Performance Evaluation of OFDM and Modulation Techniques in Mobile WiMAX (IEEE 802.16e)

• Main Author: Ganan, Imad Alhadi Omar
• Format: Thesis
• Language: English; English
• Published: 2010
• Subjects: TK5101-6720 Telecommunication
• Online Access: http://etd.uum.edu.my/2336/1/Imad_Alhadi_Omar_Ganan.pdf; http://etd.uum.edu.my/2336/2/1.Imad_Alhadi_Omar_Ganan.pdf; http://etd.uum.edu.my/2336/; http://lintas.uum.edu.my:8080/elmu/index.jsp?module=webopac-l&action=fullDisplayRetriever.jsp&szMaterialNo=0000764995

Mobile communication has developed very during the last few years. Due to this fast development in this field, subscribers of today are enjoying the use of many applications ranging from data, voice, audio to video irrespective of the place where they are stationed or moving about. WiMAX technology is fast capturing the market in the field of mobile broadband access. WiMAX uses Orthogonal Frequency Division Multiple Access (OFDMA) at the physical layer. WiMAX uses an adaptive modulation technique to modulate the signal prior to transmitting it. Under adaptive modulation, BPSK, QPSK, 16-QAM and 64 QAM are used for modulating the data depending on the channel conditions. Cyclic Prefix is used to improve the quality of the signal under hostile environments especially Rayleigh fading. Cyclic prefix adds bits to the start and end of data stream to spread the signal. The receiver removes the bits added prior to further processing of the signal. Cyclic prefixing improves the error performance of signals by minimizing Inter Symbol Interference (ISI). This study focused on the performance of the WiMAX system in terms of Bit Error Rate (BER), Signal to Noise Ratio (SNR), Power Spectral Density (PSD) and Probability of Error (Pe). Two models namely one without the Cyclic Prefix and the other with the Cyclic prefix were built to study these parameters. On analyzing the results, it was observed that adding cyclic prefix improved the error performance marginally especially when the signal is BPSK modulated. The results of BER vs SNR and Pe vs SNR are different as Pe is the expected value of BER where BER approaches Pe when the simulation is run for a long period of time and the BER is very high. Other situations, Pe and BER show different results under same conditions. Finally based on the evaluation and conclusion, recommendations were made for further work.