Title :
Second-order statistic-based detection of Alamouti-coded OFDM signals for cognitive radio
Author :
Eldemerdash, Yahia A. ; Dobre, Octavia A.
Author_Institution :
Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´s, NL, Canada
Abstract :
In this paper, an algorithm for the detection of the Alamouti-coded orthogonal frequency division multiplexing (AL-OFDM) signals is proposed. To the best of our knowledge, this is the first time in the literature when the detection of AL-OFDM signals used in recent WiMAX and LTE standards is investigated. The cross-correlation between the signals received with two antennas is studied as a detection feature, and its analytical closed-form expression obtained. These findings are further employed to develop the signal detection algorithm. The algorithm performance is investigated based on simulated standard signals. A good performance is achieved with a short sensing time and at low signal-to-noise ratios (SNRs). Additionally, the proposed algorithm requires neither information about the channel, modulation type, and noise power, nor timing synchronization.
Keywords :
Long Term Evolution; OFDM modulation; WiMax; antenna arrays; cognitive radio; higher order statistics; signal detection; space-time block codes; Alamouti-coded OFDM signal second-order statistic-based detection; Alamouti-coded orthogonal frequency division multiplexing signal detection; LTE standard; SNR; WiMAX standard; analytical closed-form expression; antenna; cognitive radio; signal-to-noise ratio; space-time block code; Feature extraction; Niobium; OFDM; Receiving antennas; Signal processing algorithms; Signal to noise ratio; Timing; Alamouti space-time block code; Cognitive radio; MIMO; OFDM;
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
DOI :
10.1109/GLOCOM.2014.7037271