Title :
Topology Control for Effective Interference Cancellation in Multi-User MIMO Networks
Author :
Gelal, Ece ; Pelechrinis, Konstantinos ; Kim, Tae-Suk ; Broustis, Ioannis ; Krishnamurthy, Srikanth V. ; Rao, Bhaskar
Author_Institution :
Univ. of California, Riverside, CA, USA
Abstract :
In Multi-User MIMO networks, receivers decode multiple concurrent signals using Successive Interference Cancellation (SIC). With SIC a weak target signal can be deciphered in the presence of stronger interfering signals. However, this is only feasible if each strong interfering signal satisfies a signal-to-noise-plus-interference ratio (SINR) requirement. This necessitates the appropriate selection of a subset of links that can be concurrently active in each receiver´s neighborhood; in other words, a sub-topology consisting of links that can be simultaneously active in the network is to be formed. If the selected sub-topologies are of small size, the delay between the transmission opportunities on a link increases. Thus, care should be taken to form a limited number of sub-topologies. We find that the problem of constructing the minimum number of sub-topologies such that SIC decoding is successful with a desired probability threshold, is NP-hard. Given this, we propose MUSIC, a framework that greedily forms and activates sub-topologies, in a way that favors successful SIC decoding with a high probability. MUSIC also ensures that the number of selected sub-topologies is kept small. We provide both a centralized and a distributed version of our framework. We prove that our centralized version approximates the optimal solution for the considered problem. We also perform extensive simulations to demonstrate that (i) MUSIC forms a small number of sub-topologies that enable efficient SIC operations; the number of sub-topologies formed is at most 17% larger than the optimum number of topologies, discovered through exhaustive search (in small networks). (ii) MUSIC outperforms approaches that simply consider the number of antennas as a measure for determining the links that can be simultaneously active. Specifically, MUSIC provides throughput improvements of up to 4 times, as compared to such an approach, in various topological settings. The improvements can be directly att- - ributable to a significantly higher probability of correct SIC based decoding with MUSIC.
Keywords :
MIMO communication; interference suppression; probability; radio receivers; telecommunication network topology; MUSIC; NP-hard problem; SIC decoding; effective interference cancellation; multiuser MIMO networks; probability threshold; radio receiver; signal-to-noise- plus-interference ratio; sub-topologies; topology control; Antenna measurements; Decoding; Delay; Interference cancellation; MIMO; Multiple signal classification; Network topology; Performance evaluation; Signal to noise ratio; Silicon carbide;
Conference_Titel :
INFOCOM, 2010 Proceedings IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-5836-3
DOI :
10.1109/INFCOM.2010.5462062