Superposition coding in ad-hoc networks and downlink multi-user multiple input multiple output systems

In the first part of this thesis, hierarchical modulation is used in conjunction with maximum-weight scheduling to achieve lower transmission delays. Via hierarchical modulation, the scheduled user has the option to transmit to two users simultaneously. Two problems are considered: 1) Each user generates equally important packets, 2) Packets can have four different priority levels. As long as there are high priority packets waiting in the scheduled user's queue, lower priority packets cannot be transmitted. When compared with single-layer transmission, using hierarchical modulation lowers packet transmission delays without any loss in throughput for the first problem. For the second problem, throughput gains are also achieved. The effect of multiple access interference is also investigated. It is shown that both single and two-layer schemes have similar average spatial reuse factors. In the second part, a downlink (DL) wireless communication channel is considered. The base station (BS) has common data for all users, unicast data for a set of intended users, and transmits the superposition of these messages. This setting neither falls into the non-orthogonal multiple access (NOMA) literature nor into the multi-group multicasting literature. In NOMA systems, the BS has unicast data for all users, and multiple users share same time, frequency or code resources. In multi-group multicasting, there are non-overlapping groups, each demanding a different multicast message. This paper studies precoder design for a downlink system, in which the BS simultaneously transmits common data to all users, and unicast data to a subset of users via superposition coding. The objective is to maximize the weighted sum rate (WSR). It is first shown that the precoders designed for WSR maximization and weighted minimum mean square error (WMMSE) minimization are equivalent. Secondly, as the optimal precoder for maximum WSR is hard to solve, an iterative, low complexity algorithm (named as WMMSE), based on WMMSE transmit precoders and receivers, is proposed. Another low-complexity precoder, the phase aligned zero forcing (PAZF) precoder is also introduced. The results show that both algorithms converge fast. The WMMSE algorithm outperforms both PAZF and the zero-forcing (ZF) precoder for all signal-to-noise ratio (SNR) ranges. It offers better interference management and high coherent combining gains for common data. Similarly, PAZF finds the optimal phase rotation on the ZF precoder, and increases coherent combining gains.