TY - JOUR
T1 - Multi-cell MIMO downlink with cell cooperation and fair scheduling
T2 - A large-system limit analysis
AU - Huh, Hoon
AU - Moon, Sung Hyun
AU - Kim, Young Tae
AU - Lee, Inkyu
AU - Caire, Giuseppe
N1 - Funding Information:
Manuscript received June 10, 2010; revised May 02, 2011; accepted July 14, 2011. Date of current version December 07, 2011. The work of G. Caire and H. Huh was supported in part by the National Science Foundation under Grant CCF 0917343. The work of I. Lee was supported by the National Research Foundation of Korea (NRF) under a grant funded by the Korean government (MEST) (2010-0017909).
PY - 2011/12
Y1 - 2011/12
N2 - We consider the downlink of a cellular network with multiple cells and multi-antenna base stations. Our model includes distance-dependent pathloss, arbitrary clusters of cooperating cells, and general "fairness" requirements. Beyond Monte Carlo simulation, no efficient computation method to evaluate the ergodic throughput of such systems has been presented, yet. Furthermore, for systems of practical size with tens of cells and hundreds of users per cell, even simulation becomes challenging. We develop an analytic framework based on the combination of results from large random matrix theory and convex optimization. This allows computationally efficient calculation of the system performance in the so-called "large system limit", i.e., in the limit of a large number of antennas per base station and a large number of users per cell, while the ratio of antennas per user is kept constant. In particular, the system ergodic throughput, subject to per-base station power constraints and to general fairness criteria, is obtained via the iterative solution of a system of fixed-point equations. Comparisons with finite-dimensional simulation results show that the large-system analysis provides remarkably accurate approximations for the actual finite-dimensional systems, even for a small number of users and base station antennas.
AB - We consider the downlink of a cellular network with multiple cells and multi-antenna base stations. Our model includes distance-dependent pathloss, arbitrary clusters of cooperating cells, and general "fairness" requirements. Beyond Monte Carlo simulation, no efficient computation method to evaluate the ergodic throughput of such systems has been presented, yet. Furthermore, for systems of practical size with tens of cells and hundreds of users per cell, even simulation becomes challenging. We develop an analytic framework based on the combination of results from large random matrix theory and convex optimization. This allows computationally efficient calculation of the system performance in the so-called "large system limit", i.e., in the limit of a large number of antennas per base station and a large number of users per cell, while the ratio of antennas per user is kept constant. In particular, the system ergodic throughput, subject to per-base station power constraints and to general fairness criteria, is obtained via the iterative solution of a system of fixed-point equations. Comparisons with finite-dimensional simulation results show that the large-system analysis provides remarkably accurate approximations for the actual finite-dimensional systems, even for a small number of users and base station antennas.
KW - Asymptotic analysis
KW - fairness scheduling
KW - inter-cell cooperation
KW - large-system limit
KW - multicell MIMO downlink
KW - weighted sum rate maximization
UR - http://www.scopus.com/inward/record.url?scp=83255193499&partnerID=8YFLogxK
U2 - 10.1109/TIT.2011.2170123
DO - 10.1109/TIT.2011.2170123
M3 - Article
AN - SCOPUS:83255193499
SN - 0018-9448
VL - 57
SP - 7771
EP - 7786
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
IS - 12
M1 - 6094252
ER -