Spatial interference alignment under realistic scenarios

Abstract

Due to the rapid growth and the aggressive throughput requirements of current wireless networks, such as the 4th Generation (4G) cellular systems, the interference has become an issue that cannot be neglected anymore. In this context, the Interference Alignment (IA) arises as a promising technique that enables transmissions free of interference with high-spectral efficiency. However, while recent works have focused mainly on the theoretical gains that the technique could provide, this dissertation aims to go a step further and clarify some of the practical issues on the implementation of this technique in a cellular network, as well as compare it to other well-established techniques. As an initial evaluation scenario, a 3-cell network was considered, for which several realistic factors were taken into account in order to perform different analyses. The first analysis was based on channel imperfections, for which the results showed that IA is more robust than Block Diagonalization (BD) regarding the Channel State Information (CSI) errors, but both are similarly affected by the correlation among transmit antennas. The impact of uncoordinated interference was also evaluated, by modeling this interference with different covariance matrices in order to mimic several scenarios. The results showed that modifications on the IA algorithms can boost their performance, with an advantage to the approach that suppresses one stream, when the Bit Error Rate (BER) is compared. To combine both factors, the temporal channel variations were taken into account. At these set of simulations, besides the presence of an external interference, the precoders were calculated using a delayed CSI, leading to results that corroborate with the previous analyses. A recurring fact on the herein considered analyses was the dilemma of weather to apply the Joint Processing (JP)-based algorithms in order to achieve higher sum capacities or to send the information through a more reliable link by using IA. A reasonable step towards solving this dilemma is to actually perform the packet transmissions, which was accomplished by employing a system-level simulator composed by a large number of Transmission Points (TPs). As a result, all analyses conducted with this simulator showed that the IA technique can provide an intermediate performance between the non-cooperation and the full cooperation scheme. Concluding, one of the main contributions of this work has been to show some scenarios/cases where the IA technique can be applied. For instance, when the CSI is not reliable it can be better to use IA than a JP-based scheme. Also, the modifications on the algorithms to take into account the external interference can boost their performance. Finally, the IA technique finds itself in-between the conventional transmissions and Coordinated Multi-Point (CoMP). IA achieves an intermediate performance, while requiring a certain degree of cooperation among the neighboring sectors, but demanding less infrastructure than the JP-based schemes.