Adaptive MMSE multiuser receivers in MIMO OFDM wireless communication systems

In a bid to cope with challenges of increasing demand for higher data rate, better quality of service, and higher network capacity, there is a migration from Single Input Single Output (SISO) antenna technology to a more promising Multiple Input Multiple Output (MIMO) antenna technology. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) technique has emerged as a very popular multi-carrier modulation technique, thus it is considered as a promising solution to enhance the data rate of future broadband wireless communication systems. The first contribution of this thesis is the development of a low complexity adaptive algorithm that is robust against slow and fast fading channel scenarios, in comparison to the conventional individual parameter estimation by E. Teletar in his famous paper of 1999. Implementing the Adaptive MMSE Receivers in MIMO OFDM systems which I refer to (AMUD MIMO OFDM), combines the adaptive minimum mean square error multiuser receiver's scheme with prior information of the channel and interference cancelation in the spatial domain, achieves enhanced joint channel estimation and signal detection which makes the new technique effectively mobile. A mathematical analysis and simulation results to estimate the Information Capacity of Mobile Communication system with MMSE DFE and OFDM receivers were investigated. The capacity of a stationary channel with ISI is achievable by both the single carrier MMSE DFE and multicarrier modulation over narrow sub channels with OFDM receivers. The achieved capacity result shows that in both techniques single carrier and multicarrier, apart from different implementations are essentially identical when it comes to achievable criteria for information channel capacity. Lastly, AMUD MIMO OFDM were compared with both adaptive vector pre-coding and iterative system and their performance were fantastic, results shows that it will assure transmission over a high channel capacity

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

Channel Modelling and Estimation in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Communication Systems

In wireless communications, the demands for high data rates, enhanced mobility, improved coverage, and link reliability have enormously increased in recent years and are expected to further increase in the near future. To meet these requirements, new concepts and technologies are needed. Theoretical studies have shown that using multiple antennas at the transmitter and receiver, known as multiple-input multipleoutput (MIMO) technology, can dramatically increase the capacity, coverage, and link reliability of a communication system. Orthogonal frequency-division multiplexing (OFDM) is an attractive technique for high data rates transmission over frequency-selective fading channels, due to its capability in combating the intersymbol interference (ISI). The combination of MIMO and OFDM results in a powerful technique that incorporates the advantages of both MIMO and OFDM, and is a strong candidate for fourth generation (4G) wireless communication systems. In this thesis, two issues related to realizing practical mobile MIMO OFDM communication systems are addressed. The first issue is about MIMO channel modeling and effect of realistic channels on the theoretical capacity. For this target, a geometrically-based three-dimensional (3-D) scattering MIMO channel model is developed. The correlation expressions are derived and analytically evaluated. The impact of spatial correlation on MIMO channel capacity is investigated under different antenna array configurations, angular energy distributions, and parameters. Analytical and numerical results have shown that the elevation angle has considerable effect on the spatial correlation and consequently on the MIMO channel capacity for the case when the antenna array of the mobile station (MS) is vertically oriented. This has led to a conclusion that 3-D scattering MIMO channel modeling is necessary for accurate prediction of MIMO system performance. The second issue addressed in this thesis is the channel estimation in MIMO OFDM systems. New time-domain (TD) adaptive estimation methods based on recursive least squares (RLS) and normalized least-mean squares (NLMS) algorithms are proposed. These estimators are then extended to blindly track the time-variations of the channel in the decision-directed (DD) mode. Simulation results have shown that TD adaptive channel estimation and tracking in MIMO OFDM systems is very effective in slow to moderate time-varying fading channels. It was observed that the performance of the DD RLS-based estimator always outperform that of the DD NLMS estimator at low mobility and low SNR. In contrast, it was found that the DD NLMS estimator gives better tracking performance at moderate mobility and higher SNR. However, as the training rate is reduced, comparable performance with both estimators is obtained at high SNR. Finally, it has been shown that channel estimation in TD is more accurate with less complexity compared to its counterpart in frequency-domain (FD)

Efficient space-frequency block coded pilot-aided channel estimation method for multiple-input-multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.An iterative pilot-aided channel estimation technique for space-frequency block coded (SFBC) multiple-input multiple-output orthogonal frequency division multiplexing systems is proposed. Traditionally, when channel estimation techniques are utilised, the SFBC information signals are decoded one block at a time. In the proposed algorithm, multiple blocks of SFBC information signals are decoded simultaneously. The proposed channel estimation method can thus significantly reduce the amount of time required to decode information signals compared to similar channel estimation methods proposed in the literature. The proposed method is based on the maximum likelihood approach that offers linearity and simplicity of implementation. An expression for the pairwise error probability (PEP) is derived based on the estimated channel. The derived PEP is then used to determine the optimal power allocation for the pilot sequence. The performance of the proposed algorithm is demonstrated in high frequency selective channels, for different number of pilot symbols, using different modulation schemes. The algorithm is also tested under different levels of Doppler shift and for different number of transmit and receive antennas. The results show that the proposed scheme minimises the error margin between slow and high speed receivers compared to similar channel estimation methods in the literature.Peer reviewe

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