Compressed Sensing Algorithms for SISO-OFDM Channel Estimation

Autor: G. Ramachandra Reddy, Khan Nabeela Khanum
Rok vydání: 2020
Předmět:
Zdroj: 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE).
DOI: 10.1109/ic-etite47903.2020.184
Popis: In this paper, the BER performance of the SISOOFDM system channel estimation is analyzed. OFDM is a multicarrier technology with high data rate and low interference, used in many 4th generations (4G) and 5th generation (5G) wireless systems like LTE, LTE-A, WiMAX and several Wi-Fi and WLAN standards. OFDM is mainly used for reducing the inter symbol interference (ISI) effect in a wideband channel. By increasing the symbol time, the effect of the delay spread reduces which helps in reducing the ISI. To exploit a MIMO-OFDM system accurate channel estimates are needed. Preeminent results can be found when a channel is considered to be sparse. A series of pilot signals are transmitted through this channel and sensed at the receiver to estimate channel parameters. Compressive sensing techniques are used to retrieve the transmitted information bits using the optimization technique of Orthogonal Matching Pursuit (OMP) and norm minimization. These techniques are compared in terms of Bit Error Rate (BER) for the SISO-OFDM System.
Databáze: OpenAIRE