14,040 research outputs found
Achieving Global Optimality for Weighted Sum-Rate Maximization in the K-User Gaussian Interference Channel with Multiple Antennas
Characterizing the global maximum of weighted sum-rate (WSR) for the K-user
Gaussian interference channel (GIC), with the interference treated as Gaussian
noise, is a key problem in wireless communication. However, due to the users'
mutual interference, this problem is in general non-convex and thus cannot be
solved directly by conventional convex optimization techniques. In this paper,
by jointly utilizing the monotonic optimization and rate profile techniques, we
develop a new framework to obtain the globally optimal power control and/or
beamforming solutions to the WSR maximization problems for the GICs with
single-antenna transmitters and single-antenna receivers (SISO), single-antenna
transmitters and multi-antenna receivers (SIMO), or multi-antenna transmitters
and single-antenna receivers (MISO). Different from prior work, this paper
proposes to maximize the WSR in the achievable rate region of the GIC directly
by exploiting the facts that the achievable rate region is a "normal" set and
the users' WSR is a "strictly increasing" function over the rate region.
Consequently, the WSR maximization is shown to be in the form of monotonic
optimization over a normal set and thus can be solved globally optimally by the
existing outer polyblock approximation algorithm. However, an essential step in
the algorithm hinges on how to efficiently characterize the intersection point
on the Pareto boundary of the achievable rate region with any prescribed "rate
profile" vector. This paper shows that such a problem can be transformed into a
sequence of signal-to-interference-plus-noise ratio (SINR) feasibility
problems, which can be solved efficiently by existing techniques. Numerical
results validate that the proposed algorithms can achieve the global WSR
maximum for the SISO, SIMO or MISO GIC.Comment: This is the longer version of a paper to appear in IEEE Transactions
on Wireless Communication
Experimental Evaluation of Large Scale WiFi Multicast Rate Control
WiFi multicast to very large groups has gained attention as a solution for
multimedia delivery in crowded areas. Yet, most recently proposed schemes do
not provide performance guarantees and none have been tested at scale. To
address the issue of providing high multicast throughput with performance
guarantees, we present the design and experimental evaluation of the Multicast
Dynamic Rate Adaptation (MuDRA) algorithm. MuDRA balances fast adaptation to
channel conditions and stability, which is essential for multimedia
applications. MuDRA relies on feedback from some nodes collected via a
light-weight protocol and dynamically adjusts the rate adaptation response
time. Our experimental evaluation of MuDRA on the ORBIT testbed with over 150
nodes shows that MuDRA outperforms other schemes and supports high throughput
multicast flows to hundreds of receivers while meeting quality requirements.
MuDRA can support multiple high quality video streams, where 90% of the nodes
report excellent or very good video quality
Robust Transmissions in Wireless Powered Multi-Relay Networks with Chance Interference Constraints
In this paper, we consider a wireless powered multi-relay network in which a
multi-antenna hybrid access point underlaying a cellular system transmits
information to distant receivers. Multiple relays capable of energy harvesting
are deployed in the network to assist the information transmission. The hybrid
access point can wirelessly supply energy to the relays, achieving multi-user
gains from signal and energy cooperation. We propose a joint optimization for
signal beamforming of the hybrid access point as well as wireless energy
harvesting and collaborative beamforming strategies of the relays. The
objective is to maximize network throughput subject to probabilistic
interference constraints at the cellular user equipment. We formulate the
throughput maximization with both the time-switching and power-splitting
schemes, which impose very different couplings between the operating parameters
for wireless power and information transfer. Although the optimization problems
are inherently non-convex, they share similar structural properties that can be
leveraged for efficient algorithm design. In particular, by exploiting
monotonicity in the throughput, we maximize it iteratively via customized
polyblock approximation with reduced complexity. The numerical results show
that the proposed algorithms can achieve close to optimal performance in terms
of the energy efficiency and throughput.Comment: 14 pages, 8 figure
Generic Multiuser Coordinated Beamforming for Underlay Spectrum Sharing
The beamforming techniques have been recently studied as possible enablers
for underlay spectrum sharing. The existing beamforming techniques have several
common limitations: they are usually system model specific, cannot operate with
arbitrary number of transmit/receive antennas, and cannot serve arbitrary
number of users. Moreover, the beamforming techniques for underlay spectrum
sharing do not consider the interference originating from the incumbent primary
system. This work extends the common underlay sharing model by incorporating
the interference originating from the incumbent system into generic combined
beamforming design that can be applied on interference, broadcast or multiple
access channels. The paper proposes two novel multiuser beamforming algorithms
for user fairness and sum rate maximization, utilizing newly derived convex
optimization problems for transmit and receive beamformers calculation in a
recursive optimization. Both beamforming algorithms provide efficient operation
for the interference, broadcast and multiple access channels, as well as for
arbitrary number of antennas and secondary users in the system. Furthermore,
the paper proposes a successive transmit/receive optimization approach that
reduces the computational complexity of the proposed recursive algorithms. The
results show that the proposed complexity reduction significantly improves the
convergence rates and can facilitate their operation in scenarios which require
agile beamformers computation.Comment: 30 pages, 5 figure
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