643 research outputs found
On the Performance of the Relay-ARQ Networks
This paper investigates the performance of relay networks in the presence of
hybrid automatic repeat request (ARQ) feedback and adaptive power allocation.
The throughput and the outage probability of different hybrid ARQ protocols are
studied for independent and spatially-correlated fading channels. The results
are obtained for the cases where there is a sum power constraint on the source
and the relay or when each of the source and the relay are power-limited
individually. With adaptive power allocation, the results demonstrate the
efficiency of relay-ARQ techniques in different conditions.Comment: Accepted for publication in IEEE Trans. Veh. Technol. 201
Green communication via Type-I ARQ: Finite block-length analysis
This paper studies the effect of optimal power allocation on the performance
of communication systems utilizing automatic repeat request (ARQ). Considering
Type-I ARQ, the problem is cast as the minimization of the outage probability
subject to an average power constraint. The analysis is based on some recent
results on the achievable rates of finite-length codes and we investigate the
effect of codewords length on the performance of ARQ-based systems. We show
that the performance of ARQ protocols is (almost) insensitive to the length of
the codewords, for codewords of length channel uses. Also, optimal
power allocation improves the power efficiency of the ARQ-based systems
substantially. For instance, consider a Rayleigh fading channel, codewords of
rate 1 nats-per-channel-use and outage probability Then, with a
maximum of 2 and 3 transmissions, the implementation of power-adaptive ARQ
reduces the average power, compared to the open-loop communication setup, by 17
and 23 dB, respectively, a result which is (almost) independent of the
codewords length. Also, optimal power allocation increases the diversity gain
of the ARQ protocols considerably.Comment: Accepted for publication in GLOBECOM 201
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
A Genetic Algorithm-based Beamforming Approach for Delay-constrained Networks
In this paper, we study the performance of initial access beamforming schemes
in the cases with large but finite number of transmit antennas and users.
Particularly, we develop an efficient beamforming scheme using genetic
algorithms. Moreover, taking the millimeter wave communication characteristics
and different metrics into account, we investigate the effect of various
parameters such as number of antennas/receivers, beamforming resolution as well
as hardware impairments on the system performance. As shown, our proposed
algorithm is generic in the sense that it can be effectively applied with
different channel models, metrics and beamforming methods. Also, our results
indicate that the proposed scheme can reach (almost) the same end-to-end
throughput as the exhaustive search-based optimal approach with considerably
less implementation complexity
On the Throughput of Large-but-Finite MIMO Networks using Schedulers
This paper studies the sum throughput of the {multi-user}
multiple-input-single-output (MISO) networks in the cases with large but finite
number of transmit antennas and users. Considering continuous and bursty
communication scenarios with different users' data request probabilities, we
derive quasi-closed-form expressions for the maximum achievable throughput of
the networks using optimal schedulers. The results are obtained in various
cases with different levels of interference cancellation. Also, we develop an
efficient scheduling scheme using genetic algorithms (GAs), and evaluate the
effect of different parameters, such as channel/precoding models, number of
antennas/users, scheduling costs and power amplifiers' efficiency, on the
system performance. Finally, we use the recent results on the achievable rates
of finite block-length codes to analyze the system performance in the cases
with short packets. As demonstrated, the proposed GA-based scheduler reaches
(almost) the same throughput as in the exhaustive search-based optimal
scheduler, with substantially less implementation complexity. Moreover, the
power amplifiers' inefficiency and the scheduling delay affect the performance
of the scheduling-based systems significantly
Spatial Wireless Channel Prediction under Location Uncertainty
Spatial wireless channel prediction is important for future wireless
networks, and in particular for proactive resource allocation at different
layers of the protocol stack. Various sources of uncertainty must be accounted
for during modeling and to provide robust predictions. We investigate two
channel prediction frameworks, classical Gaussian processes (cGP) and uncertain
Gaussian processes (uGP), and analyze the impact of location uncertainty during
learning/training and prediction/testing, for scenarios where measurements
uncertainty are dominated by large-scale fading. We observe that cGP generally
fails both in terms of learning the channel parameters and in predicting the
channel in the presence of location uncertainties.\textcolor{blue}{{} }In
contrast, uGP explicitly considers the location uncertainty. Using simulated
data, we show that uGP is able to learn and predict the wireless channel
On the Performance of Millimeter Wave-based RF-FSO Links with HARQ Feedback
This paper studies the performance of hybrid radio-frequency (RF) and
free-space optical (FSO) links in the cases with and without hybrid automatic
repeat request (HARQ). Considering millimeter wave (mmwave) characteristics in
the RF link and pointing errors in the FSO link, we derive closed-form
expressions for the message decoding probabilities as well as the throughput
and the outage probability of the RF-FSO setups. We also evaluate the effect of
various parameters such as power amplifiers efficiency, different transmission
techniques in the FSO link, pointing errors in the FSO link as well as
different coherence times/symbol rates of the RF and the FSO links on the
throughput and outage probability. The results show the efficiency of the
RF-FSO links in different conditions. Moreover, the HARQ can effectively
improve the outage probability/energy efficiency, and compensate the effect of
hardware impairments in RF-FSO links.Comment: Under review in PIMRC'201
Sequential Hybrid Beamforming Design for Multi-Link mmwave Communication
In this paper, we propose a sequential hybrid beamforming design for
multi-link transmission over mmwave frequency bands. As a starting point, a
baseline data communication link is established via traditional analog
beamforming at both the BS and UE. If an extra RF chain is available at the UE,
it can continue to probe the propagation environment at the same frequencies.
In case the environment is favorable and system resources allow, a secondary
data communication link is established to enable multi-stream transmission. In
principle, the secondary link could be served by the same BS and/or one or
several other BS(s). To initialize the secondary data communication link, a
parallel beam search scheme is proposed, which helps the UE/BS to find a
suitable beam pair with given optimization criteria without interrupting the
baseline data communication. By applying the proposed two-step approach, hybrid
beamforming becomes an add-on feature that can be easily switched on over an
analog beamforming enabled system without interrupting its operation whenever
system requires. Meanwhile, the information obtained by deploying the proposed
parallel beam search scheme can also be used for deciding a back-up beam pair
if signal blockage occurs to the baseline data communication link
Joint Data Routing and Power Scheduling for Wireless Powered Communication Networks
In a wireless powered communication network (WPCN), an energy access point
supplies the energy needs of the network nodes through radio frequency wave
transmission, and the nodes store the received energy in their batteries for
their future data transmission. In this paper, we propose an online stochastic
policy that jointly controls energy transmission from the EAP to the nodes and
data transfer among the nodes. For this purpose, we first introduce a novel
perturbed Lyapunov function to address the limitations on the energy
consumption of the nodes imposed by their batteries. Then, using Lyapunov
optimization method, we propose a policy which is adaptive to any arbitrary
channel statistics in the network. Finally, we provide theoretical analysis for
the performance of the proposed policy and show that it stabilizes the network,
and the average power consumption of the network under this policy is within a
bounded gap of the minimum power level required for stabilizing the network
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