MIMO Mutli-Cell Processing: Optimal Precoding and Power Allocation

We investigate the optimal power allocation and optimal precoding for a cluster of two BSs which cooperate to jointly maximize the achievable rate for two users connecting to each BS in a MCP framework. This framework is modeled by a virtual network MIMO channel due to the framework of full cooperation. In particular, due to sharing the CSI and data between the two BSs over the backhaul link. We provide a generalized fixed point equation of the optimal precoder in the asymptotic regimes of the low- and high-snr. We introduce a new iterative approach that leads to a closed-form expression for the optimal precoding matrix in the high-snr regime which is known to be an NP-hard problem. Two MCP distributed algorithms have been introduced, a power allocation algorithm for the UL, and a precoding algorithm for the DL.

[1]  Are Hjørungnes,et al.  Complex-Valued Matrix Differentiation: Techniques and Key Results , 2007, IEEE Transactions on Signal Processing.

[2]  Andrea J. Goldsmith,et al.  Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels , 2003, IEEE Trans. Inf. Theory.

[3]  Samah A. M. Ghanem.  Optimal Power Allocation and Optimal Precoding with Multi-Cell Processing , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[4]  Shlomo Shamai,et al.  Mutual information and minimum mean-square error in Gaussian channels , 2004, IEEE Transactions on Information Theory.

[5]  Antonia Maria Tulino,et al.  Mercury/waterfilling: optimum power allocation with arbitrary input constellations , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[6]  Samah A. M. Ghanem.  MAC Gaussian channels with arbitrary inputs: Optimal precoding and power allocation , 2012, 2012 International Conference on Wireless Communications and Signal Processing (WCSP).

[7]  Daniel Pérez Palomar,et al.  On optimal precoding in linear vector Gaussian channels with arbitrary input distribution , 2009, 2009 IEEE International Symposium on Information Theory.

[8]  Jeffrey G. Andrews,et al.  Fundamental Limits of Cooperation , 2012, IEEE Transactions on Information Theory.

[9]  Samah A. M. Ghanem.  Multiple Access Gaussian Channels with Arbitrary Inputs: Optimal Precoding and Power Allocation , 2014, ArXiv.

[10]  Meritxell Lamarca,et al.  Linear precoding for mutual information maximization in MIMO systems , 2009, 2009 6th International Symposium on Wireless Communication Systems.

[11]  Munnujahan Ara,et al.  Multi-cell processing with limited cooperation: A novel framework to timely designs and reduced feedback , 2016, 2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[12]  Miguel R. D. Rodrigues,et al.  MIMO Gaussian Channels With Arbitrary Inputs: Optimal Precoding and Power Allocation , 2010, IEEE Transactions on Information Theory.

[13]  J. H. Wilkinson.  Elementary proof of the Wielandt-Hoffman Theorem and of its generalization , 1970 .

[14]  Wei Yu,et al.  Multi-Cell MIMO Cooperative Networks: A New Look at Interference , 2010, IEEE Journal on Selected Areas in Communications.

[15]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[16]  Daniel Pérez Palomar,et al.  Gradient of mutual information in linear vector Gaussian channels , 2005, ISIT.

[17]  Samah A. M. Ghanem.  Piggybacking Codes for Network Coding: The High/Low SNR Regime , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.