1,022 research outputs found

    Weighted Max-Min Resource Allocation for Frequency Selective Channels

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    In this paper, we discuss the computation of weighted max-min rate allocation using joint TDM/FDM strategies under a PSD mask constraint. We show that the weighted max-min solution allocates the rates according to a predetermined rate ratio defined by the weights, a fact that is very valuable for telecommunication service providers. Furthermore, we show that the problem can be efficiently solved using linear programming. We also discuss the resource allocation problem in the mixed services scenario where certain users have a required rate, while the others have flexible rate requirements. The solution is relevant to many communication systems that are limited by a power spectral density mask constraint such as WiMax, Wi-Fi and UWB

    Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

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    Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

    The Game Theory: Applications in the Wireless Networks

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    Recent years have witnessed a lot of applications in the computer science, especially in the area of the wireless networks. The applications can be divided into the following two main categories: applications in the network performance and those in the energy efficiency. The game theory is widely used to regulate the behavior of the users; therefore, the cooperation among the nodes can be achieved and the network performance can be improved when the game theory is utilized. On the other hand, the game theory is also adopted to control the media access control protocol or routing protocol; therefore, the energy exhaust owing to the data collision and long route can be reduced and the energy efficiency can be improved greatly. In this chapter, the applications in the network performance and the energy efficiency are reviewed. The state of the art in the applications of the game theory in wireless networks is pointed out. Finally, the future research direction of the game theory in the energy harvesting wireless sensor network is presented

    Cooperative power control approaches towards fair radio resource allocation for wireless network

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    Performance optimization in wireless networks is a complex problem due to variability and dynamics in network topology and density, traffic patterns, mutual interference, channel uncertainties, etc. Opportunistic or selfish approaches may result in unbalanced allocation of channel capacity where particular links are overshadowed. This degrades overall network fairness and hinders a multi-hop communication by creating bottlenecks. A desired approach should allocate channel capacity proportionally to traffic priority in a cooperative manner. This work consists of two chapters that address the fairness share problem in wireless ad hoc, peer-to-peer networks and resource allocation within Cognitive Radio network. In the first paper, two fair power control schemes are proposed and mathematically analyzed. The schemes dynamically determine the viable resource allocation for a particular peer-to-peer network. In contrast, the traditional approaches often derive such viable capacity for a class of topologies. Moreover, the previous power control schemes assume that the target capacity allocation, or signal-to-interference ratio (SIR), is known and feasible. This leads to unfairness if the target SIR is not viable. The theoretical and simulation results show that the capacity is equally allocated for each link in the presence of radio channel uncertainties. In the second paper, based on the fair power control schemes, two novel power control schemes and an integrated power control scheme are proposed regarding the resource allocation for Cognitive Radio network to increase the efficiency of the resource while satisfying the Primary Users\u27 Quality of Service. Simulation result and tradeoff discussion are given --Abstract, page iv

    Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

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    Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs
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