The design of channel quantization codebooks for correlated broad-cast channels with limited feedback is addressed. A design crite-rion that effectively exploits the cell statistics is proposed, based on minimizing the average sum-rate distortion in a system with joint linear beamforming and multiuser scheduling. The proposed aver-age distortion function is optimized by generating a set of quanti-zation codebooks through random trials, keeping the codebook that yields the lowest distortion. Comparisons with limited feedback ap-proaches relying on random codebooks are provided, highlighting the importance of matching the codebook design to the cell statis-tics. Numerical results show a performance gain in scenarios with non-uniform user distributions. Further, we propose a scheme that exploits the limited channel knowledge at the base station to reduce the computational complexity of determining the beamforming vec-tors and of finding the optimal user set. 1.

The design of channel quantization codebooks for correlated broad-cast channels with limited feedback is addressed. A design crite-rion that effectively exploits the cell statistics is proposed, based on minimizing the average sum-rate distortion in a system with joint linear beamforming and multiuser scheduling. The proposed aver-age distortion function is optimized by generating a set of quanti-zation codebooks through random trials, keeping the codebook that yields the lowest distortion. Comparisons with limited feedback ap-proaches relying on random codebooks are provided, highlighting the importance of matching the codebook design to the cell statis-tics. Numerical results show a performance gain in scenarios with non-uniform user distributions. Further, we propose a scheme that exploits the limited channel knowledge at the base station to reduce the computational complexity of determining the beamforming vec-tors and of finding the optimal user set. 1.