Energy-Efficient Spectrum Selection and Resource Allocation in Downlink Cognitive Femtocell Networks

Chen, Jun-Quan; Chu, Jui-Hung; Feng, Kai-Ten

doi:10.1109/vtcspring.2015.7145820

Cited by 2 publications

(3 citation statements)

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“…The optimization problem associated with the spectrum selection with limited number of antennas for downlink cognitive femtocell networks was formulated by Chen et al [77]. The optimization problem formulated aims to maximize the system's energy efficiency while being constrained by hardware limitations and user equipment.…”

Section: B Non-linear Objective Functionmentioning

confidence: 99%

“…The authors considered open access OFDMA femtocell networks for the scenario where a macrocell user performs handover from its serving macrocell base station to a nearby femtocell access point. As was performed by Chen et al [77], a joint subchannel and power optimization problem is formulated and an efficient algorithm using dual decomposition methods is proposed.…”

Section: B Non-linear Objective Functionmentioning

confidence: 99%

“…Several papers actually applied this technique, among them is [5], even though their problem is a non-convex one and they claim that they were able to obtain an optimal solution. Other papers include: [28], [40], [41], [43], [44], [49], [58], [68], [45], [59], [75], [76], [77], [79], and [80]. El-Sherif and Mohamed [71] used this technique to obtain sub-optimal solution to their problem.…”

Section: Lagrangian Dualitymentioning

confidence: 99%

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Mixed-integer programming based techniques for resource allocation in underlay cognitive radio networks: A survey

et al. 2016

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For about the past decade and a half research efforts into cognitive radio networks (CRNs) have increased dramatically. This is because CRN is recognized as a technology that has the potential to squeeze the most out of the existing spectrum and hence virtually increase the effective capacity of a wireless communication system. The resulting increased capacity is still a limited resource and its optimal allocation is a critical requirement in order to realize its full benefits. Allocating these additional resources to the secondary users (SUs) in a CRN is an extremely challenging task and integer programming based optimization tools have to be employed to achieve the goals which include, among several aspects, increasing SUs throughput without interfering with the activities of primary users (PUs). The theory of the optimization tools that can be used for resource allocations (RA) in CRN have been well established in the literature; convex programming is one of them, in fact the major one. However when it comes to application and implementation, it is noticed that the practical problems do not fit exactly into the format of well established tools and researchers have to apply approximations of different forms to assist in the process. In this survey paper, the optimization tools that have been applied to RA in CRNs are reviewed. In some instances the limitations of techniques used are pointed out and creative tools developed by researchers to solve the problems are identified. Some ideas of tools to be considered by researchers are suggested, and direction for future research in this area in order to improve on the existing tools are presented.

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Section: B Non-linear Objective Functionmentioning

confidence: 99%

Section: B Non-linear Objective Functionmentioning

confidence: 99%