8,584 research outputs found
Designing Multi-User MIMO for Energy Efficiency: When is Massive MIMO the Answer?
Assume that a multi-user multiple-input multiple-output (MIMO) communication
system must be designed to cover a given area with maximal energy efficiency
(bit/Joule). What are the optimal values for the number of antennas, active
users, and transmit power? By using a new model that describes how these three
parameters affect the total energy efficiency of the system, this work provides
closed-form expressions for their optimal values and interactions. In sharp
contrast to common belief, the transmit power is found to increase (not
decrease) with the number of antennas. This implies that energy efficient
systems can operate at high signal-to-noise ratio (SNR) regimes in which the
use of interference-suppressing precoding schemes is essential. Numerical
results show that the maximal energy efficiency is achieved by a massive MIMO
setup wherein hundreds of antennas are deployed to serve relatively many users
using interference-suppressing regularized zero-forcing precoding.Comment: Published at IEEE Wireless Communications and Networking Conference
(WCNC 2014), 6 pages, 5 figures, 1 table. This version improves the visual
presentation of Fig. 2 and corrects a typo in Lemma
Massive MIMO Full-Duplex Relaying with Optimal Power Allocation for Independent Multipairs
With the help of an in-band full-duplex relay station, it is possible to
simultaneously transmit and receive signals from multiple users. The
performance of such system can be greatly increased when the relay station is
equipped with a large number of antennas on both transmitter and receiver
sides. In this paper, we exploit the use of massive arrays to effectively
suppress the loopback interference (LI) of a decode-and-forward relay (DF) and
evaluate the performance of the end-to-end (e2e) transmission. This paper
assumes imperfect channel state information is available at the relay and
designs a minimum mean-square error (MMSE) filter to mitigate the interference.
Subsequently, we adopt zero-forcing (ZF) filters for both detection and
beamforming. The performance of such system is evaluated in terms of bit error
rate (BER) at both relay and destinations, and an optimal choice for the
transmission power at the relay is shown. We then propose a complexity
efficient optimal power allocation (OPA) algorithm that, using the channel
statistics, computes the minimum power that satisfies the rate constraints of
each pair. The results obtained via simulation show that when both MMSE
filtering and OPA method are used, better values for the energy efficiency are
attained.Comment: Accepted to the 16th IEEE International Workshop on Signal Processing
Advances in Wireless Communications - SPAWC, Stockholm, Sweden 201
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