Seminar: Achieving Marzetta's Massive MIMO Rates with Not-so-Massive Number of Antennas
Giuseppe CAIRE - Ming Hsieh Department of Electrical Engineering University of Southern California
Date: July 1, 2011
Location: Eurecom - Salle des Conseils
Time-Division Duplexing (TDD) allows to estimate the downlink channels for an arbitrarily large number of base station antennas from a finite number of orthogonal pilot signals in the uplink, by exploiting channel reciprocity. Therefore, while the number of users per cell served in any time-frequency channel coherence block is necessarily limited by the number of pilot sequence dimensions available, the number of base station antennas can be made as large as desired. Based on this observation, Marzetta recently proposed a ``Massive MIMO'' scheme that achieves unprecedented system spectral efficiency in realistic conditions of user spatial distribution, distance-dependent pathloss and channel coherence time and bandwidth, using a very simple beamforming scheme. In this talk, we present an improved network-MIMO TDD architecture that achieves spectral efficiencies comparable with ``Massive MIMO'', with one order of magnitude less antennas per active user per cell. In order to carry out the performance analysis and the optimization of the proposed architecture in a clean and computationally efficient way, we consider the large-system regime where the number of users, the number of antennas, and the channel coherence block length go to infinity with fixed ratios. In this regime, we show that the simple beamforming scheme previously advocated by Marzetta performs very poorly. In contrast, our key idea consists of partitioning the users population into geographically determined ``bins'', such that all users in the same bin are statistically equivalent, and use an optimized network-MIMO architecture taylored for each bin. An overall scheduling scheme takes care of serving the different user bins in order to maximize a desired network utility function that reflects some desired notion of fairness. This results in a mixed-mode network-MIMO architecture, where different schemes, each of which is optimized for the served user bin, are multiplexed in time-frequency. The performance predicted by the large-system asymptotic analysis matches very well the finite-dimensional simulations. Overall, the system spectral efficiency obtained by the proposed architecture is similar to that achieved by ``Massive MIMO'', with a 10-fold reduction in the number of antennas at the base stations (roughly, from 500 to 50 antennas).
Achieving Marzetta's Massive MIMO Rates with Not-so-Massive Number of Antennas