13 research outputs found
Asymptotic Analysis of Distributed Multi-cell Beamforming
International audienceWe consider the problem of multi-cell downlink beamforming with N cells and K terminals per cell. Cooperation among base stations (BSs) has been found to increase the system throughput in a multi-cell set up by mitigating inter-cell interference. Most of the previous works assume that the BSs can exchange the instantaneous channel state information (CSI) of all their user terminals (UTs) via high speed backhaul links. However, this approach quickly becomes impractical as N and K grow large. In this work, we formulate a distributed beamforming algorithm in a multi-cell scenario under the assumption that the system dimensions are large. The design objective is the minimize the total transmit power across all BSs subject to satisfying the user SINR constraints while implementing the beamformers in a distributed manner. In our algorithm, the BSs would only need to exchange the channel statistics rather than the instantaneous CSI. We make use of tools from random matrix theory to formulate the distributed algorithm. The simulation results illustrate that our algorithm closely satisfies the target SINR constraints when the number of UTs per cell grows large, while implementing the beamforming vectors in a distributed manner
An Exclusion zone for Massive MIMO With Underlay D2D Communication
Fifth generation networks will incorporate a variety of new features in
wireless networks such as data offloading, D2D communication, and Massive MIMO.
Massive MIMO is specially appealing since it achieves huge gains while enabling
simple processing like MRC receivers. It suffers, though, from a major
shortcoming refereed to as pilot contamination. In this paper we propose a
frame-work in which, a D2D underlaid Massive MIMO system is implemented and we
will prove that this scheme can reduce the pilot contamination problem while
enabling an optimization of the system spectral efficiency. The D2D
communication will help maintain the network coverage while allowing a better
channel estimation to be performed
Optimal Linear Precoding in Multi-User MIMO Systems: A Large System Analysis
We consider the downlink of a single-cell multi-user MIMO system in which the
base station makes use of antennas to communicate with single-antenna
user equipments (UEs) randomly positioned in the coverage area. In particular,
we focus on the problem of designing the optimal linear precoding for
minimizing the total power consumption while satisfying a set of target
signal-to-interference-plus-noise ratios (SINRs). To gain insights into the
structure of the optimal solution and reduce the computational complexity for
its evaluation, we analyze the asymptotic regime where and grow large
with a given ratio and make use of recent results from large system analysis to
compute the asymptotic solution. Then, we concentrate on the asymptotically
design of heuristic linear precoding techniques. Interestingly, it turns out
that the regularized zero-forcing (RZF) precoder is equivalent to the optimal
one when the ratio between the SINR requirement and the average channel
attenuation is the same for all UEs. If this condition does not hold true but
only the same SINR constraint is imposed for all UEs, then the RZF can be
modified to still achieve optimality if statistical information of the UE
positions is available at the BS. Numerical results are used to evaluate the
performance gap in the finite system regime and to make comparisons among the
precoding techniques.Comment: 6 pages, 2 figures, IEEE Global Communications Conference (GLOBECOM),
Austin, Texas, Dec. 2014. An extended version of this work is available at
http://arxiv.org/abs/1406.598
Decentralized Multi-cell Beamforming Via Large System Analysis in Correlated Channels
Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal, 201
Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition
This paper studies joint beamforming and power control in a coordinated
multicell downlink system that serves multiple users per cell to maximize the
minimum weighted signal-to-interference-plus-noise ratio. The optimal solution
and distributed algorithm with geometrically fast convergence rate are derived
by employing the nonlinear Perron-Frobenius theory and the multicell network
duality. The iterative algorithm, though operating in a distributed manner,
still requires instantaneous power update within the coordinated cluster
through the backhaul. The backhaul information exchange and message passing may
become prohibitive with increasing number of transmit antennas and increasing
number of users. In order to derive asymptotically optimal solution, random
matrix theory is leveraged to design a distributed algorithm that only requires
statistical information. The advantage of our approach is that there is no
instantaneous power update through backhaul. Moreover, by using nonlinear
Perron-Frobenius theory and random matrix theory, an effective primal network
and an effective dual network are proposed to characterize and interpret the
asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on
Wireless Communications are correcte
A Deterministic Equivalent for the Analysis of Non-Gaussian Correlated MIMO Multiple Access Channels
Large dimensional random matrix theory (RMT) has provided an efficient
analytical tool to understand multiple-input multiple-output (MIMO) channels
and to aid the design of MIMO wireless communication systems. However, previous
studies based on large dimensional RMT rely on the assumption that the transmit
correlation matrix is diagonal or the propagation channel matrix is Gaussian.
There is an increasing interest in the channels where the transmit correlation
matrices are generally nonnegative definite and the channel entries are
non-Gaussian. This class of channel models appears in several applications in
MIMO multiple access systems, such as small cell networks (SCNs). To address
these problems, we use the generalized Lindeberg principle to show that the
Stieltjes transforms of this class of random matrices with Gaussian or
non-Gaussian independent entries coincide in the large dimensional regime. This
result permits to derive the deterministic equivalents (e.g., the Stieltjes
transform and the ergodic mutual information) for non-Gaussian MIMO channels
from the known results developed for Gaussian MIMO channels, and is of great
importance in characterizing the spectral efficiency of SCNs.Comment: This paper is the revision of the original manuscript titled "A
Deterministic Equivalent for the Analysis of Small Cell Networks". We have
revised the original manuscript and reworked on the organization to improve
the presentation as well as readabilit
On Queue-Aware Power Control in Interfering Wireless Links: Heavy Traffic Asymptotic Modelling and Application in QoS Provisioning
International audienceIn this work we address the problem of power allocation for interfering transmitter-receiver pairs so that the probability that each queue length exceeds a specified threshold is fixed at a desired value. One application is satisfying QoS requirements in a dense cellular network. We deal with this problem using heavy traffic approximation techniques which lead to an asymptotic model of a (controlled) stochas-tic differential equation. The proposed power control strategy consists of allocating most of the power according to the states of the channel and a smaller fraction according to the queue lengths, for which we find a closed-form expression. We first consider a scenario where all channel realizations and queue lengths are known instantaneously to every transmitter. Then, the algorithm is extended to the case where only local SINR feedback is available and when queue length information is shared with delays among the transmitters. These models and results are also extended to the case where the transmitters are equipped with multiple antennas. Finally, the applicability in practical system settings are discussed and simulation results are provided to illustrate the performance of the proposed method