160 research outputs found
Wireless-powered cooperative communications: protocol design, performance analysis and resource allocation
Radio frequency (RF) energy transfer technique has attracted much attention and has recently been regarded as a key enabling technique for wireless-powered communications. However, the high attenuation of RF energy transfer over distance has greatly limited the performance and applications of WPCNs in practical scenarios. To overcome this essential hurdle, in this thesis we propose to combat the propagation attenuation by incorporating cooperative communication techniques in WPCNs. This opens a new paradigm named wireless-powered cooperative communication and raises many new research opportunities with promising applications. In this thesis, we focus on the novel protocol design, performance analysis and resource allocation of wireless-powered cooperative communication networks (WPCCNs). We first propose a harvest-then-cooperate (HTC) protocol for WPCCNs, where the wireless-powered source and relay(s) harvest energy from the AP in the downlink (DL) and work cooperatively in the uplink (UL) for transmitting source information. The average throughput performance of the HTC protocol with two single relay selection schemes is analyzed. We then design two novel protocols and study the optimal resource allocation for another setup of WPCCNs with a hybrid relay that has a constant power supply. Besides cooperating with the source for UL information transmission, the hybrid relay also transmits RF energy concurrently with the AP during the DL energy transfer phase. Subsequently, we adopt the Stackelberg game to model the strategic interactions in power beacon (PB)-assisted WPCCNs, where PBs are deployed to provide wireless charging services to wireless-powered users via RF energy transfer and are installed by different operators with the AP. Finally, we develop a distributed power splitting framework using non-cooperative game theory for a large-scale WPCCN, where multiple source-destination pairs communicate through their dedicated wireless-powered relays
Performance Analysis of Cooperative V2V and V2I Communications under Correlated Fading
Cooperative vehicular networks will play a vital role in the coming years to
implement various intelligent transportation-related applications. Both
vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications
will be needed to reliably disseminate information in a vehicular network. In
this regard, a roadside unit (RSU) equipped with multiple antennas can improve
the network capacity. While the traditional approaches assume antennas to
experience independent fading, we consider a more practical uplink scenario
where antennas at the RSU experience correlated fading. In particular, we
evaluate the packet error probability for two renowned antenna correlation
models, i.e., constant correlation (CC) and exponential correlation (EC). We
also consider intermediate cooperative vehicles for reliable communication
between the source vehicle and the RSU. Here, we derive closed-form expressions
for packet error probability which help quantify the performance variations due
to fading parameter, correlation coefficients and the number of intermediate
helper vehicles. To evaluate the optimal transmit power in this network
scenario, we formulate a Stackelberg game, wherein, the source vehicle is
treated as a buyer and the helper vehicles are the sellers. The optimal
solutions for the asking price and the transmit power are devised which
maximize the utility functions of helper vehicles and the source vehicle,
respectively. We verify our mathematical derivations by extensive simulations
in MATLAB.Comment: Internet of Vehicles (IoV), Vehicular communication, Antenna
correlation, Stackelberg game, Vehicle-to-infrastructure (V2I),
Vehicle-to-vehicle (V2V), Game theory, Cooperative vehicular network
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Device-to-device (D2D) communication underlaying cellular networks allows
mobile devices such as smartphones and tablets to use the licensed spectrum
allocated to cellular services for direct peer-to-peer transmission. D2D
communication can use either one-hop transmission (i.e., in D2D direct
communication) or multi-hop cluster-based transmission (i.e., in D2D local area
networks). The D2D devices can compete or cooperate with each other to reuse
the radio resources in D2D networks. Therefore, resource allocation and access
for D2D communication can be treated as games. The theories behind these games
provide a variety of mathematical tools to effectively model and analyze the
individual or group behaviors of D2D users. In addition, game models can
provide distributed solutions to the resource allocation problems for D2D
communication. The aim of this article is to demonstrate the applications of
game-theoretic models to study the radio resource allocation issues in D2D
communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 201
MIMO-OFDM Based Energy Harvesting Cooperative Communications Using Coalitional Game Algorithm
This document is the Accepted Manuscript version. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we consider the problem of cooperative communication between relays and base station in an advanced MIMO-OFDM framework, under the assumption that the relays are supplied by electric power drawn from energy harvesting (EH) sources. In particular, we focus on the relay selection, with the goal to guarantee the required performance in terms of capacity. In order to maximize the data throughput under the EH constraint, we model the transmission scheme as a non-transferable coalition formation game, with characteristic function based on an approximated capacity expression. Then, we introduce a powerful mathematical tool inherent to coalitional game theory, namely: the Shapley value (Sv) to provide a reliable solution concept to the game. The selected relays will form a virtual dynamically-configuredMIMO network that is able to transmit data to destination using efficient space-time coding techniques. Numerical results, obtained by simulating the EH-powered cooperativeMIMO-OFDMtransmission with Algebraic Space-Time Coding (ASTC), prove that the proposed coalitional game-based relay selection allows to achieve performance very close to that obtained by the same system operated by guaranteed power supply. The proposed methodology is finally compared with some recent related state-of-the-art techniques showing clear advantages in terms of link performance and goodput.Peer reviewe
Incentivizing Signal and Energy Cooperation in Wireless Networks
Abstract-We consider a two-hop wireless network where the source(s) in the network have the ability to wirelessly power the relay(s) who also have their own data to send to the destination. Considering the fact that each node in the network aims to maximize its own metric, we adopt a game theoretic approach that foresees offering relaying of the sources' data in exchange for energy provided to the relays, and simultaneously offering energy to the relays in exchange for their relaying services. We first study a Stackelberg competition with the single relay node as the leader, and investigate the impact of having multiple source nodes in the system. We next study the reciprocal Stackelberg game with the single source as the leader, and investigate the inter-relay competition with multiple relays. We find that in the Stackelberg games, the leader can improve its individual utility by influencing the follower's decision accordingly, even more so when there are multiple followers. We next formulate a noncooperative game between the source and the relay and show the existence of a unique Nash equilibrium by an appropriate pricing mechanism. The equilibrium maximizes the total utility of the network and allows the destination to choose how much data to receive from each node
Learning for Cross-layer Resource Allocation in the Framework of Cognitive Wireless Networks
The framework of cognitive wireless networks is expected to endow wireless devices with a cognition-intelligence ability with which they can efficiently learn and respond to the dynamic wireless environment. In this dissertation, we focus on the problem of developing cognitive network control mechanisms without knowing in advance an accurate network model. We study a series of cross-layer resource allocation problems in cognitive wireless networks. Based on model-free learning, optimization and game theory, we propose a framework of self-organized, adaptive strategy learning for wireless devices to (implicitly) build the understanding of the network dynamics through trial-and-error.
The work of this dissertation is divided into three parts. In the first part, we investigate a distributed, single-agent decision-making problem for real-time video streaming over a time-varying wireless channel between a single pair of transmitter and receiver. By modeling the joint source-channel resource allocation process for video streaming as a constrained Markov decision process, we propose a reinforcement learning scheme to search for the optimal transmission policy without the need to know in advance the details of network dynamics.
In the second part of this work, we extend our study from the single-agent to a multi-agent decision-making scenario, and study the energy-efficient power allocation problems in a two-tier, underlay heterogeneous network and in a self-sustainable green network. For the heterogeneous network, we propose a stochastic learning algorithm based on repeated games to allow individual macro- or femto-users to find a Stackelberg equilibrium without flooding the network with local action information. For the self-sustainable green network, we propose a combinatorial auction mechanism that allows mobile stations to adaptively choose the optimal base station and sub-carrier group for transmission only from local payoff and transmission strategy information.
In the third part of this work, we study a cross-layer routing problem in an interweaved Cognitive Radio Network (CRN), where an accurate network model is not available and the secondary users that are distributed within the CRN only have access to local action/utility information. In order to develop a spectrum-aware routing mechanism that is robust against potential insider attackers, we model the uncoordinated interaction between CRN nodes in the dynamic wireless environment as a stochastic game. Through decomposition of the stochastic routing game, we propose two stochastic learning algorithm based on a group of repeated stage games for the secondary users to learn the best-response strategies without the need of information flooding
Protecting Secret Key Generation Systems Against Jamming: Energy Harvesting and Channel Hopping Approaches
Jamming attacks represent a critical vulnerability for wireless secret key generation (SKG) systems. In this paper, two counter-jamming approaches are investigated for SKG systems: first, the employment of energy harvesting (EH) at the legitimate nodes to turn part of the jamming power into useful communication power, and, second, the use of channel hopping or power spreading in block fading channels to reduce the impact of jamming. In both cases, the adversarial interaction between the pair of legitimate nodes and the jammer is formulated as a two-player zero-sum game and the Nash and Stackelberg equilibria are characterized analytically and in closed form. In particular, in the case of EH receivers, the existence of a critical transmission power for the legitimate nodes allows the full characterization of the game's equilibria and also enables the complete neutralization of the jammer. In the case of channel hopping versus power spreading techniques, it is shown that the jammer's optimal strategy is always power spreading while the legitimate nodes should only use power spreading in the high signal-to-interference ratio (SIR) regime. In the low SIR regime, when avoiding the jammer's interference becomes critical, channel hopping is optimal for the legitimate nodes. Numerical results demonstrate the efficiency of both counter-jamming measures
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