An analysis of 5G-MIMO communication system based SS for centralized cooperative and non-cooperative users

The purpose of 5G-MIMO communication systems is to boost the intensity of the received signal, and facilitate the application of the users’ apparatus. However, in band-grabbing systems such as these, the accessibility of a spectrum is hindered by gridlocks. Also, to be considered is the spectrum’s waveform, which is the type that contends with 5G networks specifically. This undertaking involves the development of a 5G-MIMO communication system based SS, in which the spectrum is enhanced, by way of a spectrum sensing (SS) algorithm. By replicating the energy detection procedure, this recommended SS algorithm engages the cosine law to filter the traffic signal, and subsequently portions it using the Welch algorithm. The Hann algorithm is then utilized, to window the traffic signal, to damp the high power delivered to the MIMO. The key role, of the SS algorithm, is to sense a spectrum for 5G-MIMO communication system, with the capacity to damp the MIMO effect for a variety of waveforms. The SS algorithm expressions are applicable for both non-cooperative and centralized cooperative users. For each expression, an examination was performed for waveforms used by 5G-MIMO communication systems. This included filtered-orthogonal frequency division multiplexing (F-OFDM), universal filtered multi-carrier (UFMC), and filter bank multi-carrier (FBMC) waveforms. The operating parameters, including SNR, the signal span and power, the antenna count, as well as the types of modulation for both non-cooperative and centralized cooperative users, were scrutinized. The simulation results revealed a notable achievement for the parameters lower than zero dB of SNR, greater than 95% global detection probability, less than 1% global system error probability, and less than 1% global false alarm probability. An evaluation of the recommended system’s parameters discloses its superiority, in comparison to other previously developed systems.