Low Complexity Cell Search Algorithm for Mobile OFDMA Systems

In this paper, a low complexity cell search algorithm (ML-ACL algorithm) for mobile OFDMA systems is proposed, with IEEE 802.16e as the example. The main problem on cell search is the huge computational complexity due to the long pseudo-noise (PN) series. Based on the maximum-likelihood (ML) detection theory, the ML-ACL algorithm uses an adaptive correlation length (ACL) to greatly reduce computational complexity with nearly no degradation of detection performance. Furthermore, to compensate the channel impairments, a cell search structure based on the differential demodulation in frequency domain is proposed to accomplish cell search and the integer frequency offset estimation jointly. The system simulation results show that the ML-ACL algorithm is efficient and of low complexity for OFDMA cellular systems, especially for IEEE 802.16e OFDMA systems.