Title :
Energy-aware enterprise femtocell deployment
Author :
Lin, Man ; La Porta, Tom
Author_Institution :
Dept. of Comput. Sci. & Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
Large-scale enterprise femtocell deployments can significantly impact the performance and energy consumption of the underlying wireless networks that support them. Naive femtocell deployments can lead to higher overall network energy usage, while optimized femtocell deployments can increase total network connectivity and reduce macrocell energy consumption. This paper approaches femtocell deployment as a combinatorial optimization problem. We first consider accelerated greedy algorithms using one of two metrics: femtocell coverage and area spectral efficiency. Then, motivated by an analysis of the strengths and weaknesses of each metric, we introduce an algorithm that takes the weighted sum of both metrics. We evaluate our algorithms using extensive simulations, and find that our weighted sum algorithm decreases outage probability by up to 30% relative to existing greedy approaches. Furthermore, our algorithm can lead to a reduction in total network energy usage by up to 14%.
Keywords :
combinatorial mathematics; femtocellular radio; greedy algorithms; optimisation; probability; radio networks; spectral analysis; telecommunication network reliability; telecommunication power management; area spectral efficiency; combinatorial optimization problem; energy-aware enterprise Naive femtocell deployment; extensive simulation; femtocell coverage; greedy algorithm; macrocell energy consumption. reduce; network connectivity; network energy usage reduction; outage probability decrement; weighted sum algorithm; wireless network energy consumption; Acceleration; Base stations; Greedy algorithms; Interference; Macrocell networks; Power demand; Signal to noise ratio;
Conference_Titel :
Wireless Communications and Networking Conference (WCNC), 2014 IEEE
Conference_Location :
Istanbul
DOI :
10.1109/WCNC.2014.6952690