3,018 research outputs found
Outage Performance Analysis of Multicarrier Relay Selection for Cooperative Networks
In this paper, we analyze the outage performance of two multicarrier relay
selection schemes, i.e. bulk and per-subcarrier selections, for two-hop
orthogonal frequency-division multiplexing (OFDM) systems. To provide a
comprehensive analysis, three forwarding protocols: decode-and-forward (DF),
fixed-gain (FG) amplify-and-forward (AF) and variable-gain (VG) AF relay
systems are considered. We obtain closed-form approximations for the outage
probability and closed-form expressions for the asymptotic outage probability
in the high signal-to-noise ratio (SNR) region for all cases. Our analysis is
verified by Monte Carlo simulations, and provides an analytical framework for
multicarrier systems with relay selection
Joint Resource Optimization for Multicell Networks with Wireless Energy Harvesting Relays
This paper first considers a multicell network deployment where the base
station (BS) of each cell communicates with its cell-edge user with the
assistance of an amplify-and-forward (AF) relay node. Equipped with a power
splitter and a wireless energy harvester, the self-sustaining relay scavenges
radio frequency (RF) energy from the received signals to process and forward
the information. Our aim is to develop a resource allocation scheme that
jointly optimizes (i) BS transmit powers, (ii) received power splitting factors
for energy harvesting and information processing at the relays, and (iii) relay
transmit powers. In the face of strong intercell interference and limited radio
resources, we formulate three highly-nonconvex problems with the objectives of
sum-rate maximization, max-min throughput fairness and sum-power minimization.
To solve such challenging problems, we propose to apply the successive convex
approximation (SCA) approach and devise iterative algorithms based on geometric
programming and difference-of-convex-functions programming. The proposed
algorithms transform the nonconvex problems into a sequence of convex problems,
each of which is solved very efficiently by the interior-point method. We prove
that our algorithms converge to the locally optimal solutions that satisfy the
Karush-Kuhn-Tucker conditions of the original nonconvex problems. We then
extend our results to the case of decode-and-forward (DF) relaying with
variable timeslot durations. We show that our resource allocation solutions in
this case offer better throughput than that of the AF counterpart with equal
timeslot durations, albeit at a higher computational complexity. Numerical
results confirm that the proposed joint optimization solutions substantially
improve the network performance, compared with cases where the radio resource
parameters are individually optimized
Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity
The use of unmanned aerial vehicles (UAVs) that serve as aerial base stations
is expected to become predominant in the next decade. However, in order for
this technology to unfold its full potential it is necessary to develop a
fundamental understanding of the distinctive features of air-to-ground (A2G)
links. As a contribution in this direction, this paper proposes a generic
framework for the analysis and optimization of the A2G systems. In contrast to
the existing literature, this framework incorporates both height-dependent path
loss exponent and small-scale fading, and unifies a widely used
ground-to-ground channel model with that of A2G for analysis of large-scale
wireless networks. We derive analytical expressions for the optimal UAV height
that minimizes the outage probability of a given A2G link. Moreover, our
framework allows us to derive a height-dependent closed-form expression and a
tight lower bound for the outage probability of an \textit{A2G cooperative
communication} network. Our results suggest that the optimal location of the
UAVs with respect to the ground nodes does not change by the inclusion of
ground relays. This enables interesting insights in the deployment of future
A2G networks, as the system reliability could be adjusted dynamically by adding
relaying nodes without requiring changes in the position of the corresponding
UAVs
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Cooperative smartphone relay selection based on fair power utilization for network coverage extension
This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either by providing access to out-of-range devices or by facilitating multi-path network access to connected devices. In this work, we assume that all mobile devices can benefit from using other mobile devices as relays and investigate the fairness of relay selection algorithms. We point out that signal strength based relay selection inevitably leads to unfair relay selection and devise a new algorithm that is based on fair utilization of power resources on mobile devices. We call this algorithm Credit based Fair Relay Selection (CF-RS) and in this paper show through simulation that the algorithm results in fair battery power utilization, while providing similar data rates compared with traditional approaches. We then extend the solution to demonstrate that adding incentives for relay operation adds clear value for mobile devices in the case they require relay service. Typically, mobile devices represent self-interested users who are reluctant to cooperate with other network users, mainly due to the cost in terms of power and network capacity. In this paper, we present an incentive based solution which provides clear mutual benefit for mobile devices and demonstrate this benefit in the simulation of symmetric and asymmetric network topologies. The CF-RS algorithm achieves the same performance in terms of achievable data rate, Jain's fairness index and utility of end devices in both symmetric and asymmetric network configurations
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