Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications

The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to frame multiple users per transmission and the per-antenna transmit power limitations, are addressed. To this end, the so-called frame-based precoding problem is optimally solved using the principles of physical layer multicasting to multiple co-channel groups under per-antenna constraints. In this context, a novel optimization problem that aims at maximizing the system sum rate under individual power constraints is proposed. Added to that, the formulation is further extended to include availability constraints. As a result, the high gains of the sum rate optimal design are traded off to satisfy the stringent availability requirements of satellite systems. Moreover, the throughput maximization with a granular spectral efficiency versus SINR function, is formulated and solved. Finally, a multicast-aware user scheduling policy, based on the channel state information, is developed. Thus, substantial multiuser diversity gains are gleaned. Numerical results over a realistic simulation environment exhibit as much as 30% gains over conventional systems, even for 7 users per frame, without modifying the framing structure of legacy communication standards.Comment: Accepted for publication to the IEEE Transactions on Wireless Communications, 201

Optimal Distributed Scheduling in Wireless Networks under the SINR interference model

Radio resource sharing mechanisms are key to ensuring good performance in wireless networks. In their seminal paper \cite{tassiulas1}, Tassiulas and Ephremides introduced the Maximum Weighted Scheduling algorithm, and proved its throughput-optimality. Since then, there have been extensive research efforts to devise distributed implementations of this algorithm. Recently, distributed adaptive CSMA scheduling schemes \cite{jiang08} have been proposed and shown to be optimal, without the need of message passing among transmitters. However their analysis relies on the assumption that interference can be accurately modelled by a simple interference graph. In this paper, we consider the more realistic and challenging SINR interference model. We present {\it the first distributed scheduling algorithms that (i) are optimal under the SINR interference model, and (ii) that do not require any message passing}. They are based on a combination of a simple and efficient power allocation strategy referred to as {\it Power Packing} and randomization techniques. We first devise algorithms that are rate-optimal in the sense that they perform as well as the best centralized scheduling schemes in scenarios where each transmitter is aware of the rate at which it should send packets to the corresponding receiver. We then extend these algorithms so that they reach throughput-optimality

Optimal CSMA-based Wireless Communication with Worst-case Delay and Non-uniform Sizes

Carrier Sense Multiple Access (CSMA) protocols have been shown to reach the full capacity region for data communication in wireless networks, with polynomial complexity. However, current literature achieves the throughput optimality with an exponential delay scaling with the network size, even in a simplified scenario for transmission jobs with uniform sizes. Although CSMA protocols with order-optimal average delay have been proposed for specific topologies, no existing work can provide worst-case delay guarantee for each job in general network settings, not to mention the case when the jobs have non-uniform lengths while the throughput optimality is still targeted. In this paper, we tackle on this issue by proposing a two-timescale CSMA-based data communication protocol with dynamic decisions on rate control, link scheduling, job transmission and dropping in polynomial complexity. Through rigorous analysis, we demonstrate that the proposed protocol can achieve a throughput utility arbitrarily close to its offline optima for jobs with non-uniform sizes and worst-case delay guarantees, with a tradeoff of longer maximum allowable delay