Frame Based Precoding in Satellite Communications: A Multicast Approach

In the present work, a multibeam satellite that employs aggressive frequency reuse towards increasing the offered throughput is considered. Focusing on the forward link, the goal is to employ multi-antenna signal processing techniques, namely linear precoding, to manage the inter-beam interferences. In this context, fundamental practical limitations, namely the rigid framing structure of satellite communication standards and the on-board per-antenna power constraints, are herein considered. Therefore, the concept of optimal frame based precoding under per-antenna constraints, is discussed. This consists in precoding the transmit signals without changing the underlying framing structure of the communication standard. In the present work, the connection of the frame based precoding problem with the generic signal processing problem of conveying independent sets of common data to distinct groups of users is established. This model is known as physical layer multicasting to multiple co-channel groups. Building on recent results, the weighted fair per-antenna power constrained multigroup multicast precoders are employed for frame based precoding. The throughput performance of these solutions is compared to multicast aware heuristic precoding methods over a realistic multibeam satellite scenario. Consequently, the gains of the proposed approach are quantified via extensive numerical results.Comment: Accepted for presentation at the IEEE ASMS 201

Large-Scale MIMO versus Network MIMO for Multicell Interference Mitigation

This paper compares two important downlink multicell interference mitigation techniques, namely, large-scale (LS) multiple-input multiple-output (MIMO) and network MIMO. We consider a cooperative wireless cellular system operating in time-division duplex (TDD) mode, wherein each cooperating cluster includes $B$ base-stations (BSs), each equipped with multiple antennas and scheduling $K$ single-antenna users. In an LS-MIMO system, each BS employs $BM$ antennas not only to serve its scheduled users, but also to null out interference caused to the other users within the cooperating cluster using zero-forcing (ZF) beamforming. In a network MIMO system, each BS is equipped with only $M$ antennas, but interference cancellation is realized by data and channel state information exchange over the backhaul links and joint downlink transmission using ZF beamforming. Both systems are able to completely eliminate intra-cluster interference and to provide the same number of spatial degrees of freedom per user. Assuming the uplink-downlink channel reciprocity provided by TDD, both systems are subject to identical channel acquisition overhead during the uplink pilot transmission stage. Further, the available sum power at each cluster is fixed and assumed to be equally distributed across the downlink beams in both systems. Building upon the channel distribution functions and using tools from stochastic ordering, this paper shows, however, that from a performance point of view, users experience better quality of service, averaged over small-scale fading, under an LS-MIMO system than a network MIMO system. Numerical simulations for a multicell network reveal that this conclusion also holds true with regularized ZF beamforming scheme. Hence, given the likely lower cost of adding excess number of antennas at each BS, LS-MIMO could be the preferred route toward interference mitigation in cellular networks.Comment: 13 pages, 7 figures; IEEE Journal of Selected Topics in Signal Processing, Special Issue on Signal Processing for Large-Scale MIMO Communication