Blind Known Interference Cancellation

This paper investigates interference-cancellation schemes at the receiver, in which the interference data, which is valid data intended for another receiver, is known a priori. The interference channel, however, is unknown (the blind part). Such a priori knowledge is common in wireless relay networks. For example, a relay could be relaying data that was previously transmitted by a node A. If node A is now receiving a signal from another node B, the interference from the relay is actually self-information known to node A. Besides the case of self-information, the node could also have overheard or received the interference data in a prior transmission by another node. Directly removing the known interference requires accurate estimate of the interference channel, which may be difficult in many situations. In this paper, we propose a novel scheme, Blind Known-Interference Cancellation (BKIC), to cancel known interference without interference channel information. BKIC consists of two steps. The first step combines adjacent symbols to cancel the interference, exploiting the fact that the channel coefficients are almost the same between successive symbols. After such interference cancellation, however, the signal of interest is distorted. The second step recovers the signal of interest amidst the distortion. We propose two algorithms for the critical second steps. The first algorithm (BKIC-S) is based on the principle of smoothing. It is simple and has near optimal performance in the slow fading scenario. The second algorithm (BKIC-RBP) is based on the principle of real-valued belief propagation. Since there is no loop in the Tanner graph, BKIC-RBP can achieve MAP-optimal performance with fast convergence, and has near interference-free performance even in the fast fading scenario. Both BKIC schemes outperform the traditional self-interference cancellation schemes that have perfect initial channel information by a large margin, while having lower complexities.