Wireless communication encountered lots of issues in the channel as the signal is being propagated from transmitter to the receiver. The mobile users continue increasing and the quality of service is very poor due to unreliable nature of the channel. There has been signaling fading, attenuation, calls drop, interference, network capacity and signal loss which may be traced to path propagation problems. The data was collected from MTN base station at four different locations in and . The optimized model is recommended for better deployment and would be more accurate to be applied for path loss prediction in the suburban area.

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This paper presents an improved hybrid Equal Gain Combiner-Maximal Ratio Combiner (EGC-MRC) diversity scheme in 5G millimeter wave (mm-wave) frequency. The term 5G mm-wave refers to the radio frequency spectrum between 24 and 100. The signal interference is a challenging task in 5G mm-wave frequency, and radio network suffer from co-channel and adjacent channel interference. 5G network deployment depends on large number of antennas, which resulted in signal interference. The conventional receiver's diversity techniques have high hardware complexity and are characterized by low performance. A new hybrid EGC-MRC diversity scheme was proposed as an improvement on the performance of existing MRC scheme. In achieving this, Probability Density Function (PDF) of the hybrid model was derived using the instantaneous Signal-to-Noise Ratio (SNR) obtained from the output of MRC and EGC diversity schemes. The performance of the developed model was evaluated using Outage Probability () and Processing time () at different SNR with number of paths. Simulation of the MRC, EGC and hybrid EGC-MRC models were carried out using MATLAB 2018a and the results compared. The output results showed that hybrid EGC-MRC performed better than EGC and MRC by having a lower and. This new model has the potential to mitigate network interference, multipath propagation, and hardware complexity in 5G mm-wave frequency. Therefore, the developed model can be deployed by network operators to solve signal interference in 5G network.

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