Energy efficiency of mmWave massive MIMO precoding with low-resolution DACs

With the congestion of the sub-6 GHz spectrum, the interest in massive multiple-input multiple-output (MIMO) systems operating on millimeter wave spectrum grows. In order to reduce the power consumption of such massive MIMO systems, hybrid analog/digital transceivers and application of low-resolution digital-to-analog/analog-to-digital converters have been recently proposed. In this work, we investigate the energy efficiency of quantized hybrid transmitters equipped with a fully/partially-connected phase-shifting network composed of active/passive phase-shifters and compare it to that of quantized digital precoders. We introduce a quantized single-user MIMO system model based on an additive quantization noise approximation considering realistic power consumption and loss models to evaluate the spectral and energy efficiencies of the transmit precoding methods. Simulation results show that partially-connected hybrid precoders can be more energy-efficient compared to digital precoders, while fully-connected hybrid precoders exhibit poor energy efficiency in general. Also, the topology of phase-shifting components offers an energy-spectral efficiency trade-off: active phase-shifters provide higher data rates, while passive phase-shifters maintain better energy efficiency.Comment: Published in IEEE Journal of Selected Topics in Signal Processin

A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

IEEE Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area

Low complexity detection for SC-FDE massive MIMO systems

Nowadays we continue to observe a big and fast growth of wireless com-munication usage due to the increasing number of access points, and fields of application of this technology. Furthermore, these new usages can require higher speed and better quality of service in order to create market. As example we can have: live 4K video transmission, M2M (Machine to Machine communication), IoT (Internet of Things), Tactile Internet, between many others. As a consequence of all these factors, the spectrum is getting overloaded with communications, increasing the interference and affecting the system's per-formance. Therefore a different path of ideas has been followed and the commu-nication process has been taken to the next level in 5G by the usage of big arrays of antennas and multi-stream communication (MIMO systems) which in a greater scale are called massive MIMO schemes. These systems can be combined with an SC-FDE (Single-Carrier Frequency Domain Equalization) scheme to im-prove the power efficiency due to the low envelope fluctuations. This thesis focused on the equalization in massive MIMO systems, more specifically in the FDE (Frequency Domain Equalization), studying the perfor-mance of different approaches, namely ZF (Zero Forcing), EGD (Equal Gain De-tector), MRD (Maximum Ratio Detector), IB-DFE (Iterative Block Decision Feed-back Equalizer) and a proposed receiver combining MRD (or EGD) and IB-DFE.With this approach we want to minimize the ICI (Inter Carrier Interference) in order to have almost independent data streams and to produce a low complexity code, so that the receiver's performance doesn't affect the total system's perfor-mance, with a final objective of increasing the data throughput in a great scale

Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area

Exploiting the increasing correlation of space constrained massive MIMO for CSI relaxation

In this paper, we explore low-complexity transmission in physically-constrained massive multiple-input multiple-output (MIMO) systems by means of channel state information (CSI) relaxation. In particular, we propose a strategy to take advantage of the correlation experienced by the channels of neighbour antennas when deployed in tightly packed antenna arrays. The proposed scheme is based on collecting CSI for only a subset of antennas during the pilot training stage and, subsequently, using averages of the acquired CSI for the remaining closely-spaced antennas. By doing this, the total number of radio frequency (RF) chains, for both CSI acquisition and data transmission, and the baseband signal processing are reduced, hence simplifying the overall system operation. At the same time, this impacts the quality of the channel estimation produced after the CSI acquisition process. To characterize this tradeoff, we explore the impact that the number of antennas with instantaneous CSI has on the performance, signal processing complexity, and energy efficiency of time-division duplex (TDD) systems. The analytical and simulation results presented in this paper show that the application of the proposed strategy in size-constrained antenna arrays is able to significantly enhance the energy efficiency against systems with full CSI availability, while approximately preserving their average performance

Design Exploration & Enhancements for Low Complexity Massive MIMO Detectors with High Modulation Order

Global energy consumed by communication and information technologies is expected to increase rapidly due to continuous usage of wireless standards and the expansion for their requirements [1]. In the next generation wireless communications, Multi Input and Multi Output (MIMO) systems are most promising technology to achieve high spectral efficiencies, while going past various challenges like resource and energy constraints [2]. There exists many detection algorithms like Maximum Likelihood (ML), Zero Forcing (ZF), Minimum Mean Square Error (MMSE) which have low silicon complexity but consume significant power for high-end MIMO systems, due to their high computational complexity. And then there are certain low power detection algorithms like real domain breadth first search K-best, with either conventional enumeration or Schnorr Euchner (SE) based enumeration. This improvement through either, comes with cost of comparatively high silicon complexity and sacrifices the performance in terms of detection bit error rate (BER). The complex domain equivalent may improve the BER performance but it’s dedicated algorithm ensures even higher silicon complexity. Several modifications have been performed on original complex domain K-best algorithm to decrease its high silicon complexity, retaining the better performance of the system. This work focuses on study and implementation of original real SE based K-best algorithm [3]. It also features my attempt to perform theoretical analysis of original complex domain detection algorithm, and to implement modified [4] and improved versions of complex domain to decrease its high silicon complexity, retaining BER performance. This work also focuses on exploration and implementation of past attempts on design modifications of complex domain algorithms and compare them across different attributes such as performance, computational and silicon complexity. Few system level and algorithmic level enhancements have been proposed and implemented for low complexity detectors explored. Dynamic fixed point iterative version of original real domain detector [3] has been studied and implemented, along with possible enhancements for complex domain detector. Pipelined hardware architecture of real domain SE based K-best detector [5] has also been studied as part of this work, with the intention of extending this to dynamic fixed point version and also complex domain detector