed preceding scheme provides a good capacity improvement as compared to existing preceding schemes using only spatial correlation, and its performance is better in an environment with higher (spatial or path) correlation.

This paper presents a general framework for precoder designs for MIMO systems using partial channel knowledge on the transmit and receive correlation matrices at the transmitter. It is shown that the optimal linear precoder for any uncoded and coded MIMO system based on the MMSE or ergodic capacity criterion, or for an orthogonal ST coded MIMO system based on the minimum PEP criterion, is an eigen-beamformer that transmits the signal along eigenvectors of the transmit correlation matrix. Based on the eigen-values of both the transmit and receive correlation matrices, power loading across the eigen-beams is determined by water-pouring policy. Individual effects of the transmit and receive correlation matrices on the system performance are investigated. Simulation results show noticeable performance improvement over MIMO systems without precoder, particularly when the transmit correlation matrix has low rank

This paper presents a precoder design based only on the correlation matrices to avoid the need of perfect channel knowledge at the transmitter and receiver in practical MIMO systems. The structures for optimal linear precoders are derived for three criteria: minimum pairwise error probability, minimum mean squared-error, and maximum ergodic (mean) channel capacity. The minimum pairwise error probability and minimum mean squared-error criteria lead to the same optimum precoder structure. It is shown that, in general, the optimal linear transformations for the three criteria are the eigen-beamformers that transmit the signal along the eigenvectors of the transmit correlation matrix. Power loading across the eigen-beams is determined by considering the eigenvalues of both transmit and receive correlation matrices and can be viewed as a water-pouring policy. Simulation results show noticeable performance improvement over conventional systems, particularly when their transmit correlation matrix has low rank.

This paper presents a precoder design based on the minimum mean squared error (MMSE) criterion and using the knowledge of only the transmit and receive correlation matrices of the underlying MIMO channel. The optimal transformations are shown to be eigen-beamformers, which transmit the signal along eigenvectors of the transmit correlation matrix. Power loading across the eigenbeams are determined based on eigenvalues of both transmit and receive correlation matrices and can be viewed as a waterpouring policy. Performance of the proposed precoders using partial channel information in various MIMO channels is evaluated and compared to that of precoders based on full channel knowledge at transmitter. It was shown that as the number of the transmit and receive antennas increases, the MMSE-based MIMO precoders using partial channel knowledge can achieve the performance of precoders using full channel knowledge. Furthermore, the channel that gives the best performance is the one with only one strong eigen mode for cases with a large number of receive antenna or a small number of transmit antenna. For small number of receive antennas or large number of transmit antennas, the full rank channel with equal gain eigen modes will gives the best performance.

This paper presents neural network (NN) approaches for modeling the I-V characteristics of silicon-on-insulator MOSFETs. The modeling approach is technology independent, fast, and accurate, which makes it suitable for circuit simulators. In the model, two different NN architectures, namely, multilayer perceptron and generalized radial basis function, are used and compared. To increase the training efficiency of the NN, both modular and region partitioning methods have been proposed and utilized. In addition, two approaches for obtaining the transconductance and output conductance of the device are discussed. The first approach makes use of an NN for the conductances, while the second uses the numerical differentiation of the I-V results. To confirm the accuracy of the model, the drain-current characteristics as well as conductances obtained by the model are compared to the simulation data for the points where the NNs are not trained. The comparison shows excellent agreements with relative errors of around 1% over a wide range of drain and gate voltages as well as channel lengths and widths.