138 research outputs found
Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers
This work focuses on the downlink and uplink of large-scale single-cell
MU-MIMO systems in which the base station (BS) endowed with antennas
communicates with single-antenna user equipments (UEs). Particularly, we
aim at reducing the complexity of the linear precoder and receiver that
maximize the minimum signal-to-interference-plus-noise ratio subject to a given
power constraint. To this end, we consider the asymptotic regime in which
and grow large with a given ratio. Tools from random matrix theory (RMT)
are then used to compute, in closed form, accurate approximations for the
parameters of the optimal precoder and receiver, when imperfect channel state
information (modeled by the generic Gauss-Markov formulation form) is available
at the BS. The asymptotic analysis allows us to derive the asymptotically
optimal linear precoder and receiver that are characterized by a lower
complexity (due to the dependence on the large scale components of the channel)
and, possibly, by a better resilience to imperfect channel state information.
However, the implementation of both is still challenging as it requires fast
inversions of large matrices in every coherence period. To overcome this issue,
we apply the truncated polynomial expansion (TPE) technique to the precoding
and receiving vector of each UE and make use of RMT to determine the optimal
weighting coefficients on a per-UE basis that asymptotically solve the max-min
SINR problem. Numerical results are used to validate the asymptotic analysis in
the finite system regime and to show that the proposed TPE transceivers
efficiently mimic the optimal ones, while requiring much lower computational
complexity.Comment: 13 pages, 4 figures, submitted to IEEE Transactions on Signal
Processin
Precoder Design for Physical Layer Multicasting
This paper studies the instantaneous rate maximization and the weighted sum
delay minimization problems over a K-user multicast channel, where multiple
antennas are available at the transmitter as well as at all the receivers.
Motivated by the degree of freedom optimality and the simplicity offered by
linear precoding schemes, we consider the design of linear precoders using the
aforementioned two criteria. We first consider the scenario wherein the linear
precoder can be any complex-valued matrix subject to rank and power
constraints. We propose cyclic alternating ascent based precoder design
algorithms and establish their convergence to respective stationary points.
Simulation results reveal that our proposed algorithms considerably outperform
known competing solutions. We then consider a scenario in which the linear
precoder can be formed by selecting and concatenating precoders from a given
finite codebook of precoding matrices, subject to rank and power constraints.
We show that under this scenario, the instantaneous rate maximization problem
is equivalent to a robust submodular maximization problem which is strongly NP
hard. We propose a deterministic approximation algorithm and show that it
yields a bicriteria approximation. For the weighted sum delay minimization
problem we propose a simple deterministic greedy algorithm, which at each step
entails approximately maximizing a submodular set function subject to multiple
knapsack constraints, and establish its performance guarantee.Comment: 37 pages, 8 figures, submitted to IEEE Trans. Signal Pro
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