DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models

The work identifies the first general, explicit, and non-random MIMO encoder-decoder structures that guarantee optimality with respect to the diversity-multiplexing tradeoff (DMT), without employing a computationally expensive maximum-likelihood (ML) receiver. Specifically, the work establishes the DMT optimality of a class of regularized lattice decoders, and more importantly the DMT optimality of their lattice-reduction (LR)-aided linear counterparts. The results hold for all channel statistics, for all channel dimensions, and most interestingly, irrespective of the particular lattice-code applied. As a special case, it is established that the LLL-based LR-aided linear implementation of the MMSE-GDFE lattice decoder facilitates DMT optimal decoding of any lattice code at a worst-case complexity that grows at most linearly in the data rate. This represents a fundamental reduction in the decoding complexity when compared to ML decoding whose complexity is generally exponential in rate. The results' generality lends them applicable to a plethora of pertinent communication scenarios such as quasi-static MIMO, MIMO-OFDM, ISI, cooperative-relaying, and MIMO-ARQ channels, in all of which the DMT optimality of the LR-aided linear decoder is guaranteed. The adopted approach yields insight, and motivates further study, into joint transceiver designs with an improved SNR gap to ML decoding.Comment: 16 pages, 1 figure (3 subfigures), submitted to the IEEE Transactions on Information Theor

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Frequency-Domain Turbo Equalisation in Coded SC-FDMA Systems: EXIT Chart Analysis and Performance

In this paper, we investigate the achievable performance of channel coded single-carrier frequency division multiple-access (SC-FDMA) systems employing various detection schemes, when communicating over frequency-selective fading channels. Specifically, three types of minimum mean-square error (MMSE) based frequency-domain (FD) turbo equalisers are considered. The first one is the turbo FD linear equaliser (LE). The second one is a parallel interference cancellation (PIC)-assisted turbo FD decision-feedback equaliser (DFE). The final one is the proposed hybrid interference cancellation (HIC)-aided turboFD-DFE, which combines successive interference cancellation (SIC) with iterative PIC and decoding. The benefit of interference cancellation (IC) is analysed with the EXtrinsic Information Transfer (EXIT) charts. The performance of the coded SC-FDMA systems employing the above-mentioned detection schemes is investigated with the aid of simulations. Our studies show that the IC techniques achieve an attractive performance at a moderate complexity

MIMO-OFCDM systems with joint iterative detection and optimal power allocation

This paper investigates the orthogonal frequency and code division multiplexing (OFCDM) systems with multiple input multiple output multiplexing (MIMO-OFCDM) and multicode transmission. Combining the iterative detection in the space domain and the hybrid multi-code interference (MDI) cancellation and minimum mean square error (MMSE) detection in the frequency domain, a joint iterative detection is proposed, which enables space and frequency diversity gains to be jointly exploited. Moreover, using a two-dimensional (2-D) averaging channel estimation algorithm, a close form expression is derived for the optimal power allocation between the pilot and all data channels that achieves the best system performance. It is shown that the optimal power ratio mainly depends on the channel estimation algorithm, the number of transmit antennas as well as the number of pilot and data symbols in a packet, but is not sensitive to the changes in signal-to-noise ratio (SNR) and diversity gains. Simulations are conducted to verify the derived optimal power ratio and study the performance of the proposed joint detection algorithm. It is shown that considerable improvement can be obtained when the number of loops in the joint iterative detection increases. Moreover, the system performance is enhanced significantly when the frequency domain spreading factor, N/sub F/, increases. © 2006 IEEE.published_or_final_versio

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