Multiple-antenna Communication Systems Research Articles

RIS-Assisted Secure Communications: Low-Complexity Beamforming Design

Joint active and passive beamforming optimization is investigated to enhance the physical layer security of a reconfigurable intelligent surface (RIS)-assisted multiple-antenna communication system. The problems are formulated under two criteria: secrecy rate maximization and power consumption minimization. For each design problem, a novel collaborative design algorithm is proposed by capitalizing on the mathematical structure of the optimal active beamforming vector, which requires no iterative updating between the transmit beamformer and the RIS-reflecting beamformer. Numerical results demonstrate that the proposed algorithms enjoy much lower computational complexity than the state-of-the-art alternating optimization-based methods while achieving almost identical secrecy performance.

A Powerful Joint Modulation and STBC Identification Algorithm for Multiuser Uplink SC-FDMA Transmissions

Owing to the rapid development and broad adoption of multiple antenna communication systems over the past few years, space-time block coding (STBC) identification has emerged as a crucial responsibility for smart radios. The majority of previous analysis of STBC identification assumed that the utilized modulation schemes for single-user and uncoded broadcasts were known. This paper investigates the challenge of joint STBC and modulation identification for uplink transmissions with numerous users in single-carrier frequency division multiple access (SC-FDMA) systems using coded transmissions. Multi-user channel estimation brings us one step closer to implementing the proposed design in real-world systems. We additionally employ the channel decoder’s deliverables, which are common in many real-world systems, to enhance the identifying and estimating procedures. Mathematical findings prove that a recursive approach can be utilized to tackle the maximum likelihood (ML) problem of simultaneous STBC and modulation identification with channel estimation. Distinguishing the superimposed signals that originate at the base-station (BS) is accomplished with the use of the space-alternating generalized expectation-maximization (SAGE) algorithm. After that, an expectation-maximization (EM) engine is deployed to make the necessary adjustments to the parameters being considered for each user. The success of the above-mentioned architecture for usage in practical applications is demonstrated by the simulation results obtained under various conditions.

Convergence Guarantees for Non-Convex Optimisation With Cauchy-Based Penalties

In this paper, we propose a proximal splitting methodology with a non-convex penalty function based on the heavy-tailed Cauchy distribution. We first suggest a closed-form expression for calculating the proximal operator of the Cauchy prior, which then makes it applicable in generic proximal splitting algorithms. We further derive the condition required for guaranteed convergence to a solution in optimisation problems involving the Cauchy based penalty function. Setting the system parameters by satisfying the proposed condition ensures convergence even though the overall cost function is non-convex when minimisation is performed via a proximal splitting algorithm. The proposed method based on Cauchy regularisation is evaluated by solving generic signal processing examples, i.e. 1D signal denoising in the frequency domain, two image reconstruction tasks including de-blurring and denoising, and error recovery in a multiple-antenna communication system. We experimentally verify the proposed convergence conditions for various cases, and show the effectiveness of the proposed Cauchy based non-convex penalty function over state-of-the-art penalty functions such as $L_1$ and total variation ($TV$) norms.

Blind Spectrum Sensing Using Extreme Eigenvalues for Cognitive Radio Networks

Here, a new spectrum sensing method, called mean-to-square extreme eigenvalue (MSEE), is proposed. Considering a multiple antenna communication system, the proposal is drawn from the arithmetic-to-geometric mean (AGM) algorithm using only the smallest and the largest eigenvalues of the covariance matrix of the received signal. The aim of MSEE is to avoid the heavy computational costs of AGM method. First, based on the random matrix theory, a theoretical development to set the threshold of the proposal is provided. Then, the validity of the expression is verified by simulations. Finally, simulation results show an interesting performance of MSEE compared with several spectrum sensing methods in the literature.

Secret Key Exchange Using Private Random Precoding in MIMO FDD and TDD Systems

Along with the ongoing evolution of multiple antenna communication systems, new physical layer security techniques are continuing to achieve higher levels of secrecy. Most physical layer approaches, however, concern time division duplex (TDD) channels which rely on using the channel reciprocity feature as a shared randomness and tend to be associated with a large computational burden. In this paper, we propose a new physical layer method which utilizes private random precoding for exchanging the secret key bits in multiple-input–multiple-output (MIMO) systems. The principle of this method is to exploit the precoding matrix index in a manner that produces low correlation at the adversary. A robust key exchange between the transmitter and the receiver is established by uniquely relating the secret key bits to the channel precoding matrix using a private version of the universal codebooks. What is more is that the proposed method is applicable in both frequency division duplex (FDD) and TDD channels. The results demonstrate that the proposed method can offer superior performance in terms of the key agreement, secrecy level, and computational load.

Mutual Coupling Mitigation in Broadband Multiple-Antenna Communication Systems Using Feedforward Technique

An efficient method to mitigate the forward scattering (shadowing) effect and the near-field coupling among elements of broadband multiple-antenna communication systems is proposed. The technique is based on provision of a passive feedforward coupling among elements to cancel out the mutual couplings. Electrical current paths, with appropriate shape, location, and length, between adjacent elements are established to provide current distributions on adjacent elements that are approximately equal in magnitude and out of phase with the induced current on the same antenna due to the near-field coupling and scattering effects. As the coupling level decreases, the radiation pattern of an excited array element, in the presence of the other array elements, approaches the pattern of the antenna element in isolation. The technique is first detailed for a two-element wideband monoconical antenna array and is then extended to a uniform 12-element circular array of the same monoconical antennas where only feedforward paths are applied to circumferentially adjacent elements to reduce the coupling over a very wide bandwidth. The experimental results indicate that the application of the proposed feedforward technique to a 12-element circular array of monoconical antennas can provide a minimum of 2-dB reduction in the average gain deviation from omnidirectional radiation over an about 30% fractional bandwidth. Another important feature of the feedforward technique is removal of radiation nulls of the array elements at all frequencies and all directions.

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous-valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Noncoherent unitary space-time codes: Constellation design and decoding algorithm

Two novel schemes of unitary space-time constellations generation based on zero vectors adding are proposed for the multiple-antenna communication system. In the first scheme, T 2 zero row vectors are added into conventional unitary matrices directly, and the number of new unitary matrices obtained by different positions of the added zero vectors in T symbol duration is ⌊T / T 2 ⌋ times larger than that of conventional unitary matrices. In the second scheme, one part of the required constellations is created by the first scheme and the other part is obtained by the conventional design. This means that more information bits can be transmitted by the new constellations. According to their special construction, two corresponding decoding algorithms are proposed with low complexity in flat fading channel, respectively. At the same time, the probability of miss detection is deduced for the decoding algorithms. Performance analysis and simulation results show that the proposed constellations outperform the conventional constellations and the proposed decoding algorithms are efficient and simple.

COMPRESSIVE ESTIMATION OF CLUSTER-SPARSE CHANNELS

Cluster-sparse multipath channels, i.e., non-zero taps occurring in clusters, exist frequently in many communication systems, e.g., underwater acoustic (UWA), ultra-wide band (UWB), and multiple-antenna communication systems. Conventional sparse channel estimation methods often ignore the additional structure in the problem formulation. In this paper, we propose an improved compressive channel estimation (CCE) method using block orthogonal matching pursuit algorithm (BOMP) based on the cluster-sparse channel model. Making explicit use of the concept of cluster-sparsity can yield better estimation performance than the conventional sparse channel estimation methods. Compressive sensing utilizes cluster- sparse information to improve the estimation performance by further mitigating the coherence in training signal matrix. Finally, we present the simulation results to conflrm the performance of the proposed method based on cluster-sparse.

Design criterion and construction methods for partially coherent multiple antenna constellations

We consider multiple-antenna communication systems in Rayleigh fading channel, where the transmitter does not know the channel coefficients and the receiver has only an estimate of them. We further assume that the transmitter and receiver know the statistics of the estimation error. We refer to this system as partially coherent system, for which we derive the expressions for the optimal detector and study the constellation design problem. Since the Chernoff bound on pairwise error probability of the partially coherent systems appears to be intractable, we use Stein's Lemma to propose a design criterion based on Kullback-Leibler (KL) distance between conditional distributions. Using the KL-based design criterion, we construct constellations for multiple-antenna systems which can be demodulated in the presence of channel estimation errors. The proposed constellations are multi-level, with multi-dimensional spherical constellations at each level. We show that these new constellations provide significant performance improvement over the conventional single-antenna PSK and QAM constellations, and multiple-antenna techniques such as Bell Lab's Space-Time (BLAST) architecture and orthogonal transmit diversity (OTD) schemes, when the estimation variance is comparable to the reciprocal of the signal-to-noise ratio.

Transmit antenna selection based strategies in MISO communication systems with low-rate channel state feedback

The performance of multiple-antenna communication systems is known to critically depend on the amount of channel state information (CSI) available at the transmitter. In the low-rate CSI feedback case, an important problem is what kind of information should be submitted to the transmitter in each feedback cycle and what is the optimal transmission strategy in this case. In this paper, we address this problem in the multiple-input single-output (MISO) case by analytically comparing the bit error rate (BER) performance of different low-rate feedback based transmitter strategies involving various combinations of transmit antenna selection, Alamouti's spacetime coding, and adaptive power allocation.

Body-Worn E-Textile Antennas: The Good, the Low-Mass, and the Conformal

Support of ever increasing applications for wireless data and communications on a body-centric platform requires novel antenna systems that can be integrated with the body-worn environment, while maintaining free-range of movement and minimal mass impact. E-textile antennas show great promise due to their ease of integration with other textile materials, and they are inherently low-mass and flexible relative to conventional antenna materials. Much attention has been given recently to multiple-antenna communication systems due to the increased performance compared to conventional single-antenna systems. For body-centric applications, the low-mass, flexibility, and integration simplicity of e-textile antennas can enable multiple-antenna systems, which otherwise would be precluded by the rigidity and mass of conventional antenna materials. Several examples of this are considered here with e-textile antennas in an array environment. A conventional microstrip array constructed with e-textiles is shown to have robust performance with moderate amounts of bending, similar to that which might be seen with body-worn arrays. In addition to the conventional array, a wideband multiple-antenna system to support a variety of wireless communication protocols, while maintaining polarization diversity and excellent coverage over a majority of the radian sphere is demonstrated.

Utilizing the Spatial Information Provided by Channel Norm Feedback in SDMA Systems

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> To achieve high performance, in terms of reliability and throughput, in future multiple-antenna communication systems, it is essential to fully exploit the spatial dimensions of the wireless propagation channel. In multiuser communication systems, the throughput can be significantly increased by simultaneously transmitting to several users in the same time-frequency slot by means of <emphasis emphasistype="boldital">spatial-division multi-access</emphasis> (SDMA). A major limiting factor for downlink SDMA transmission is the amount of <emphasis emphasistype="boldital">channel-state information</emphasis> (CSI) that is available at the transmitter. In most cases, CSI can be measured/estimated only at the user terminals and must be fed back to the base station. This procedure typically constrains the amount of CSI that can be conveyed to the base station. Herein, we develop several low-complexity, as well as optimized, SDMA downlink resource-allocation schemes that are particularly suitable for systems utilizing statistical channel information and partial CSI feedback. </para>

Quantization Bounds on Grassmann Manifolds and Applications to MIMO Communications

The Grassmann manifold G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n,p</sub> (L) is the set of all p-dimensional planes (through the origin) in the n-dimensional Euclidean space L <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> , where L is either R or C. This paper considers the quantization problem in which a source in G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n,p</sub> (L) is quantized through a code in G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n,q</sub> (L), with p and q not necessarily the same. The analysis is based on the volume of a metric ball in G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n,p</sub> (L) with center in G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n,q</sub> (L), and our chief result is a closed-form expression for the volume of a metric ball of radius at most one. This volume formula holds for arbitrary n, p, q, and L, while previous results pertained only to some special cases. Based on this volume formula, several bounds are derived for the rate-distortion tradeoff assuming that the quantization rate is sufficiently high. The lower and upper bounds on the distortion rate function are asymptotically identical, and therefore precisely quantify the asymptotic rate-distortion tradeoff. We also show that random codes are asymptotically optimal in the sense that they achieve the minimum possible distortion in probability as n and the code rate approach infinity linearly. Finally, as an application of the derived results to communication theory, we quantify the effect of beamforming matrix selection in multiple-antenna communication systems with finite rate channel state feedback.

Low complexity iterative decoding for bit-interleaved coded modulation

Bit-interleaved coded modulation with iterative decoding (ID) is an effective scheme for both AWGN and fading channels because it simultaneously realizes large Euclidean distance and high diversity. In the literature, ID schemes with hard-decision feedback (HDF), as well as soft-decision feedback (SDF), have been investigated. While HDF/ID exhibits a performance inferior to SDF/ID, it is much simpler to implement. To enhance the performance of HDF/ID with moderate additional complexity, we propose a uniform soft-decision feedback ID (USF/ID) scheme. The proposed scheme is applicable in both single antenna and multiple antenna communication systems. The simulation results verify that it achieves impressive performance gain over HDF/ID and has a practically more attractive implementation than SDF/ID, especially for complexity-constrained wireless applications

On Optimal Training Sequence Design for Multiple-Antenna Systems Over Dispersive Fading Channels and Its Extensions

In this correspondence, previous work on (P,V,M) code sequences, which are sequences with a zero-correlation zone (ZCZ) that can be used to accurately and efficiently perform channel estimation in multiple-antenna communication systems, are noted. In addition, extensions of ZCZ sequence sets based on perfect sequences, almost-perfect sequences, and perfect arrays are presented. It is shown that those ZCZ sets based on perfect sequences/arrays are optimal with respect to theoretical bounds.

Multiple-antenna communication systems: an emerging technology

A recent development in wireless communications is the application of multiple-input multiple-output (MIMO) systems to radio communications via use of multiple antennas. In order to investigate the technologys potential, an experimental MIMO system containing two four-element antenna arrays (4x4) has been developed at the University of Alberta. The system is used to obtain MIMO channel measurements in a typical indoor office environment in the ISM band (902-928 MHz). Measurement campaigns have been performed using different antenna spacings and two different types of antenna: half-wavelength (lambda/2) centre-fed dipoles and dual-polarized patches. The measurements are used to calculate channel capacities for an indoor 4x4 MIMO system. The measurements confirm the high capacity potential of a MIMO channel, with ergodic capacity of approximately 21 bits per channel use available with either antenna type at a signal-to-noise ratio of 20 dB if the antenna element separation is lambda/2 or larger. An introduction to basic MIMO theory, a discussion of the University of Alberta wireless MIMO testbed, and observations regarding the measured indoor MIMO channel are presented in the paper.

Multiple antenna systems: Their role and impact in future wireless access

Multiple antennas play an important role in improving radio communications. In view of this role, the area of multiple antenna communication systems is in the forefront of wireless research. This article reviews two key related aspects of multiple antenna communication systems: multiple access interference mitigation at the receiver via multi-user beamforming; and space-time modulation and coding for MIMO systems. It is shown that both multi-user and MIMO receivers share similar signal processing and complexity tradeoffs.. Following that, a general unified framework for assessing different types of space-time modulation for MIMO systems is introduced. These space-time modulation methods are then compared in terms of Shannon capacity over multipath channels. Key MIMO system performance and implementation issues are also highlighted.

Optimal binary training sequence design for multiple-antenna systems over dispersive fading channels

Accurate and efficient channel estimation is important in multiple-antenna communication systems in order to effectively reduce the mutual interference among different transmitting antennas. For a nondispersive channel that is modeled by a single tap for each transmitting and receiving antenna pair, the well-known Hadamard sequences can be applied to estimate the channel coefficients. However, for a dispersive channel that has multipath problem and is modeled by multiple taps, the optimal sequences must have both good autocorrelations and cross correlations. The existence of binary sequences with such good property is an open problem. In this paper, we devise an algorithm to find these sequence sets. These codes can be applied in multiple-antenna systems.

Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations.