Optimal Multiuser Diversity in Multi-Cell MIMO Uplink Networks: User Scaling Law and Beamforming Design

We introduce a distributed protocol to achieve multiuser diversity in a multicell multiple-input multiple-output (MIMO) uplink network, referred to as a MIMO interfering multiple-access channel (IMAC). Assuming both no information exchange among base stations (BS) and local channel state information at the transmitters for the MIMO IMAC, we propose a joint beamforming and user scheduling protocol, and then show that the proposed protocol can achieve the optimal multiuser diversity gain, i.e., KMlog(SNRlog N), as long as the number of mobile stations (MSs) in a cell, N, scales faster than SNR K M − L 1 − ϵ for a small constant ϵ > 0, where M, L, K, and SNR denote the number of receive antennas at each BS, the number of transmit antennas at each MS, the number of cells, and the signal-to-noise ratio, respectively. Our result indicates that multiuser diversity can be achieved in the presence of intra-cell and inter-cell interference even in a distributed fashion. As a result, vital information on how to design distributed algorithms in interference-limited cellular environments is provided.

[1]  Arogyaswami Paulraj,et al.  Opportunistic Interference Alignment for MIMO Interfering Multiple-Access Channels , 2013, IEEE Transactions on Wireless Communications.

[2]  Hon Tat Hui,et al.  Multi-Cell Random Beamforming: Achievable Rate and Degrees of Freedom Region , 2012, IEEE Transactions on Signal Processing.

[3]  Syed Ali Jafar,et al.  A Distributed Numerical Approach to Interference Alignment and Applications to Wireless Interference Networks , 2011, IEEE Transactions on Information Theory.

[4]  Wan Choi,et al.  Multi-user diversity in a spectrum sharing system , 2009, IEEE Transactions on Wireless Communications.

[5]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channels with partial side information , 2005, IEEE Transactions on Information Theory.

[6]  Bang Chul Jung,et al.  On the multiuser diversity in SIMO interfering multiple access channels: Distributed user scheduling framework , 2015, Journal of Communications and Networks.

[7]  Bang Chul Jung,et al.  Can One Achieve Multiuser Diversity in Uplink Multi-Cell Networks? , 2012, IEEE Transactions on Communications.

[8]  Sae-Young Chung,et al.  Parallel Opportunistic Routing in Wireless Networks , 2009, IEEE Transactions on Information Theory.

[9]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[10]  Bang Chul Jung,et al.  On the joint design of beamforming and user scheduling in multi-cell MIMO uplink networks , 2014, 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC).

[11]  Thomas L. Marzetta,et al.  Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas , 2010, IEEE Transactions on Wireless Communications.

[12]  Arogyaswami Paulraj,et al.  Opportunistic Downlink Interference Alignment for Multi-Cell MIMO Networks , 2017, IEEE Transactions on Wireless Communications.

[13]  Kwang Bok Lee,et al.  Distributed user selection scheme for uplink multiuser MIMO systems in a multicell environment , 2012, EURASIP J. Wirel. Commun. Netw..

[14]  David Tse,et al.  Opportunistic beamforming using dumb antennas , 2002, IEEE Trans. Inf. Theory.

[15]  Raymond Knopp,et al.  Information capacity and power control in single-cell multiuser communications , 1995, Proceedings IEEE International Conference on Communications ICC '95.

[16]  Donald E. Knuth,et al.  Big Omicron and big Omega and big Theta , 1976, SIGA.