A reconfigurable iterative algorithm for the K-user MIMO interference channel

• The algorithm adjusts itself to the interference levels and channel conditions.
• The algorithm performs interference alignment in the interference-limited regime.
• When interference is weak, the algorithm performs interference-myopic transmissions.
• Sum-rate results are presented over various asymmetric Ricean fading channels.
• The algorithm outperforms many well-known techniques for all tested cases.

Interference alignment (IA) is a recently proposed transmission technique for the K  -user interference channel (IFC), which is proven to achieve a sum-rate multiplexing gain of K/2K/2 at the high interference regime. Motivated by our recent work [1] that showed how the sum-rate scaling can range between K/2K/2 and K for moderate-to-low interference conditions, in this paper we present a novel iterative algorithm for the K-user multiple-input multiple-output (MIMO) IFC with arbitrary number of transceiver antennas. The proposed algorithm automatically adjusts itself to the interference regime at hand, in the above sense, as well as to the wireless channel in order to achieve the appropriate sum-rate scaling. Our reconfigurable algorithm combines the system-wide mean squared error minimization criterion with the single-user waterfilling solution to maximize each user's transmission rate according to the interference levels and channel conditions. Extensive computer simulation results for the sum-rate performance of the proposed reconfigurable algorithm over various Ricean fading channels are presented. It is shown that, in the interference-limited regime, the proposed algorithm reconfigures itself so as to achieve the IA scaling whereas, in the moderate-to-low interference regime, it chooses interference-myopic MIMO transmissions for all K communication pairs.