TY - GEN
T1 - Energy-aware enterprise femtocell deployment
AU - Lin, Michael
AU - La Porta, Thomas
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2016/4/3
Y1 - 2016/4/3
N2 - 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%.
AB - 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%.
UR - http://www.scopus.com/inward/record.url?scp=84912121289&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84912121289&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2014.6952690
DO - 10.1109/WCNC.2014.6952690
M3 - Conference contribution
AN - SCOPUS:84912121289
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 2312
EP - 2317
BT - IEEE Wireless Communications and Networking Conference, WCNC
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE Wireless Communications and Networking Conference, WCNC 2014
Y2 - 6 April 2014 through 9 April 2014
ER -