Sum rate maximization for uplink distributed massive MIMO systems with limited backhaul capacity

We investigated the uplink sum rate maximization for Distributed Massive MIMO (DM-MIMO) system with limited backhaul capacity. In this system, a number of single antenna autonomous terminals simultaneously transmit data streams to a group of distributed Remote Radio Heads (RRH). These RRHs are connected to a Central Unit (CU) via links with limited capacity. Each RRH quantizes the signal received by each of its antennas and forwards the bits to the backhaul. In this paper we first derive uplink achievable sum rate of the DM-MIMO system under limited backhaul capacity. Due to the complexity of the derived sum rate, an estimation is presented considering the massive MIMO context. This estimated sum rate is verified numerically. Then we show that even if backhaul capacity is limited, DM-MIMO can outperform the centralized case. Finally the sum rate maximization problem for DM-MIMO is formulated and simplified version of the problem is solved.

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

[2]  Tiejun Lv,et al.  An ESPRIT-Based Approach for 2-D Localization of Incoherently Distributed Sources in Massive MIMO Systems , 2014, IEEE Journal of Selected Topics in Signal Processing.

[3]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[4]  Min Chen,et al.  Distributed Antenna Systems: Open Architecture for Future Wireless Communications , 2006 .

[5]  Giuseppe Caire,et al.  Scalable Synchronization and Reciprocity Calibration for Distributed Multiuser MIMO , 2013, IEEE Transactions on Wireless Communications.

[6]  David Tse,et al.  Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality , 2003, IEEE Trans. Inf. Theory.

[7]  Robert W. Heath,et al.  Shifting the MIMO Paradigm , 2007, IEEE Signal Processing Magazine.

[8]  Kien T. Truong,et al.  The viability of distributed antennas for massive MIMO systems , 2013, 2013 Asilomar Conference on Signals, Systems and Computers.

[9]  Erik G. Larsson,et al.  Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems , 2011, IEEE Transactions on Communications.

[10]  T.L. Marzetta,et al.  How Much Training is Required for Multiuser Mimo? , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[11]  Xiaojun Yuan,et al.  Hermitian Precoding for Distributed MIMO Systems with Individual Channel State Information , 2013, IEEE Journal on Selected Areas in Communications.

[12]  Honglin Hu,et al.  Distributed Antenna Systems: Open Architecture for Future Wireless Communications , 2007 .

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

[14]  Erik G. Larsson,et al.  Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays , 2012, IEEE Signal Process. Mag..

[15]  Mérouane Debbah,et al.  Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need? , 2013, IEEE Journal on Selected Areas in Communications.

[16]  A. W. M. van den Enden,et al.  Discrete Time Signal Processing , 1989 .

[17]  Shlomo Shamai,et al.  On the achievable throughput of a multiantenna Gaussian broadcast channel , 2003, IEEE Transactions on Information Theory.