3,160 research outputs found
Optimal Distributed Beamforming for MISO Interference Channels
We consider the problem of quantifying the Pareto optimal boundary in the
achievable rate region over multiple-input single-output (MISO) interference
channels, where the problem boils down to solving a sequence of convex
feasibility problems after certain transformations. The feasibility problem is
solved by two new distributed optimal beamforming algorithms, where the first
one is to parallelize the computation based on the method of alternating
projections, and the second one is to localize the computation based on the
method of cyclic projections. Convergence proofs are established for both
algorithms.Comment: 7 Pages, 6 figures, extended version for the one in Proceeding of
Asilomar, CA, 201
Optimal Distributed Beamforming for MISO Interference Channels
In this thesis, the problem of quantifying the Pareto optimal boundary of the achievable rate region is considered over multiple-input single-output(MISO)interference channels, where the problem boils down to solving a sequence of convex feasibility problems after certain transformations. The feasibility problem is solved by two new distributed optimal beam forming algorithms, where the first one is to parallelize the computation based on the method of alternating projections, and the second one is to localize the computation based on the method of cyclic projections. Convergence proofs are established for both algorithms
Coordinated Beamforming with Relaxed Zero Forcing: The Sequential Orthogonal Projection Combining Method and Rate Control
In this paper, coordinated beamforming based on relaxed zero forcing (RZF)
for K transmitter-receiver pair multiple-input single-output (MISO) and
multiple-input multiple-output (MIMO) interference channels is considered. In
the RZF coordinated beamforming, conventional zero-forcing interference leakage
constraints are relaxed so that some predetermined interference leakage to
undesired receivers is allowed in order to increase the beam design space for
larger rates than those of the zero-forcing (ZF) scheme or to make beam design
feasible when ZF is impossible. In the MISO case, it is shown that the
rate-maximizing beam vector under the RZF framework for a given set of
interference leakage levels can be obtained by sequential orthogonal projection
combining (SOPC). Based on this, exact and approximate closed-form solutions
are provided in two-user and three-user cases, respectively, and an efficient
beam design algorithm for RZF coordinated beamforming is provided in general
cases. Furthermore, the rate control problem under the RZF framework is
considered. A centralized approach and a distributed heuristic approach are
proposed to control the position of the designed rate-tuple in the achievable
rate region. Finally, the RZF framework is extended to MIMO interference
channels by deriving a new lower bound on the rate of each user.Comment: Lemma 1 proof corrected; a new SOPC algorithm invented; K > N case
considere
Energy Efficient Coordinated Beamforming for Multi-cell MISO Systems
In this paper, we investigate the optimal energy efficient coordinated
beamforming in multi-cell multiple-input single-output (MISO) systems with
multiple-antenna base stations (BS) and single-antenna mobile stations
(MS), where each BS sends information to its own intended MS with cooperatively
designed transmit beamforming. We assume single user detection at the MS by
treating the interference as noise. By taking into account a realistic power
model at the BS, we characterize the Pareto boundary of the achievable energy
efficiency (EE) region of the links, where the EE of each link is defined
as the achievable data rate at the MS divided by the total power consumption at
the BS. Since the EE of each link is non-cancave (which is a non-concave
function over an affine function), characterizing this boundary is difficult.
To meet this challenge, we relate this multi-cell MISO system to cognitive
radio (CR) MISO channels by applying the concept of interference temperature
(IT), and accordingly transform the EE boundary characterization problem into a
set of fractional concave programming problems. Then, we apply the fractional
concave programming technique to solve these fractional concave problems, and
correspondingly give a parametrization for the EE boundary in terms of IT
levels. Based on this characterization, we further present a decentralized
algorithm to implement the multi-cell coordinated beamforming, which is shown
by simulations to achieve the EE Pareto boundary.Comment: 6 pages, 2 figures, to be presented in IEEE GLOBECOM 201
Coalitional Games in MISO Interference Channels: Epsilon-Core and Coalition Structure Stable Set
The multiple-input single-output interference channel is considered. Each
transmitter is assumed to know the channels between itself and all receivers
perfectly and the receivers are assumed to treat interference as additive
noise. In this setting, noncooperative transmission does not take into account
the interference generated at other receivers which generally leads to
inefficient performance of the links. To improve this situation, we study
cooperation between the links using coalitional games. The players (links) in a
coalition either perform zero forcing transmission or Wiener filter precoding
to each other. The -core is a solution concept for coalitional games
which takes into account the overhead required in coalition deviation. We
provide necessary and sufficient conditions for the strong and weak
-core of our coalitional game not to be empty with zero forcing
transmission. Since, the -core only considers the possibility of
joint cooperation of all links, we study coalitional games in partition form in
which several distinct coalitions can form. We propose a polynomial time
distributed coalition formation algorithm based on coalition merging and prove
that its solution lies in the coalition structure stable set of our coalition
formation game. Simulation results reveal the cooperation gains for different
coalition formation complexities and deviation overhead models.Comment: to appear in IEEE Transactions on Signal Processing, 14 pages, 14
figures, 3 table
Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
In cognitive radio (CR) networks, there are scenarios where the secondary
(lower priority) users intend to communicate with each other by
opportunistically utilizing the transmit spectrum originally allocated to the
existing primary (higher priority) users. For such a scenario, a secondary user
usually has to trade off between two conflicting goals at the same time: one is
to maximize its own transmit throughput; and the other is to minimize the
amount of interference it produces at each primary receiver. In this paper, we
study this fundamental tradeoff from an information-theoretic perspective by
characterizing the secondary user's channel capacity under both its own
transmit-power constraint as well as a set of interference-power constraints
each imposed at one of the primary receivers. In particular, this paper
exploits multi-antennas at the secondary transmitter to effectively balance
between spatial multiplexing for the secondary transmission and interference
avoidance at the primary receivers. Convex optimization techniques are used to
design algorithms for the optimal secondary transmit spatial spectrum that
achieves the capacity of the secondary transmission. Suboptimal solutions for
ease of implementation are also presented and their performances are compared
with the optimal solution. Furthermore, algorithms developed for the
single-channel transmission are also extended to the case of multi-channel
transmission whereby the secondary user is able to achieve opportunistic
spectrum sharing via transmit adaptations not only in space, but in time and
frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE
Journal of Special Topics in Signal Processing, special issue on Signal
Processing and Networking for Dynamic Spectrum Acces
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