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

Uplink Multiuser MIMO Detection Scheme with Reduced Computational Complexity

The wireless communication systems with multiple antennas have recently received significant attention due to their higher capacity and better immunity to fading channels as compared to single antenna systems. A fast antenna selection scheme has been introduced for the uplink multiuser multiple-input multiple-output (MIMO) detection to achieve diversity gains, but the computational complexity of the fast antenna selection scheme in multiuser systems is very high due to repetitive pseudo-inversion computations. In this paper, a new uplink multiuser detection scheme is proposed adopting a switch-and-examine combining (SEC) scheme and the Cholesky decomposition to solve the computational complexity problem. K users are considered that each users is equipped with two transmit antennas for Alamouti space-time block code (STBC) over wireless Rayleigh fading channels. Simulation results show that the computational complexity of the proposed scheme is much lower than the systems with exhaustive and fast antenna selection, while the proposed scheme does not experience the degradations of bit error rate (BER) performances

MIMO Assisted Space-Code-Division Multiple-Access: Linear Detectors and Performance over Multipath Fading Channels

In this contribution we propose and investigate a multiple-input multiple-output space-division, code-division multiple-access (MIMO SCDMA) scheme. The main objective is to improve the capacity of the existing DS-CDMA systems, for example, for supporting an increased number of users, by deploying multiple transmit and receive antennas in the corresponding systems and by using some advanced transmission and detection algorithms. In the proposed MIMO SCDMA system, each user can be distinguished jointly by its spreading code-signature and its unique channel impulse response (CIR) transfer function referred to as spatial-signature. Hence, the number of users might be supported by the MIMO SCDMA system and the corresponding achievable performance are determined by the degrees of freedom provided by both the code-signatures and the spatial-signatures, as well as by how efficiently the degrees of freedom are exploited. Specifically, the number of users supported by the proposed MIMO SCDMA can be significantly higher than the number of chips per bit, owing to the employment of space-division. In this contribution space-time spreading (STS) is employed for configuring the transmitted signals. Three types of low-complexity linear detectors, namely correlation, decorrelating and minimum mean-square error (MMSE), are considered for detecting the MIMO SCDMA signals. The BER performance of the MIMO SCDMA system associated with these linear detectors are evaluated by simulations, when assuming that the MIMO SCDMA signals are transmitted over multipath Rayleigh fading channels. Our study and simulation results show that MIMO SCDMA assisted by multiuser detection is capable of facilitating joint space-time de-spreading, multipath combining and receiver diversity combining, while simultaneously suppressing the multiuser interfering signals

SGD Frequency-Domain Space-Frequency Semiblind Multiuser Receiver with an Adaptive Optimal Mixing Parameter

A novel stochastic gradient descent frequency-domain (FD) space-frequency (SF) semiblind multiuser receiver with an adaptive optimal mixing parameter is proposed to improve performance of FD semiblind multiuser receivers with a fixed mixing parameters and reduces computational complexity of suboptimal FD semiblind multiuser receivers in SFBC downlink MIMO MC-CDMA systems where various numbers of users exist. The receiver exploits an adaptive mixing parameter to mix information ratio between the training-based mode and the blind-based mode. Analytical results prove that the optimal mixing parameter value relies on power and number of active loaded users existing in the system. Computer simulation results show that when the mixing parameter is adapted closely to the optimal mixing parameter value, the performance of the receiver outperforms existing FD SF adaptive step-size (AS) LMS semiblind based with a fixed mixing parameter and conventional FD SF AS-LMS training-based multiuser receivers in the MSE, SER and signal to interference plus noise ratio in both static and dynamic environments