On the Capacity and Performance of Generalized Spatial Modulation

Generalized spatial modulation (GSM) uses $N$ antenna elements but fewer radio frequency (RF) chains ($R$) at the transmitter. Spatial modulation and spatial multiplexing are special cases of GSM with $R=1$ and $R=N$, respectively. In GSM, apart from conveying information bits through $R$ modulation symbols, information bits are also conveyed through the indices of the $R$ active transmit antennas. In this paper, we derive lower and upper bounds on the the capacity of a ($N,M,R$)-GSM MIMO system, where $M$ is the number of receive antennas. Further, we propose a computationally efficient GSM encoding (i.e., bits-to-signal mapping) method and a message passing based low-complexity detection algorithm suited for large-scale GSM-MIMO systems.Comment: Expanded version of the IEEE Communications Letters pape

MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity

In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Performance evaluation of detection algorithms for MOMI OFDM systems

Includes abstract.Includes bibliographical references (leaves 79-86).Introduction of Multi Input Multi Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) as the base air interface method for Next Generation Network (NGN) will face a number of challenges from hostile channel conditions to interference from other users. This would result in an increase of detection complexity required for mobile systems. Complex detection will reduce the battery life of mobile devices because of the many calculations that have to be done to decode the signal. Very powerful detection algorithms exist but they introduce high detection complexity. NGN will employ different MIMO systems, but this research will consider spatially multiplexed MIMO which is used to improve the data rate and network capacity. In NGN different multi access modulation schemes will be used for uplink and downlink but they both have OFDM as the basic building block. In this work performance of MIMO OFDM is investigated in different channels models and detection algorithms. A low complexity detection scheme is proposed in this research to improve performance of MIMO OFDM. The proposed detection scheme is investigated for different channel characteristics. Realistic channels conditions are introduced to evaluate the performance of the proposed detection scheme. We analyze weaknesses of existing linear detectors and the enhancements that can be done to improve their performance in different channel conditions. Performance of the detectors is evaluated by comparison of Bit Error Rate (BER) and Symbol Error Rate (SER) against signal to noise ratio (SNR). This thesis proposes a detector which shows a higher complexity than linear detectors but less than Maximum Likelihood Detector (MLD). The proposed detector shows significant BER improvement in all channel conditions. For better performance evaluation this work also investigates performance of MIMO OFDM detectors in realistic channels like Kronecker and Weichselberger channel models

MIMO signal processing in offset-QAM based filter bank multicarrier systems

Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft