PERFORMANCE EVALUATION OF FILTER BANK MULTI-CARRIER MODULATION IN MULTIPATH FADING CHANNELS

Filter Bank Multi-Carrier (FBMC) modulation is one of the most significant enablers for future 5G technologies. It is a modulation technique for resolving inter-carrier and inter-symbol interference using two possible methods: Frequency Spreading (FS) and Poly Phase (PP) implementation. Cyclic prefixes are used in OFDM for signal robustness, but they have some disadvantages in orthogonal frequency division multiplexing. FBMC is used to solve the disadvantages of OFDM and save a bandwidth. In this paper, performance comparisons in terms of symbol error rate between OFDM and FBMC systems in AWGN and multipath fading channels are presented. The obtained results show that FBMC over performs OFDM in multipath fading channels and the improvement margin is increased as the number of subcarriers decreased.

Future OFDM-based Communication Systems Towards 6G and Beyond: Machine Learning Approaches

The vision towards 6G and beyond communication systems demands higher rate transmission, massive amount of data processing, and low latency communication. Orthogonal Frequency Division Modulation (OFDM) has been adopted in the current 5G networks and has become one of the potential candidates for the future communication systems. Although OFDM offers many benefits including high spectrum efficiency and high robustness against the multipath fading channels, it has major challenges such as frequency offset and high Peak to Power Ratio (PAPR). In 5G communication network, there is a significant increase in the number of sensors and other low-power devices where users or devices may create large amount of connection and dynamic data processing. In order to deal with the increasingly complex communication network, Machine Learning (ML) has been increasingly utilised to create intelligent and more efficient communication network. This paper discusses challenges and the impacts of embedding ML in OFDM-based communication systems.

Study of Modulation Schemes over a Multipath Fading Channels

Communications systems concerted over wireless channels depend on the environment. Communications system can be more reliable and efficient by properly analyzing wireless channels. Today's most important features are a high data rate and reliable performance to exploiting viable networks during this new information age. The channel is not time-invariant in wireless communication, so the received signal exhibits amplitude, phase, and angle variations due to multipath fading. Increasing data rates and reducing bandwidth make Orthogonal Frequency Division Multiplexing (OFDM) an important component of wireless communication systems. The OFDM technique uses many carriers very efficiently. With this scheme, interference is robustly reduced, and fading scenarios are easily accommodated. Analyzing digital modulation schemes requires evaluating link performance with fading channels. The paper compares channel performance over varying fading environments using a variety of modulation schemes. We study the BER and SNR properties of the AWGN, Rician fading and Rayleigh fading channels modulated with BPSK, QPSK, and M-ary QAM.

Cognitive Spectrum Sensing with Multiple Primary Users in Rayleigh Fading Channels

Accurate detection of white spaces is crucial in cognitive radio networks. Initial investigations show that the accurate detection in a multiple primary users environment is challenging, especially under severe multipath conditions. Among many techniques, recently proposed eigenvalue-based detectors that use random matrix theories to eliminate the need of prior knowledge of the signals proved to be a solid approach. In this work, we study the effect of Rayleigh multipath fading channels on spectrum sensing in a multiple primary user environment for a pre-proposed detector called the spherical detector using the eigenvalue approach. Simulation results show interesting outcomes.

Cognitive Spectrum Sensing with Multiple Primary Users in Rayleigh Fading Channels

Accurate detection of white spaces is crucial in cognitive radio networks. Initial investigations show that the accurate detection in a multiple primary users environment is challenging, especially under severe multipath conditions. Among many techniques, recently proposed eigenvalue-based detectors that use random matrix theories to eliminate the need of prior knowledge of the signals proved to be a solid approach. In this work, we study the effect of Rayleigh multipath fading channels on spectrum sensing in a multiple primary user environment for a pre-proposed detector called the spherical detector using the eigenvalue approach. Simulation results show interesting outcomes.