Name
Abstract | ||
|---|---|---|
Interference alignment (IA) is a promising technique in wireless networks. However, existing works are mostly based on symmetric IA networks. To meet the requirements of practical applications, we consider asymmetric IA networks based on the various pathloss. In this paper, a spectrum-efficient topology management scheme is proposed for the asymmetric IA networks. In the scheme, for the user far away from others, solely adopting spatial multiplexing (SM) as a point-to-point subnetwork is more spectrum-efficient. On the other hand, for the others aggregating together, jointly comprising an IA subnetwork may be a better choice. We first present the criterion to decide which is more spectrum-efficient for the topology management scheme, i.e., IA or SM. Then, the topology management scheme is elaborated with the graph theory. In addition, the designs of the precoding and decoding matrices are presented in the IA and SM schemes, respectively. Simulation results show that the proposed topology management scheme is much more spectrum-efficient than the conventional IA scheme in the asymmetric multiuser network. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICCChina.2014.7008352 | Communications in China |
Keywords | DocType | Citations |
decoding,graph theory,interference (signal),matrix algebra,precoding,radio spectrum management,space division multiplexing,sm scheme,asymmetric interference alignment network,asymmetric multiuser network,decoding matrix,path-loss,point-to-point subnetwork,precoding matrix,spatial multiplexing,spectrum-efficient topology management scheme,symmetric ia network,wireless network,interference alignment,asymmetric multiuser networks,spectrum efficiency,topology management,interference,topology,algorithm design and analysis,signal to noise ratio,network topology,wireless communication | Conference | 3 |
PageRank | References | Authors |
0.37 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinyu Zhang | 1 | 24 | 12.48 |
| Fei Yu | 2 | 5116 | 335.58 |
| Ying He | 3 | 248 | 12.27 |
| Nan Zhao | 4 | 1591 | 123.85 |