2,356 research outputs found
Asymptotic Analysis of Double-Scattering Channels
We consider a multiple-input multiple-output (MIMO) multiple access channel
(MAC), where the channel between each transmitter and the receiver is modeled
by the doubly-scattering channel model. Based on novel techniques from random
matrix theory, we derive deterministic approximations of the mutual
information, the signal-to-noise-plus-interference-ratio (SINR) at the output
of the minimum-mean-square-error (MMSE) detector and the sum-rate with MMSE
detection which are almost surely tight in the large system limit. Moreover, we
derive the asymptotically optimal transmit covariance matrices. Our simulation
results show that the asymptotic analysis provides very close approximations
for realistic system dimensions.Comment: 5 pages, 2 figures, submitted to the Annual Asilomar Conference on
Signals, Systems, and Computers, Pacific Grove, CA, USA, 201
Random Beamforming over Correlated Fading Channels
We study a multiple-input multiple-output (MIMO) multiple access channel
(MAC) from several multi-antenna transmitters to a multi-antenna receiver. The
fading channels between the transmitters and the receiver are modeled by random
matrices, composed of independent column vectors with zero mean and different
covariance matrices. Each transmitter is assumed to send multiple data streams
with a random precoding matrix extracted from a Haar-distributed matrix. For
this general channel model, we derive deterministic approximations of the
normalized mutual information, the normalized sum-rate with
minimum-mean-square-error (MMSE) detection and the
signal-to-interference-plus-noise-ratio (SINR) of the MMSE decoder, which
become arbitrarily tight as all system parameters grow infinitely large at the
same speed. In addition, we derive the asymptotically optimal power allocation
under individual or sum-power constraints. Our results allow us to tackle the
problem of optimal stream control in interference channels which would be
intractable in any finite setting. Numerical results corroborate our analysis
and verify its accuracy for realistic system dimensions. Moreover, the
techniques applied in this paper constitute a novel contribution to the field
of large random matrix theory and could be used to study even more involved
channel models.Comment: 35 pages, 5 figure
Optimal Energy Allocation For Delay-Constrained Traffic Over Fading Multiple Access Channels
In this paper, we consider a multiple-access fading channel where users
transmit to a single base station (BS) within a limited number of time slots.
We assume that each user has a fixed amount of energy available to be consumed
over the transmission window. We derive the optimal energy allocation policy
for each user that maximizes the total system throughput under two different
assumptions on the channel state information. First, we consider the offline
allocation problem where the channel states are known a priori before
transmission. We solve a convex optimization problem to maximize the
sum-throughput under energy and delay constraints. Next, we consider the online
allocation problem, where the channels are causally known to the BS and obtain
the optimal energy allocation via dynamic programming when the number of users
is small. We also develop a suboptimal resource allocation algorithm whose
performance is close to the optimal one. Numerical results are presented
showing the superiority of the proposed algorithms over baseline algorithms in
various scenarios.Comment: IEEE Global Communications Conference: Wireless Communications
(Globecom2016 WC
- …