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

Performance analysis of non-linear generalised pre-coding aided spatial modulation

Developed from the recently emerged generalized pre-coding aided spatial modulation (GPSM) concept, a novel non-linear GPSM scheme based on the powerful vector perturbation philosophy is proposed, where a particular subset of receive antennas is activated and the specific activation pattern itself conveys useful implicit information in addition to the conventional modulated and perturbed symbols. Explicitly, both the infinite and finite alphabet capacities are derived for the proposed non-linear GPSM scheme. The associated complexity, energy efficiency, and error probability are also investigated. Our numerical results show that, as the only known non-linear realization within the spatial modulation family, the proposed scheme constitutes an attractive solution to the flexible design of green transceivers, since it is capable of striking a compelling compromise amongst the key performance indicators of throughput, energy consumption, complexity, and performance. In particular, in the challenging full-rank scenario, conveying information through receive antenna indices exhibits a lower complexity, a higher energy efficiency, and a better error resilience than that of the conventional arrangement