چكيده به لاتين
Wireless network receivers should cope with interference from undesired transmitters in addition to the ambient noise, and hence, there is a rising interest in using advanced interference mitigation techniques to improve the network performance. Traditional techniques for managing interference do not typically utilize spectrum resource efficiently. In contrast, Interference alignment (IA) can improve the throughput significantly, and make the sum of degree of freedom scale up linearly with the number of users. Therefore, IA is a promising technique to effectively manage the interference. IA has proven to be a powerful tool in characterizing the high signal to noise ratio (SNR) behavior of wireless networks. However, IA encounters limitations in practical applications because of limited SNR. In addition, perfect IA typically requires many signal dimensions. In the first part of this thesis, a single-hop general interference network where each transmitter emits an independent message and each receiver requests an arbitrary subset of the messages is being considered. An Iterative algorithm designed to minimize the leakage interference at each receiver is utilized to provide numerical insights into the feasibility of IA in these networks. Next chapter deals with the necessary and sufficient conditions on the channel structure of an interference network with time-varying fading to make perfect IA feasible within limited number of channel extensions. A new method is proposed based on the obtained conditions to achieve perfect IA, where each user can achieve at least half its interference-free capacity at any SNR. In our second proposed scheme, conditions on the channel structure of a fully connected interference network are evaluated such that part of interference becomes very strong, and perfect IA becomes feasible, and capacity gains are achieved at finite SNR values.
