286 research outputs found
Sub-Stream Fairness and Numerical Correctness in MIMO Interference Channels
Signal-to-interference plus noise ratio (SINR) and rate fairness in a system
are substantial quality-of-service (QoS) metrics. The acclaimed SINR
maximization (max-SINR) algorithm does not achieve fairness between user's
streams, i.e., sub-stream fairness is not achieved. To this end, we propose a
distributed power control algorithm to render sub-stream fairness in the
system. Sub-stream fairness is a less restrictive design metric than stream
fairness (i.e., fairness between all streams) thus sum-rate degradation is
milder. Algorithmic parameters can significantly differentiate the results of
numerical algorithms. A complete picture for comparison of algorithms can only
be depicted by varying these parameters. For example, a predetermined iteration
number or a negligible increment in the sum-rate can be the stopping criteria
of an algorithm. While the distributed interference alignment (DIA) can
reasonably achieve sub-stream fairness for the later, the imbalance between
sub-streams increases as the preset iteration number decreases. Thus comparison
of max-SINR and DIA with a low preset iteration number can only depict a part
of the picture. We analyze such important parameters and their effects on SINR
and rate metrics to exhibit numerical correctness in executing the benchmarks.
Finally, we propose group filtering schemes that jointly design the streams of
a user in contrast to max-SINR scheme that designs each stream of a user
separately.Comment: To be presented at IEEE ISWTA'1
Pareto Boundary of the Rate Region for Single-Stream MIMO Interference Channels: Linear Transceiver Design
We consider a multiple-input multiple-output (MIMO) interference channel
(IC), where a single data stream per user is transmitted and each receiver
treats interference as noise. The paper focuses on the open problem of
computing the outermost boundary (so-called Pareto boundary-PB) of the
achievable rate region under linear transceiver design. The Pareto boundary
consists of the strict PB and non-strict PB. For the two user case, we compute
the non-strict PB and the two ending points of the strict PB exactly. For the
strict PB, we formulate the problem to maximize one rate while the other rate
is fixed such that a strict PB point is reached. To solve this non-convex
optimization problem which results from the hard-coupled two transmit
beamformers, we propose an alternating optimization algorithm. Furthermore, we
extend the algorithm to the multi-user scenario and show convergence. Numerical
simulations illustrate that the proposed algorithm computes a sequence of
well-distributed operating points that serve as a reasonable and complete inner
bound of the strict PB compared with existing methods.Comment: 16 pages, 9 figures. Accepted for publication in IEEE Tans. Signal
Process. June. 201
Linear Precoding Designs for Amplify-and-Forward Multiuser Two-Way Relay Systems
Two-way relaying can improve spectral efficiency in two-user cooperative
communications. It also has great potential in multiuser systems. A major
problem of designing a multiuser two-way relay system (MU-TWRS) is transceiver
or precoding design to suppress co-channel interference. This paper aims to
study linear precoding designs for a cellular MU-TWRS where a multi-antenna
base station (BS) conducts bi-directional communications with multiple mobile
stations (MSs) via a multi-antenna relay station (RS) with amplify-and-forward
relay strategy. The design goal is to optimize uplink performance, including
total mean-square error (Total-MSE) and sum rate, while maintaining individual
signal-to-interference-plus-noise ratio (SINR) requirement for downlink
signals. We show that the BS precoding design with the RS precoder fixed can be
converted to a standard second order cone programming (SOCP) and the optimal
solution is obtained efficiently. The RS precoding design with the BS precoder
fixed, on the other hand, is non-convex and we present an iterative algorithm
to find a local optimal solution. Then, the joint BS-RS precoding is obtained
by solving the BS precoding and the RS precoding alternately. Comprehensive
simulation is conducted to demonstrate the effectiveness of the proposed
precoding designs.Comment: 13 pages, 12 figures, Accepted by IEEE TW
Linear Transceiver design for Downlink Multiuser MIMO Systems: Downlink-Interference Duality Approach
This paper considers linear transceiver design for downlink multiuser
multiple-input multiple-output (MIMO) systems. We examine different transceiver
design problems. We focus on two groups of design problems. The first group is
the weighted sum mean-square-error (WSMSE) (i.e., symbol-wise or user-wise
WSMSE) minimization problems and the second group is the minimization of the
maximum weighted mean-squareerror (WMSE) (symbol-wise or user-wise WMSE)
problems. The problems are examined for the practically relevant scenario where
the power constraint is a combination of per base station (BS) antenna and per
symbol (user), and the noise vector of each mobile station is a zero-mean
circularly symmetric complex Gaussian random variable with arbitrary covariance
matrix. For each of these problems, we propose a novel downlink-interference
duality based iterative solution. Each of these problems is solved as follows.
First, we establish a new mean-square-error (MSE) downlink-interference
duality. Second, we formulate the power allocation part of the problem in the
downlink channel as a Geometric Program (GP). Third, using the duality result
and the solution of GP, we utilize alternating optimization technique to solve
the original downlink problem. For the first group of problems, we have
established symbol-wise and user-wise WSMSE downlink-interference duality.Comment: IEEE TSP Journa
Energy-Efficient Power Control: A Look at 5G Wireless Technologies
This work develops power control algorithms for energy efficiency (EE)
maximization (measured in bit/Joule) in wireless networks. Unlike previous
related works, minimum-rate constraints are imposed and the
signal-to-interference-plus-noise ratio takes a more general expression, which
allows one to encompass some of the most promising 5G candidate technologies.
Both network-centric and user-centric EE maximizations are considered. In the
network-centric scenario, the maximization of the global EE and the minimum EE
of the network are performed. Unlike previous contributions, we develop
centralized algorithms that are guaranteed to converge, with affordable
computational complexity, to a Karush-Kuhn-Tucker point of the considered
non-convex optimization problems. Moreover, closed-form feasibility conditions
are derived. In the user-centric scenario, game theory is used to study the
equilibria of the network and to derive convergent power control algorithms,
which can be implemented in a fully decentralized fashion. Both scenarios above
are studied under the assumption that single or multiple resource blocks are
employed for data transmission. Numerical results assess the performance of the
proposed solutions, analyzing the impact of minimum-rate constraints, and
comparing the network-centric and user-centric approaches.Comment: Accepted for Publication in the IEEE Transactions on Signal
Processin
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