To enable densely deployed base stations (BSs) or access points (APs) to serve an increasing number of users and provide diverse mobile services, we need to improve spectrum utilization in wireless communication networks. Although spectral efficiency (SE) can be enhanced via smart and dynamic resource allocation, interference has become a major impediment in improving SE. There have been numerous interference management (IM) proposals at the interfering transmitter or the victim transmitter/receiver separately or cooperatively. Moreover, the existing IM schemes rely mainly on the use of channel state information (CSI). However, in some communication scenarios, the option to adjust the interferer is not available, and, in the case of downlink transmission, it is always difficult or even impossible for the victim receiver to acquire necessary information for IM.Based on the above observations, we first propose a novel IM technique, called interference steering (IS). By making use of both CSI w.r.t. and data carried in the interfering signal, IS generates a signal to modify the spatial feature of the original interference, so that the steered interference at the victim receiver is orthogonal to its intended signal. We then apply IS to an infrastructurebased enterprise wireless local area network (WLAN) in which the same frequency band is reused by adjacent basic service sets (BSSs) with overlapping areas. With IS, multiple nearby APs could simultaneously transmit data on the same channel to their mobile stations (STAs), thus enhancing spectrum reuse. Our in-depth simulation results show that IS significantly improves network SE over existing IM schemes.

Wireless networks are usually deployed to cover more overlapping areas, experiencing severe interferences and hence making interference management essential for their viability. Interference alignment (IA) is an effective way of interference management and has thus received significant attention. With IA, at least one degree-of-freedom (DoF) should be used to place the aligned interferences. However, when multiple interferences are from one identical transmitter and to a common destination, IA is not applicable under a one-DoF cost constraint. If these interfering signals are aligned in the same direction at the interfered receiver, they will also overlap with each other at their intended receiver, thus becoming indistinguishable. Moreover, IA is realized by adjusting the spatial feature of disturbance, hence incurring co-channel interference to the interfering transmissionpair's own communication. To solve this problem, we propose cooperative IA. Instead of adjusting the spatial characteristics of all interferences, we aim to achieve IA by adjusting interferences' strength along with one or none interference's signature, based on the interactions among multiple wireless disturbances. We propose two cooperative IA schemes: cooperative IA with spacepower adjustment and cooperative IA with power adjustment. With the first method, the overall effect of all interferences is aligned in the orthogonal direction with respect to the desired signal at the interfered receiver. This method modifies the direction of one interference with a properly designed precoding vector and the strength of all interferences via power allocation. Under the second scheme, the strength of all interfering signals is modified so that the overall effect of multiple interferences is orthogonal to the desired transmission while guaranteeing the orthogonality among the interfering signals at their intended receiver. Our theoretical analysis and in-depth simulation have shown that the proposed schemes can effectively manage multiple interferences from an identical source while achieving good