Predicting the Probability of Spectrum Sensing with LMS Process in Heterogeneous LTE Networks

Abstract

Mobile communication systems present an actuality subject in academic and industrial research activities due to several phenomena such as interferences, multipath, fading, and shadowing. All this lead to a severe perturbation on handover mechanism which depends on specific reports, essentially, reference signal received power (RSRP) and signal-to-interference and noise ratio(SINR). In this paper, we design a new technique in handover domain; it consists of combining energy detection method used in cognitive radio with least mean square (LMS) process in order to prognosticate the handover impact in a realistic scenario of heterogeneous LTE network. More exactly, technique sense of the word "triggering" will be changed to a probability of detection Pd. The proposed algorithm cycle follows two main steps; Firstly, predict at what time the absence of spectrum (primary user) will occur, using a predicted sensing probability Pˆd (t+p) . Secondly, search others spectrums in this time by calculating Pd(t) for each sensed signal and hand-off secondary user in the best spectrum. The results achieved of the simulation are evaluating, it shows that the proposed method predict the original Pd correctly with minimal errors and select the best spectrum successfully.