Joint alignment and steering to manage interference

Abstract

In wireless communication networks, mobile users in overlapping areas may experience severe interference, therefore, designing effective Interference Management (IM) methods is crucial to improving network performance. However, when managing multiple disturbances from the same source, it may not be feasible to use existing IM methods such as Interference Alignment (IA) and Interference Steering (IS) exclusively. It is because with IA, the aligned interference becomes indistinguishable at its desired Receiver (Rx) under the cost constraint of Degrees-of-Freedom (DoF), while with IS, more transmit power will be consumed in the direct and repeated application of IS to each interference. To remedy these deficiencies, Interference Alignment Steering (IAS) is proposed by incorporating IA and IS and exploiting their advantages in IM. With IAS, the interfering Transmitter (Tx) first aligns one interference incurred by the transmission of one data stream to a one-dimensional subspace orthogonal to the desired transmission at the interfered Rx, and then the remaining interferences are treated as a whole and steered to the same subspace as the aligned interference. Moreover, two improved versions of IAS, i.e., IAS with Full Adjustment at the Interfering Tx (IAS-FAIT) and Interference Steering and Alignment (ISA), are presented. The former considers the influence of IA on the interfering user-pair's performance. The orthogonality between the desired signals at the interfered Rx can be maintained by adjusting the spatial characteristics of all interferences and the aligned interference components, thus ensuring the Spectral Efficiency (SE) of the interfering communication pairs. Under ISA, the power cost for IS at the interfered Tx is minimized, hence improving SE performance of the interfered communication-pairs. Since the proposed methods are realized at the interfering and interfered Txs cooperatively, the expenses of IM are shared by both communication-pairs. Our in-depth simulation results show that joint use of IA and IS can effectively manage multiple disturbances from the same source and improve the system's SE.