Space Division Multiple Access Orthogonal Frequency Division Multiplexing Research Articles

A novel multiuser detection based on honey bees mating optimisation and tabu search algorithm for SDMA-OFDM systems

In the wireless communication systems, the classic Multi-User Detection (MUD) techniques such as the Minimum Mean Square Error (MMSE) detector have some limitations and imperfections due to Multi-Access Interference (MAI) especially in overloaded scenarios when the number of users is more than the number of receiving antennas. The optimal Maximum Likelihood (ML) detector gives an excellent result to estimate the transmitted data but suffers from a computational complexity that grows exponentially with the number of users. In this paper, we propose a new metaheuristic approach for multiuser detection based on Honey Bees Mating Optimisation (HBMO) hybridised with Tabu Search (TS) for an uplink Space Division Multiple Access-Orthogonal Frequency Division Multiplexing (SDMA-OFDM) system in a flat Rayleigh fading channel. Indeed, the HBMO algorithm provides a good estimation for TS while exploring the largest regions, while the TS algorithm uses this estimation to find the best solution of the problem. The simulation results show that the proposed algorithm HBMO-TS-MUD provides the best trade-off between performance and computational complexity comparing to the conventional detector and the other MUD detectors proposed as Genetic Algorithm hybridised with the Tabu Search (GA-TS).

A signal power adaptive regularized sphere decoding algorithm based multiuser detection technique for underdetermined OFDM/SDMA uplink system

SummaryThis work considers a regularized Fincke‐Pohst Sphere Decoder (R‐FSD) to detect the multiuser data of orthogonal frequency division multiplexing/space division multiple access (OFDM/SDMA) uplink system with underdetermined and rank‐deficient channel. Rank‐deficiency of the detected channel coefficients makes error‐free multiuser detection (MUD) a difficult task. In literature, most of the papers deal with either a determined or over‐determined full‐rank system. The method proposed in this work transforms an original ill‐posed least squares (LS) problem to a well‐posed one at the receiver, by using the standard Tikhonov regularization method. This is an efficient, direct, and less complex approach where the channel is modified using a regularization parameter that adapts to the signal power at the receiver. The result obtained is compared with maximum likelihood (ML), zero forcing (ZF), minimum mean squared error (MMSE) and ordered successive interference cancellation (OSIC) based detection techniques.

Firefly algorithm assisted multi-user detection for OFDM/SDMA uplink system

Orthogonal frequency division multiplexing/space division multiple access (OFDM/SDMA), as a technique proposed for future high data-rate requirements, is capable of achieving higher user capacity. The error free detection of the transmitted data of the users poses many challenging issues. Alternatives are explored for optimum maximum likelihood (ML) aided detection due to its exponential complexity with the number of users and constellation size. Conventional detection techniques using zero forcing (ZF) and minimum mean square error (MMSE) are less complex with much poor performance. The possibility of nature-inspired meta-heuristic algorithms to detect the user data have been of great research interest these days. With these optimisation algorithms, we can obtain almost optimum results with much reduced computational complexity. In this paper, recently developed firefly algorithm (FA) has been utilised to detect the users' transmitted data and the result has been compared with genetic algorithm (GA) and particle swarm optimisation (PSO) aided data detection.

Joint Multiple-Access Channel Effective Order and CIR Estimation Algorithm for Multi-User OFDM/SDMA System

In this paper, a novel joint estimation of channel effective order and channel impulse response (CIR) is presented for multiuser orthogonal frequency division multiplexing/space-division multiple-access (OFDM/SDMA) systems. By exploiting Akaike’s Information Criterion (AIC) as the fitness function to search the optimal order, the proposed scheme performs the channel effective order and CIR estimation in a parallel way based on differential evolution (DE) algorithm. Simulation results demonstrate that the proposed scheme is capable of attaining a better mean square error performance than the fixed channel order scheme, and improving the performance of time-domain maximum likelihood (ML) channel estimator.

Turbo Multi-User Detection for OFDM/SDMA Systems Relying on Differential Evolution Aided Iterative Channel Estimation

A differential evolution (DE) algorithm aided iterative channel estimation and turbo multi-user detection (MUD) scheme is proposed for multi-user multi-input multiple-output aided orthogonal frequency-division multiplexing / space-division multiple-access (OFDM/SDMA) systems. The proposed scheme iteratively exchanges the estimated channel information and the detected data between the channel estimator and MUD employing a turbo technique, which gradually improves the accuracy of the channel estimation and the MUD, especially for the first iteration. Quadrature amplitude modulation (QAM) is employed in most wireless standards by virtue of providing a high throughput. However, the optimal maximum likelihood (ML)-MUD becomes extremely complex for employment in QAM-aided multi-user systems. Hence, two different DE aided MUD schemes, the DE aided minimum symbol error rate (MSER)-MUD as well as the discrete DE aided ML-MUD, were developed, and their achievable performance versus complexity was characterized. The simulation results demonstrate that the proposed DE aided channel estimator is capable of approaching the Cramer-Rao lower bound with just two or three iterations. The ultimate bit error rate lower-bound of the single-user additive white Gaussian noise scenario has been approached in the range of E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> / N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> ≥ 10 dB and E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> / N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> ≥ 6 dB for the DE aided MSER-MUD and the discrete DE aided ML-MUD, respectively.

Joint Channel Estimation and Multiuser Detection for SDMA/OFDM Based on Dual Repeated Weighted Boosting Search

A joint channel estimation and multiuser detection (JCEMUD) scheme is proposed for multiuser multiple-input-multiple-output (MIMO) space-division multiple-access/orthogonal frequency-division-multiplexing (SDMA/OFDM) systems. We design a dual repeated weighted boosting search (DRWBS) scheme for JCEMUD, which is capable of providing “soft” outputs, which are directly fed to the forward error correction (FEC) decoder. The proposed DRWBS-JCEMUD scheme iteratively estimates the channel impulse responses and detects the users' transmitted signals while exploiting the error correction capability of an FEC decoder to iteratively exchange information between the detector and the estimator. Furthermore, the proposed DRWBS-JCEMUD scheme is capable of providing the log-likelihood ratios of the coded bits at low computational complexity (comparable with the single-user scenario), which can directly be fed to the FEC decoder. The simulation results demonstrate that the proposed DRWBS-JCEMUD scheme is capable of attaining a mean square error performance close to that of the ideal scenario of the least-square channel estimator associated with 100% pilot overhead and narrows the discrepancy with respect to the optimal maximum-likelihood (ML) MUD associated with perfect channel knowledge. As an example, at E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> = 10 dB, a factor-of-0.756 complexity reduction was achieved at the cost of a 1-dB performance penalty, in comparison with the ML-MUD.

Joint Decision-Directed Channel and Noise-Variance Estimation for MIMO OFDM/SDMA Systems Based on Expectation-Conditional Maximization

A joint channel impulse response (CIR) and noise-variance estimation scheme is proposed for multiuser multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing/space-division multiple access (OFDM/SDMA) systems, which is based on the expectation-conditional maximization (ECM) algorithm. Multiple users communicating over fading channels exhibiting a range of different characteristics are considered in this paper. Channel estimation becomes quite challenging in this scenario since an increased number of independent transmitter-receiver links having different statistical characteristics have to be simultaneously estimated for each subcarrier. To cope with this scenario, we design an ECM-based joint CIR and noise-variance estimator for multiuser MIMO OFDM/SDMA systems, which is capable of simultaneously estimating diverse CIRs and noise variance. Furthermore, we propose a forward error code (FEC)-aided decision-directed channel estimation scheme based on the ECM algorithm, which further improves the ECM algorithm by exploiting the error correction capability of an FEC decoder for iteratively exchanging information between the decoder and the ECM algorithm.

Capacity-aware linear MMSE detector for OFDM-SDMA systems

This paper presents a capacity-aware linear minimum mean square error (MMSE) detector for orthogonal frequency-division multiplexing/space-division multiple access (OFDM-SDMA) applications. We derive closed-form expressions for the signal-to-interference plus noise ratio (SINR) performance of OFDM-SDMA systems with linear MMSE detection method, where capacity enhancements have been introduced in the transmit/receive weight computations. Using the derived expressions, we compare the performance of the proposed scheme with the regular multiple-input multiple-output (MIMO)-MMSE system in OFDM-SDMA applications. It is shown that in enhancing the system capacity, the capacity-aware MIMO-MMSE scheme also enhances the SINR, resulting in lower symbol error rate (SER) compared to the conventional MIMO-MMSE beamforming schemes.

Receiver Cancellation Technique for Nonlinear Power Amplifier Distortion in SDMA–OFDM Systems

Space-division multiple access (SDMA) and orthogonal frequency-division multiplexing (OFDM) can be combined to design a robust communications system with increased spectral efficiency and system capacity. This combination is one of the most promising candidates for future wireless local area network implementations. However, one drawback of OFDM systems is the high peak-to-average power ratio, which imposes strong requirements on the linearity of power amplifiers (PAs). Such linearity requirements translate into high back-off that results in low power efficiency. In order to improve power efficiency, a PA nonlinearity cancellation (PANC) technique is introduced in this paper. This technique reduces the nonlinear distortion effects on the received signal. The performance of the new technique is evaluated with simulations, which show significant power efficiency improvements. To obtain meaningful results for comparison purposes, we derive a theoretical upper bound on the bit error rate performance of an SDMA-OFDM system subject to PA nonlinearities. In addition, a novel channel estimation technique that combines frequency- and time-domain channel estimation with PANC is also presented. Simulation results show the robustness of the cancellation method also when channel estimation is included.

Hybrid Iterative Multiuser Detection for Channel Coded Space Division Multiple Access OFDM Systems

Space division multiple access (SDMA) aided orthogonal frequency division multiplexing (OFDM) systems assisted by efficient multiuser detection (MUD) techniques have recently attracted intensive research interests. The maximum likelihood detection (MLD) arrangement was found to attain the best performance, although this was achieved at the cost of a computational complexity, which increases exponentially both with the number of users and with the number of bits per symbol transmitted by higher order modulation schemes. By contrast, the minimum mean-square error (MMSE) SDMA-MUD exhibits a lower complexity at the cost of a performance loss. Forward error correction (FEC) schemes such as, for example, turbo trellis coded modulation (TTCM), may be efficiently combined with SDMA-OFDM systems for the sake of improving the achievable performance. Genetic algorithm (GA) based multiuser detection techniques have been shown to provide a good performance in MUD-aided code division multiple access (CDMA) systems. In this contribution, a GA-aided MMSE MUD is proposed for employment in a TTCM-assisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its optimum MLD-aided counterpart at a significantly lower complexity, especially at high user loads. Moreover, when the proposed biased Q-function based mutation (BQM) assisted iterative GA (IGA) MUD is employed, the GA-aided system's performance can be further improved, for example, by reducing the bit error ratio (BER) measured at 3 dB by about five orders of magnitude in comparison to the TTCM-assisted MMSE-SDMA-OFDM benchmarker system, while still maintaining modest complexity.

Iterative receiver for OFDM-SDMA system

An iterative receiver is proposed based on the EM (Expectation-Maximization) algorithm for an OFDM-SDMA (Orthogonal Frequency Division Multiplexing-Space Division Multiple Access) system. By using a few pilots in every OFDM symbol, both channel estimation and multiuser detection can be simultaneously obtained by iteration. The computer simulation results show this receiver can track channel variations and detect multiuser symbols for different number of users under time-varying multipath channels.