Multi-pair massive MIMO relay networks: power scaling laws and user scheduling strategy

This study studies a multi-pair massive multiple-input multiple-output (MIMO) relaying network, where multiple pairs of users are served by a single relay station with a large number of antennas, and the amplify-and-forward protocol and zero-forcing (ZF) beamforming are used at the relay. The authors investigate the ergodic achievable rates for the users and obtain tight approximations in closed form for finite number of antennas. The rate performance and power efficiency are studied based on the analytical results for asymptotic scenarios, and the effect of scaling factors of transmit powers for users and relay are discussed. The closed-form expressions enable us to determine the optimal user scheduling which maximizes the ergodic sum-rate for the selected pairs. A simplified user scheduling algorithm is proposed which greatly reduces the average complexity of the optimal use pair search without any rate loss. Moreover, the complexity reduction for the proposed algorithm increases nonlinearly with the increase of the number of user pairs, which indicates that the simplified scheduling algorithm has notable advantages when the number of users is increased. The tightness for the analytical approximations and the superiority of the proposed algorithm are verified by Monte-Carlo simulation results

Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces

The use of large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements $N$ when using Massive MIMO receivers and half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs) have recently attracted attention since these can relay signals to achieve an SNR that grows as $N^2$, which seems like a major benefit. In this paper, we use a deterministic propagation model for a planar array of arbitrary size, to demonstrate that the mentioned SNR behaviors, and associated power scaling laws, only apply in the far-field. They cannot be used to study the regime where $N\to\infty$. We derive an exact channel gain expression that captures three essential near-field behaviors and use it to revisit the power scaling laws. We derive new finite asymptotic SNR limits but also conclude that these are unlikely to be approached in practice. We further prove that an IRS-aided setup cannot achieve a higher SNR than an equal-sized Massive MIMO setup, despite its faster SNR growth. We quantify analytically how much larger the IRS must be to achieve the same SNR. Finally, we show that an optimized IRS does not behave as an "anomalous" mirror but can vastly outperform that benchmark.Comment: Published in IEEE Open Journal of the Communications Society, 18 pages, 11 figures. Typo in Eq. (64) has been correcte

Hardware-Conscious Wireless Communication System Design

The work at hand is a selection of topics in efficient wireless communication system design, with topics logically divided into two groups.One group can be described as hardware designs conscious of their possibilities and limitations. In other words, it is about hardware that chooses its configuration and properties depending on the performance that needs to be delivered and the influence of external factors, with the goal of keeping the energy consumption as low as possible. Design parameters that trade off power with complexity are identified for analog, mixed signal and digital circuits, and implications of these tradeoffs are analyzed in detail. An analog front end and an LDPC channel decoder that adapt their parameters to the environment (e.g. fluctuating power level due to fading) are proposed, and it is analyzed how much power/energy these environment-adaptive structures save compared to non-adaptive designs made for the worst-case scenario. Additionally, the impact of ADC bit resolution on the energy efficiency of a massive MIMO system is examined in detail, with the goal of finding bit resolutions that maximize the energy efficiency under various system setups.In another group of themes, one can recognize systems where the system architect was conscious of fundamental limitations stemming from hardware.Put in another way, in these designs there is no attempt of tweaking or tuning the hardware. On the contrary, system design is performed so as to work around an existing and unchangeable hardware limitation. As a workaround for the problematic centralized topology, a massive MIMO base station based on the daisy chain topology is proposed and a method for signal processing tailored to the daisy chain setup is designed. In another example, a large group of cooperating relays is split into several smaller groups, each cooperatively performing relaying independently of the others. As cooperation consumes resources (such as bandwidth), splitting the system into smaller, independent cooperative parts helps save resources and is again an example of a workaround for an inherent limitation.From the analyses performed in this thesis, promising observations about hardware consciousness can be made. Adapting the structure of a hardware block to the environment can bring massive savings in energy, and simple workarounds prove to perform almost as good as the inherently limited designs, but with the limitation being successfully bypassed. As a general observation, it can be concluded that hardware consciousness pays off

Full-duplex MU-MIMO systems under the effects of non-ideal transceivers: performance analysis and power allocation optimization

Modern Technologies, particularly connectivity, increasingly support many facets of everyday life. The next generation of wireless communication systems aims to provide new advanced services and support new demands. These services are required to serve a massive number of devices and achieve higher spectral and energy efficiency, ultra-low latency, and reliable communication. The research community around the globe is still working on finding novel technologies to meet these requirements. Full duplex (FD) communications have been recognized as one of the promising wireless transmission candidates and gamechangers for the future of wireless communication and networking technologies, thanks to their ability to greatly improve spectral efficiency (SE) and dramatically enhance energy efficiency (EE). In this thesis, first, the influence of hardware impairment (HWI) on singleinput single-output (SISO) FD access point (AP) is studied. More precisely, the SE and EE when the system’s terminals have impaired transceivers are analyzed. Optimization problem for EE maximization is formulated to fulfill quality of service (QoS) and power budget constraints. An algorithm to solve the optimization problem by using the fractional programming theory and Karush–Kuhn–Tucker (KKT) conditions technique is proposed. [...