UAV-Enabled Multi-Pair Massive MIMO-NOMA Relay Systems With Low-Resolution ADCs/DACs

In this article, we consider an unmanned aerial vehicle (UAV)-enabled massive multiple-input multiple-out (MIMO) non-orthogonal multiple access (NOMA) full-duplex (FD) two-way relay (TWR) system with low-resolution analog-to-digital converters/digital-to-analog converters (ADCs/DACs), where the UAV provide services for multi-pair ground users (GUs). By employing maximum ratio combining/maximum ratio transmission (MRC/MRT), the approximate closed-form expressions for sum spectrum/energy efficiency (SE/EE) with imperfect channel state information (CSI), imperfect successive interference cancellation (SIC) and quantization noise are derived. To evaluate the effects of the parameters on system performance, the asymptotic analysis and the power scaling laws are further provided. Finally, an optimization scheme is proposed to maximize the SE of the considered system. The numerical results verify the accuracy of theoretical analysis and show that the interference and noise can be effectively eliminated by deploying large-scale antennas and applying proper power scaling law. We also demonstrate that the proposed system can obtain better SE by adjusting the height of the UAV. Moreover, the system performance is related to the ADCs/DACs quantization bits, where the SE saturation values increase by increasing number of quantization bits, while the EE first increases and then decreases. Finally, the SE/EE trade-off at low precision ADCs/DACs can be achieved by choosing the appropriate number of quantization bits, and the trade-off region grows as Rician factor increases

Optimized Training Design for Wireless Energy Transfer

Radio-frequency (RF) enabled wireless energy transfer (WET), as a promising solution to provide cost-effective and reliable power supplies for energy-constrained wireless networks, has drawn growing interests recently. To overcome the significant propagation loss over distance, employing multi-antennas at the energy transmitter (ET) to more efficiently direct wireless energy to desired energy receivers (ERs), termed \emph{energy beamforming}, is an essential technique for enabling WET. However, the achievable gain of energy beamforming crucially depends on the available channel state information (CSI) at the ET, which needs to be acquired practically. In this paper, we study the design of an efficient channel acquisition method for a point-to-point multiple-input multiple-output (MIMO) WET system by exploiting the channel reciprocity, i.e., the ET estimates the CSI via dedicated reverse-link training from the ER. Considering the limited energy availability at the ER, the training strategy should be carefully designed so that the channel can be estimated with sufficient accuracy, and yet without consuming excessive energy at the ER. To this end, we propose to maximize the \emph{net} harvested energy at the ER, which is the average harvested energy offset by that used for channel training. An optimization problem is formulated for the training design over MIMO Rician fading channels, including the subset of ER antennas to be trained, as well as the training time and power allocated. Closed-form solutions are obtained for some special scenarios, based on which useful insights are drawn on when training should be employed to improve the net transferred energy in MIMO WET systems.Comment: 30 pages, 9 figures, to appear in IEEE Trans. on Communication

Achievable Rates for Full-Duplex Massive MIMO Systems With Low-Resolution ADCs/DACs

This paper investigates the uplink and downlink achievable rates of full-duplex (FD) massive multi-input-multi-output (MIMO) systems in which low-resolution analog-to-digital converters/digital-to-analog converters (ADCs/DACs) are employed and maximum ratio combining/maximum ratio transmission processing are adopted. Then, employing an additive quantization noise model, we derive approximate expressions of the uplink and downlink achievable rates, in which the effect of the quantization error, the loop interference, and the inter-user interference is considered. The theoretical results show that using proper power scaling law and more antennas can eliminate the interference and the noise. Furthermore, under the fixed number of antennas, the uplink and downlink approximate achievable rates will become a constant, as the number of quantization bits tends to infinity. Increasing the resolution of ADCs/DACs will limitedly improve the system performance but cause excessive overhead and power consumption, so adopting low-resolution ADCs/DACs in FD massive MIMO systems is sensible

A Tutorial on Nonorthogonal Multiple Access for 5G and Beyond

Today's wireless networks allocate radio resources to users based on the orthogonal multiple access (OMA) principle. However, as the number of users increases, OMA based approaches may not meet the stringent emerging requirements including very high spectral efficiency, very low latency, and massive device connectivity. Nonorthogonal multiple access (NOMA) principle emerges as a solution to improve the spectral efficiency while allowing some degree of multiple access interference at receivers. In this tutorial style paper, we target providing a unified model for NOMA, including uplink and downlink transmissions, along with the extensions tomultiple inputmultiple output and cooperative communication scenarios. Through numerical examples, we compare the performances of OMA and NOMA networks. Implementation aspects and open issues are also detailed.Comment: 25 pages, 10 figure