2,041 research outputs found
Totally Distributed Energy-Efficient Transmission in MIMO Interference Channels
In this paper, we consider the problem of maximizing the energy efficiency
(EE) for multi-input multi-output (MIMO) interference channels, subject to the
per-link power constraint. To avoid extensive information exchange among all
links, the optimization problem is formulated as a noncooperative game, where
each link maximizes its own EE. We show that this game always admits a Nash
equilibrium (NE) and the sufficient condition for the uniqueness of the NE is
derived for the case of arbitrary channel matrices, which can be checked in
practice. To reach the NE of this game, we develop a totally distributed EE
algorithm, in which each link updates its own transmit covariance matrix in a
completely distributed and asynchronous way: Some players may update their
solutions more frequently than others or even use the outdated interference
information. The sufficient conditions that guarantee the global convergence of
the proposed algorithm to the NE of the game have been given as well. We also
study the impact of the circuit power consumption on the sum-EE performance of
the proposed algorithm in the case when the links are separated sufficiently
far away. Moreover, the tradeoff between the sum-EE and the sum-spectral
efficiency (SE) is investigated with the proposed algorithm under two special
cases: 1) low transmit power constraint regime; 2) high transmit power
constraint regime. Finally, extensive simulations are conducted to evaluate the
impact of various system parameters on the system performance.Comment: 42 pages, 8 figures, accepted in TW
Wireless Cellular Networks
When aiming for achieving high spectral efficiency in wireless cellular networks, cochannel interference (CCI) becomes the dominant performancelimiting factor. This article provides a survey of CCI mitigation techniques, where both active and passive approaches are discussed in the context of both open- and closed-loop designs.More explicitly, we considered both the family of flexible frequency-reuse (FFR)-aided and dynamic channel allocation (DCA)-aided interference avoidance techniques as well as smart antenna-aided interference mitigation techniques, which may be classified as active approach
Full-Duplex Cognitive Radio: A New Design Paradigm for Enhancing Spectrum Usage
With the rapid growth of demand for ever-increasing data rate, spectrum
resources have become more and more scarce. As a promising technique to
increase the efficiency of the spectrum utilization, cognitive radio (CR)
technique has the great potential to meet such a requirement by allowing
un-licensed users to coexist in licensed bands. In conventional CR systems, the
spectrum sensing is performed at the beginning of each time slot before the
data transmission. This unfortunately results in two major problems: 1)
transmission time reduction due to sensing, and 2) sensing accuracy impairment
due to data transmission. To tackle these problems, in this paper we present a
new design paradigm for future CR by exploring the full-duplex (FD) techniques
to achieve the simultaneous spectrum sensing and data transmission. With FD
radios equipped at the secondary users (SUs), SUs can simultaneously sense and
access the vacant spectrum, and thus, significantly improve sensing
performances and meanwhile increase data transmission efficiency. The aim of
this article is to transform the promising conceptual framework into the
practical wireless network design by addressing a diverse set of challenges
such as protocol design and theoretical analysis. Several application scenarios
with FD enabled CR are elaborated, and key open research directions and novel
algorithms in these systems are discussed
Distributed Game Theoretic Optimization and Management of Multichannel ALOHA Networks
The problem of distributed rate maximization in multi-channel ALOHA networks
is considered. First, we study the problem of constrained distributed rate
maximization, where user rates are subject to total transmission probability
constraints. We propose a best-response algorithm, where each user updates its
strategy to increase its rate according to the channel state information and
the current channel utilization. We prove the convergence of the algorithm to a
Nash equilibrium in both homogeneous and heterogeneous networks using the
theory of potential games. The performance of the best-response dynamic is
analyzed and compared to a simple transmission scheme, where users transmit
over the channel with the highest collision-free utility. Then, we consider the
case where users are not restricted by transmission probability constraints.
Distributed rate maximization under uncertainty is considered to achieve both
efficiency and fairness among users. We propose a distributed scheme where
users adjust their transmission probability to maximize their rates according
to the current network state, while maintaining the desired load on the
channels. We show that our approach plays an important role in achieving the
Nash bargaining solution among users. Sequential and parallel algorithms are
proposed to achieve the target solution in a distributed manner. The
efficiencies of the algorithms are demonstrated through both theoretical and
simulation results.Comment: 34 pages, 6 figures, accepted for publication in the IEEE/ACM
Transactions on Networking, part of this work was presented at IEEE CAMSAP
201
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