928 research outputs found
Joint Optimization of Power Allocation and Training Duration for Uplink Multiuser MIMO Communications
In this paper, we consider a multiuser multiple-input multiple-output
(MU-MIMO) communication system between a base station equipped with multiple
antennas and multiple mobile users each equipped with a single antenna. The
uplink scenario is considered. The uplink channels are acquired by the base
station through a training phase. Two linear processing schemes are considered,
namely maximum-ratio combining (MRC) and zero-forcing (ZF). We optimize the
training period and optimal training energy under the average and peak power
constraint so that an achievable sum rate is maximized.Comment: Submitted to WCN
Electromagnetic Lens-focusing Antenna Enabled Massive MIMO: Performance Improvement and Cost Reduction
Massive multiple-input multiple-output (MIMO) techniques have been recently
advanced to tremendously improve the performance of wireless communication
networks. However, the use of very large antenna arrays at the base stations
(BSs) brings new issues, such as the significantly increased hardware and
signal processing costs. In order to reap the enormous gain of massive MIMO and
yet reduce its cost to an affordable level, this paper proposes a novel system
design by integrating an electromagnetic (EM) lens with the large antenna
array, termed the EM-lens enabled MIMO. The EM lens has the capability of
focusing the power of an incident wave to a small area of the antenna array,
while the location of the focal area varies with the angle of arrival (AoA) of
the wave. Therefore, in practical scenarios where the arriving signals from
geographically separated users have different AoAs, the EM-lens enabled system
provides two new benefits, namely energy focusing and spatial interference
rejection. By taking into account the effects of imperfect channel estimation
via pilot-assisted training, in this paper we analytically show that the
average received signal-to-noise ratio (SNR) in both the single-user and
multiuser uplink transmissions can be strictly improved by the EM-lens enabled
system. Furthermore, we demonstrate that the proposed design makes it possible
to considerably reduce the hardware and signal processing costs with only
slight degradations in performance. To this end, two complexity/cost reduction
schemes are proposed, which are small-MIMO processing with parallel receiver
filtering applied over subgroups of antennas to reduce the computational
complexity, and channel covariance based antenna selection to reduce the
required number of radio frequency (RF) chains. Numerical results are provided
to corroborate our analysis.Comment: 30 pages, 9 figure
Power Allocation Schemes for Multicell Massive MIMO Systems
This paper investigates the sum-rate gains brought by power allocation
strategies in multicell massive multipleinput multiple-output systems, assuming
time-division duplex transmission. For both uplink and downlink, we derive
tractable expressions for the achievable rate with zero-forcing receivers and
precoders respectively. To avoid high complexity joint optimization across the
network, we propose a scheduling mechanism for power allocation, where in a
single time slot, only cells that do not interfere with each other adjust their
transmit powers. Based on this, corresponding transmit power allocation
strategies are derived, aimed at maximizing the sum rate per-cell. These
schemes are shown to bring considerable gains over equal power allocation for
practical antenna configurations (e.g., up to a few hundred). However, with
fixed number of users (N), these gains diminish as M turns to infinity, and
equal power allocation becomes optimal. A different conclusion is drawn for the
case where both M and N grow large together, in which case: (i) improved rates
are achieved as M grows with fixed M/N ratio, and (ii) the relative gains over
the equal power allocation diminish as M/N grows. Moreover, we also provide
applicable values of M/N under an acceptable power allocation gain threshold,
which can be used as to determine when the proposed power allocation schemes
yield appreciable gains, and when they do not. From the network point of view,
the proposed scheduling approach can achieve almost the same performance as the
joint power allocation after one scheduling round, with much reduced
complexity
Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas
The main focus and contribution of this paper is a novel network-MIMO TDD
architecture that achieves spectral efficiencies comparable with "Massive
MIMO", with one order of magnitude fewer antennas per active user per cell. The
proposed architecture is based on a family of network-MIMO schemes defined by
small clusters of cooperating base stations, zero-forcing multiuser MIMO
precoding with suitable inter-cluster interference constraints, uplink pilot
signals reuse across cells, and frequency reuse. The 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 the
optimal network-MIMO architecture in the family for each bin. A scheduler takes
care of serving the different bins on the time-frequency slots, in order to
maximize a desired network utility function that captures 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. 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. 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).Comment: Full version with appendice (proofs of theorems). A shortened version
without appendice was submitted to IEEE Trans. on Wireless Commun. Appendix B
was revised after submissio
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