150,723 research outputs found
Optimal power control in Cognitive MIMO systems with limited feedback
In this paper, the problem of optimal power allocation in Cognitive Radio
(CR) Multiple Input Multiple Output (MIMO) systems is treated. The focus is on
providing limited feedback solutions aiming at maximizing the secondary system
rate subject to a constraint on the average interference caused to primary
communication. The limited feedback solutions are obtained by reducing the
information available at secondary transmitter (STx) for the link between STx
and the secondary receiver (SRx) as well as by limiting the level of available
information at STx that corresponds to the link between the STx and the primary
receiver PRx. Monte Carlo simulation results are given that allow to quanitfy
the performance achieved by the proposed algorithms
Reinforcement-based data transmission in temporally-correlated fading channels: Partial CSIT scenario
Reinforcement algorithms refer to the schemes where the results of the
previous trials and a reward-punishment rule are used for parameter setting in
the next steps. In this paper, we use the concept of reinforcement algorithms
to develop different data transmission models in wireless networks. Considering
temporally-correlated fading channels, the results are presented for the cases
with partial channel state information at the transmitter (CSIT). As
demonstrated, the implementation of reinforcement algorithms improves the
performance of communication setups remarkably, with the same feedback
load/complexity as in the state-of-the-art schemes.Comment: Accepted for publication in ISWCS 201
Green Communication via Power-optimized HARQ Protocols
Recently, efficient use of energy has become an essential research topic for
green communication. This paper studies the effect of optimal power controllers
on the performance of delay-sensitive communication setups utilizing hybrid
automatic repeat request (HARQ). The results are obtained for repetition time
diversity (RTD) and incremental redundancy (INR) HARQ protocols. In all cases,
the optimal power allocation, minimizing the outage-limited average
transmission power, is obtained under both continuous and bursting
communication models. Also, we investigate the system throughput in different
conditions. The results indicate that the power efficiency is increased
substantially, if adaptive power allocation is utilized. For instance, assume
Rayleigh-fading channel, a maximum of two (re)transmission rounds with rates
nats-per-channel-use and an outage probability constraint
. Then, compared to uniform power allocation, optimal power
allocation in RTD reduces the average power by 9 and 11 dB in the bursting and
continuous communication models, respectively. In INR, these values are
obtained to be 8 and 9 dB, respectively.Comment: Accepted for publication on IEEE Transactions on Vehicular Technolog
Sparse Signal Processing Concepts for Efficient 5G System Design
As it becomes increasingly apparent that 4G will not be able to meet the
emerging demands of future mobile communication systems, the question what
could make up a 5G system, what are the crucial challenges and what are the key
drivers is part of intensive, ongoing discussions. Partly due to the advent of
compressive sensing, methods that can optimally exploit sparsity in signals
have received tremendous attention in recent years. In this paper we will
describe a variety of scenarios in which signal sparsity arises naturally in 5G
wireless systems. Signal sparsity and the associated rich collection of tools
and algorithms will thus be a viable source for innovation in 5G wireless
system design. We will discribe applications of this sparse signal processing
paradigm in MIMO random access, cloud radio access networks, compressive
channel-source network coding, and embedded security. We will also emphasize
important open problem that may arise in 5G system design, for which sparsity
will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces
Artificial-Noise-Aided Secure Multi-Antenna Transmission with Limited Feedback
We present an optimized secure multi-antenna transmission approach based on
artificial-noise-aided beamforming, with limited feedback from a desired
single-antenna receiver. To deal with beamformer quantization errors as well as
unknown eavesdropper channel characteristics, our approach is aimed at
maximizing throughput under dual performance constraints - a connection outage
constraint on the desired communication channel and a secrecy outage constraint
to guard against eavesdropping. We propose an adaptive transmission strategy
that judiciously selects the wiretap coding parameters, as well as the power
allocation between the artificial noise and the information signal. This
optimized solution reveals several important differences with respect to
solutions designed previously under the assumption of perfect feedback. We also
investigate the problem of how to most efficiently utilize the feedback bits.
The simulation results indicate that a good design strategy is to use
approximately 20% of these bits to quantize the channel gain information, with
the remainder to quantize the channel direction, and this allocation is largely
insensitive to the secrecy outage constraint imposed. In addition, we find that
8 feedback bits per transmit antenna is sufficient to achieve approximately 90%
of the throughput attainable with perfect feedback.Comment: to appear in IEEE Transactions on Wireless Communication
Thresholds Optimization for One-Bit Feedback Multi-User Scheduling
We propose a new one-bit feedback scheme with scheduling decision based on
the maximum expected weighted rate. We show the concavity of the -user case
and provide the optimal solution which achieves the maximum weighted rate of
the users. For the general asymmetric M-user case, we provide a heuristic
method to achieve the maximum expected weighted rate. We show that the sum rate
of our proposed scheme is very close to the sum rate of the full channel state
information case, which is the upper bound performance
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