Research Of Opportunity Interference Alignment And Blind Interference Alignment Technology

Interference alignment(IA) has recently emerged from the capacity analysis of interference networks, which improves capacity limits of both wireless and wired networks by conventional methods. IA is to force the direction of interfering signal fall into interference subspace to the maximum extent, while the useful signal subspace remains uncontained. While the significant degree of freedom(DoF) of IA have been shown under idealized conditions such as global knowledge of channel, bandwidth expansion, infinite resolution, high signal strengths and strong delays. However, in practical communication,there are still many challenges to meet IA. For example: the complexity of iterative IA is high; more signal space dimensions are required to achieve IA; In addition, it is also considered the effect of channel variation in practical relay system. To solve the above problems, the IA algorithm is proposed as follows:1.For high complexity of traditional iterative IA algorithm, this artical proposes a opportunity interference alignment(OIA) and the improved algorithm.OIA takes advantage of user diversity and chooses a better user to communicate, which reduces the interference leakage to achieve IA. However, the number of users for selection is less, the possibility of reducing the interference leakage is higher, which restricts the performance of IA. To solve this problem, we propose an effective user selection mechanism.To be concrete, the users calculate the interference leakage, and the base station chooses the best user. Combining pre-coding vector information with channel state information(CSI), the base station obtains better filter based on singular value decomposition(SVD) so that the direction of interference can be efficiently compressed. In addition, for the channel information is inaccurately estimated in practical system, the improved OIA is proposed to improve signal to interference and noise power ratio, which reduces the power of interference obtained by estimate.2.For the problem of spatial dimension to achieve IA and the difficulty to obtain CSI at transmitters in pratical system, blind interference alignment(BIA) for single-input single-output(SISO) system is studied in this paper. The dimension of the signal space could be increased through asymmetric complex signaling(AC signaling),which is the solution to a single antenna constraint. In addition, it is analyzed that transmitters could arbitrarily design non-zero beamforming vectors to achieve BIA without knowing CSI. Finally, based on this analysis,we show that K/ 2 DoF is achievable for K-user interference channel, which is also an outer bound with perfect CSI at transmitters.3.For the problem of the effect of channel variation and the high complexity of relay iterative IA in relay system.This paper proposes IA algorithm. Firstly, in the relay SISO system, it is analyzed that the dimension of signal space can be increased through AC signaling,which is the solution to symbol extension of relay-assisted limited channel. At the same time, it proves that the performance of the proposed scheme is the same with the performance without interference. Secondly, for the constraint and influence of the number of antenna at nodes,we study the IA algorithm in relay MIMO system. Relay designs the relay-processing matrix to minimize or eliminate the interference completely.Compared with the relay iterative IA algorithm, the complexity of the proposed scheme is lower. Finally, alternate SISO AF relaying is studied in this article to make up for the capacity pre-log factor loss of 1/2 owning to the half-duplex relaying. Furthermore, the utilization of slots and the system performance are effectively improved. And computer simulations are also provided.