TY - GEN
T1 - Resource Allocation for Outdoor Visible Light Communications with Energy Harvesting Capabilities
AU - Abdelhady, Amr Mohamed Abdelaziz
AU - Amin, Osama
AU - Chaaban, Anas
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2018/1/25
Y1 - 2018/1/25
N2 - Visible light communication (VLC) is a promising technology that can support high data rate services for outdoor mass gathering night events while permitting energy harvesting. In this paper, a VLC system is considered where a transmitter sends data to multiple users with energy harvesting capabilities. This multi-user VLC scenario can be supported using time division multiple access (TDMA). The achievable rates using TDMA are expressed in terms of the allocated resources per user, represented by average optical intensity and time slots. This allocation is to be optimized in order to maximize the average spectral efficiency while meeting power and quality-of-service (QoS) constraints. Herein, QoS is defined as a worst-case guaranteed rate and a minimum harvested energy. To solve this optimization, the optimality conditions are first derived. Then, an efficient algorithm is developed based on the derived conditions, and its near-optimality is verified through several numerical evaluations. The obtained performance is also compared to lower-complexity algorithms, thus reflecting the performance-complexity trade-off of these algorithms.
AB - Visible light communication (VLC) is a promising technology that can support high data rate services for outdoor mass gathering night events while permitting energy harvesting. In this paper, a VLC system is considered where a transmitter sends data to multiple users with energy harvesting capabilities. This multi-user VLC scenario can be supported using time division multiple access (TDMA). The achievable rates using TDMA are expressed in terms of the allocated resources per user, represented by average optical intensity and time slots. This allocation is to be optimized in order to maximize the average spectral efficiency while meeting power and quality-of-service (QoS) constraints. Herein, QoS is defined as a worst-case guaranteed rate and a minimum harvested energy. To solve this optimization, the optimality conditions are first derived. Then, an efficient algorithm is developed based on the derived conditions, and its near-optimality is verified through several numerical evaluations. The obtained performance is also compared to lower-complexity algorithms, thus reflecting the performance-complexity trade-off of these algorithms.
UR - http://hdl.handle.net/10754/627312
UR - http://ieeexplore.ieee.org/document/8269148/
UR - http://www.scopus.com/inward/record.url?scp=85050471058&partnerID=8YFLogxK
U2 - 10.1109/glocomw.2017.8269148
DO - 10.1109/glocomw.2017.8269148
M3 - Conference contribution
SN - 9781538639207
SP - 1
EP - 6
BT - 2017 IEEE Globecom Workshops (GC Wkshps)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -