Robust optimization for multi-cell interfering MIMO-MAC under limited feedback

We consider a multi-cell interfering MIMO-MAC system, where each user transmits a single data stream to its desired base station (BS). First, we study the multiplexing gain of the system using two interference cancellation (IC) schemes: the coordinated zero-forcing receiver (CZFR) and the extended grouping method based IA (EGM-IA) with the perfect channel state information at transmitters (CSIT). Then, we propose two algorithms to find the IC transceivers maximizing the rate of each user. Under limited feedback, we additionally propose an algorithm to maximize the minimum worst-case rate of the users by adaptively allocating the feedback bits. Numerical results illustrate the performance of the proposed algorithms.