Multiple-output Communication Systems Research Articles

Error probability of the data transmission in mimo systems with space-division multiple access in Rayleigh fading environments

We consider multiple-input multiple-output (MIMO) communication systems with adaptive antenna arrays at both ends of the link in which the data transmission is performed via parallel eigenchannels matched to the random spatial channel. The effectiveness of the projection method of space-division multiple access is studied. The method does not require estimation of the arrival directions of signals and is based on orthogonalization of all eigenchannels. Exact analytical expressions are obtained for the bit-error probability during the data transmission via the channel with uncorrelated Rayleigh fading of signals in an MIMO system with an arbitrary number of users and antennas.

Automatic design of orthogonal or near-orthogonal linear dispersive space-time block codes

This paper considers a wireless multiple-input multiple-output (MIMO) communication system in a frequency-nonselective scenario with spatially uncorrelated Rayleigh fading channel coefficients and investigates the design of linear dispersive (LD) space-time block codes. Efficient LD codes are obtained by optimizing the constituent weight matrices so that an upper bound on the union bound of the codeword error probability is minimized. Interestingly, the proposed design procedure automatically generates LD codes that either correspond to, or are close to, the well-known class of orthogonal space-time block (OSTB) codes. A theoretical analysis confirms this by proving that OSTB codes are indeed optimal, when the setup under study permits their existence. Simulation results demonstrate the excellent performance of the designed codes. In particular, the importance of the codes' near-orthogonal property is illustrated by showing that low-complexity linear equalizer techniques can be used for decoding purposes while incurring a relatively moderate performance loss compared with optimal maximum-likelihood (ML) decoding

Fast techniques for computing finite-length MIMO MMSE decision feedback equalizers

Multiple-input multiple-output (MIMO) digital communication systems have received great attention due to their potential of increasing the overall system throughput. In such systems, MIMO decision feedback equalization (DFE) schemes are often used to mitigate intersymbol interference (ISI) resulting from channel multipath propagation. In this context, the existing computationally efficient methods for exact estimation of the DFE filters under minimum mean-square-error criteria (MMSE-DFE) rely on fast Cholesky decomposition and backsubstitution or Levinson techniques. These methods may still present several difficulties in implementation as the demand on higher transmission rates increases, and thus a simple solution is necessary. In this paper, new procedures for fast computation of the MIMO-MMSE-DFE are presented. The new algorithms are obtained from a simple observation, namely, that the optimal feedforward filter (FFF) is related to the well-known Kalman gain matrix, commonly encountered in fast recursive least squares adaptive algorithms-for which fast recursions exist and are readily applicable. Moreover, the feedback filter can be easily computed via stable fast MIMO convolution techniques. As a result, the proposed method is less complex, more structured, and can be as reliable in finite precision as known approaches in the literature.

Compact polarisation and spatial multiplexing antenna for MIMO applications

A compact size, polarisation and spatial multiplexing slot antenna utilising the Spatial Multiplexing of Local Elements (SMILE) technique, is proposed. The antenna is used to explore diversity gain with a single RF channel in the applications of a multiple-input multiple-output (MIMO) wireless communication system.

Spatially correlated multiple-antenna channel capacity distributions

The capacity of multiple-input multiple-output (MIMO) wireless communication systems over spatially correlated Rayleigh distributed flat fading channels with complex Gaussian additive noise is investigated. Specifically, the probability density function of the mutual information between transmitted and received complex signals of MIMO systems is derived. Using this density the closed-form ergodic capacity (mean), delay-limited capacity, capacity variance and outage capacity formulas for spatially correlated channels are derived and then these formulas are evaluated numerically. Numerical results show how the channel correlation degrades the capacity of MIMO communication systems. It is also shown that the density of mutual information of correlated/uncorrelated MIMO systems can be approximated by a Gaussian density with derived mean and variance, even for a finite number of inputs and outputs.

Designing MIMO communication systems: constellation choice and linear transceiver design

This papers considers the design of a mutiple-input multiple-output (MIMO) communication system with channel knowledge at the transmitter and receiver. The design methods available in the literature have addressed the following two aspects of the problem: a) choice of the symbol constellations for a given transmission scheme or b) choice of the optimal (linear) precoder and equalizer for a given choice of the constellations. More specifically, the choice of the constellations has been made enforcing a diagonal, or parallel, transmission. However, in practice, the two problems of choosing the constellations and the linear precoder/equalizer are clearly coupled, and the diagonal structure may not be necessarily the best. This paper attempts to provide a global view of the problem by bridging the gap between the existing results on the selection of the constellations and on the design of the signal processing in the form of a linear transceiver (i.e., precoding at the transmitter and equalization at the receiver).

Open-Loop and Closed-Loop Transmit Diversity Techniques—Overview and New Results

We present an overview of multiple-input multiple-output (MIMO) wireless communication systems followed by some of the new techniques proposed by us to enhance performance. Firstly, some of the popular transmit and receive diversity schemes available in the literature are discussed and issues like diversity, rate, power distribution, decoding complexity, decoding delay, amount of feedback and feedback delay and their tradeoffs to achieve reliable and cost effective communications are described. We then analyze the merits and demerits of some of the open-loop (no feedback) and closed-loop (with feedback) schemes, and discuss various methods proposed by us recently to improve the performance of such schemes. The symbol error rate (SER) performance of the various schemes are compared through computer simulations.

Minimum BER prefilter transform for communications systems with binary signaling and known FIR MIMO channel

The problem of designing an optimal prefilter transform for finite impulse response (FIR) multiple-input multiple-output (MIMO) communication systems is addressed. The bit error rate (BER) is minimized under a power constraint. Binary signaling is assumed. The transmitter requires knowledge of the channel transfer function coefficients and the receiver transform. It is shown that the proposed prefiltering transform outperforms three previously known prefilter transform methods in terms of BER versus channel quality. The proposed prefilter transform is applicable to downlink communication systems where the base station can estimate the channel while receiving data from the mobile station.

Minimum Variance Linear Receivers for Multiaccess MIMO Wireless Systems with Space-Time Block Coding

We consider the problem of joint space-time decoding and multiaccess interference (MAI) rejection in multiuser multiple-input multiple-output (MIMO) wireless communication systems. We address the case when both the receiver and multiple transmitters are equipped with multiple antennas and when space-time block codes (STBCs) are used to send the data simultaneously from each transmitter to the receiver. A new linear receiver structure is developed to decode the data sent from the transmitter-of-interest while rejecting MAI, self-interference, and noise. The proposed receivers are designed by minimizing the output power subject to constraints that zero-force self-interference and/or preserve a unity gain for all symbols of the transmitter-of-interest. Simulation results show that in multiaccess scenarios, the proposed techniques have substantially lower symbol error rates as compared with the matched filter (MF) receiver, which is equivalent to the maximum likelihood (ML) space-time decoder in the point-to-point MIMO communication case.

A Hybrid Approach to Spatial Multiplexing in Multiuser MIMO Downlinks

In the downlink of a multiuser multiple-input multiple-output (MIMO) communication system, simultaneous transmission to several users requires joint optimization of the transmitted signals. Allowing all users to have multiple antennas adds an additional degree of complexity to the problem. In this paper, we examine the case where a single base station transmits to multiple users using linear processing (beamforming) at each of the antenna arrays. We propose generalizations of several previous iterative algorithms for multiuser transmit beamforming that allow multiple antennas and multiple data streams for each user, and that take into account imperfect channel estimates at the transmitter. We then present a new hybrid algorithm that is based on coordinated transmit-receive beamforming, and combines the strengths of nonorthogonal iterative solutions with zero-forcing solutions. The problem of distributing power among the subchannels is solved by using standard bit-loading algorithms combined with the subchannel gains resulting from the zero-forcing solution. The result is a significant performance improvement over equal power distribution. At the same time, the number of iterations required to compute the final solution is reduced.

Genetic algorithms with applications in wireless communications

Genetic algorithms (GAs) are known to locate the global optimal solution provided sufficient population and/or generation is used. Practically, a near-optimal satisfactory result can be found by Gas with a limited number of generations. In wireless communications, the exhaustive searching approach is widely applied to many techniques, such as maximum likelihood decoding (MLD) and distance spectrum (DS) techniques. The complexity of the exhaustive searching approach in the MLD or the DS technique is exponential in the number of transmit antennas and the size of the signal constellation for the multiple-input multiple-output (MIMO) communication systems. If a large number of antennas and a large size of signal constellations, e.g. PSK and QAM, are employed in the MIMO systems, the exhaustive searching approach becomes impractical and time consuming. In this paper, the GAs are applied to the MLD and DS techniques to provide a near-optimal performance with a reduced computational complexity for the MIMO systems. Two different GA-based efficient searching approaches are proposed for the MLD and DS techniques, respectively. The first proposed approach is based on a GA with sharing function method, which is employed to locate the multiple solutions of the distance spectrum for the Space-time Trellis Coded Orthogonal Frequency Division Multiplexing (STTC-OFDM) systems. The second approach is the GA-based MLD that attempts to find the closest point to the transmitted signal. The proposed approach can return a satisfactory result with a good initial signal vector provided to the GA. Through simulation results, it is shown that the proposed GA-based efficient searching approaches can achieve near-optimal performance, but with a lower searching complexity comparing with the original MLD and DS techniques for the MIMO systems.

A Soft Detector with Good Performance/Complexity Trade-Off for a MIMO System

We present a hybrid soft detector that has a good performance/complexity trade-off for a multiple-input multiple-output (MIMO) wireless communication system with known channel information. The new soft detector combines the merits of a simple unstructured least-squares (LS)-based soft detector and a list sphere decoder (LSD)-based soft detector for data bit detection. The former is computationally much more efficient than the latter at the cost of poorer performance. The poor performance of the former occurs mainly when the channel matrix is ill-conditioned. Whenever this happens, we use the LSD-based soft detector in the hybrid soft detector; otherwise, we use the LS-based one. Moreover, we provide a tight radius for a sphere decoder, a hard detector, via using the output of an LS-based hard detector. These two hard detectors are needed to determine if LS or LSD should be used in the hybrid soft detector. As an application example, we consider doubling the maximum data rate of the IEEE 802.11a conformable wireless local area networks by a MIMO system with two transmit and two receive antennas. For this application, the new soft detector is about 10 times faster than the LSD-based one and is about 10 times slower than the LS-based one. Yet the packet error rate due to using the new soft detector is quite close to that of using the LSD-based one.

Optimization of Nonlinear Signal Constellations for Real-World MIMO Channels

The performance of spatial multiplexing (SM) multiple-input multiple-output (MIMO) communication systems is highly dependent on the richness of scattering, the presence of dominant components, and the interelement spacings. In this paper, a new interpretation of the impact of transmit correlation on the performance of SM is given based on a so-called "symbol-related array factor." Nonlinear signal constellations for SM over real-world fading channels are then designed by minimizing an estimate of the average symbol error rate under an average transmit power constraint. The new transmission scheme exploits the spectral efficiency advantage of SM and the robustness of eigen-beamforming. Through simulations, it is shown to be more robust against fading correlations and high Ricean K-factors than SM using the classical phase shift keying (PSK) and quadrature amplitude modulation (QAM) constellations. The symbol error rate performance of this scheme is not affected by a change in the propagation environment or the interelement distance. Furthermore, if the scheme is used on the uplink, no explicit rate-consuming feedback link from the base station to the mobile station is required.

Effectiveness of Space-Division Multiple-Access in MIMO Communication Systems with Parallel Data Transmission

We consider multiple-input multiple-output (MIMO) cellular communication systems with antenna arrays at both link ends and data transmission via parallel eigenchannels matched with a random spatial channel. We analyze the effectiveness of the space-division multiple-access (SDMA) method, which does not require estimation of signal-arrival directions and is based on orthogonalization of the parallel channels of all users. We obtained approximate analytical expressions for the mean ratio of the signal power to the noise power and the MIMO system capacity, which are derived for the case of Rayleigh fading of signals. Although the obtained formulas are much simpler than the exact ones, they ensure high accuracy for an arbitrary number of transmitting and receiving antennas and an arbitrary power of transmitter. Our results demonstrate the high effectiveness of the proposed SDMA method.

Space Division Multiple Access in MIMO Systems with Parallel Data Transmission

We study multiple-input multiple-output (MIMO) cellular communication systems with antenna arrays at both link ends and parallel channels for data transmission. These channels (the so-called eigenchannels) are formed with the help of adaptive transmitting and receiving beamformer processors matched with a random fading environment. To increase the capacity of MIMO systems, we propose a space-division multiple-access (SDMA) method, which does not require estimation of signal-arrival directions and is based on orthogonalization of the parallel channels of all users. We find the signal-to-noise ratios at the eigenchannel outputs and the total capacity of a MIMO system in the case of simultaneous servicing of an arbitrary number of users. We present numerical results for the case of Rayleigh fading of signals, which confirm the high effectiveness of the proposed SDMA method.