M-ary Coded Mouldation Assisted Genetic Algorithm Based Multiuser Detection for CDMA Systems

In this contribution we propose a novel M-ary Coded Modulation assisted Genetic Algorithm based Multiuser Detection (CM-GA-MUD) scheme for synchronous CDMA systems. The performance of the proposed scheme was investigated using Quadrature-Phase-Shift-Keying (QPSK), 8-level PSK (8PSK) and 16-level Quadrature Amplitude Modulation (16QAM) when communicating over AWGN and narrowband Rayleigh fading channels. When compared with the optimum MUD scheme, the GAMUD subsystem is capable of reducing the computational complexity significantly. On the other hand, the CM subsystem is capable of obtaining considerable coding gains despite being fed with sub-optimal information provided by the GA-MUD output

On Interference Cancellation and Iterative Techniques

Recent research activities in the area of mobile radio communications have moved to third generation (3G) cellular systems to achieve higher quality with variable transmission rate of multimedia information. In this paper, an overview is presented of various interference cancellation and iterative detection techniques that are believed to be suitable for 3G wireless communications systems. Key concepts are space-time processing and space-division multiple access (or SDMA) techniques. SDMA techniques are possible with software antennas. Furthermore, to reduce receiver implementation complexity, iterative detection techniques are considered. A particularly attractive method uses tentative hard decisions, made on the received positions with the highest reliability, according to some criterion, and can potentially yield an important reduction in the computational requirements of an iterative receiver, with minimum penalty in error performance. A study of the tradeoffs between complexity and performance loss of iterative multiuser detection techniques is a good research topic

Low-complexity dominance-based Sphere Decoder for MIMO Systems

The sphere decoder (SD) is an attractive low-complexity alternative to maximum likelihood (ML) detection in a variety of communication systems. It is also employed in multiple-input multiple-output (MIMO) systems where the computational complexity of the optimum detector grows exponentially with the number of transmit antennas. We propose an enhanced version of the SD based on an additional cost function derived from conditions on worst case interference, that we call dominance conditions. The proposed detector, the king sphere decoder (KSD), has a computational complexity that results to be not larger than the complexity of the sphere decoder and numerical simulations show that the complexity reduction is usually quite significant

High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16x16 and 32x32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.Comment: v3: Performance/complexity comparison of the proposed scheme with other large-MIMO architectures/detectors has been added (Sec. IV-D). The paper has been accepted for publication in IEEE Journal of Selected Topics in Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO Systems. v2: Section V on Channel Estimation is update

Genetically Enhanced TTCM Assisted MMSE Multi-user Detection for SDMA-OFDM

Space Division Multiple Access (SDMA) aided Orthogonal Frequency Division Multiplexing (OFDM) systems assisted by efficient Multi-User 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 Turbo Trellis Coded Modulation (TTCM) may be efficiently amalgamated 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 MLD-aided counterpart at a significantly lower complexity, especially at high user loads