Open AccessApplication of ANFIS Power Control for Downlink CDMA‐Based LMDS Systems
Author(s) -
Lee ZeShin,
Tsay MuKing,
Liao ChienHsing
Publication year - 2009
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.09.0108.0296
Subject(s) - telecommunications link , local multipoint distribution service , power control , computer science , code division multiple access , interference (communication) , electronic engineering , wireless , adaptive neuro fuzzy inference system , power (physics) , real time computing , fuzzy control system , fuzzy logic , engineering , computer network , channel (broadcasting) , telecommunications , artificial intelligence , physics , quantum mechanics
Rain attenuation and intercell interference are two crucial factors in the performance of broadband wireless access networks such as local multipoint distribution systems (LMDS) operating at frequencies above 20 GHz. Power control can enhance the performance of downlink CDMA‐based LMDS systems by reducing intercell interference under clear sky conditions; however, it may damage system performance under rainy conditions. To ensure robust operation under both clear sky and rainy conditions, we propose a novel power‐control scheme which applies an adaptive neuro‐fuzzy inference system (ANFIS) for downlink CDMA‐based LMDS systems. In the proposed system, the rain rate and the number of users are two inputs of the fuzzy inference system, and output is defined as channel quality, which is applied in the power control scheme to adjust the power control region. Moreover, ITU‐R P.530 is employed to estimate the rain attenuation. The influence of the rain rate and the number of users on the distance‐based power control (DBPC) scheme is included in the simulation model as the training database. Simulation results indicate that the proposed scheme improves the throughput of the DBPC scheme.