Stochastic geometry modelling and analysis for cooperative NOMA with large transmit antennas for 5G applications and beyond

• Published in: IET Communications
• Main Authors: Samuel Tweneboah‐Koduah, Emmanuel Ampoma Affum, James Adu Ansere, Eric Gyamfi, Kwasi Adu‐Boahen Opare, Sunday Adeola Ajagbe, Matthew O. Adigun
• Format: Article
• Language: English
• Published: Wiley 2023-08-01
• Subjects: 5G mobile communication; amplify and forward communication; channel estimation; cooperative communication; decode and forward communication; MIMO communication
• Online Access: https://doi.org/10.1049/cmu2.12648
• ISSN: 1751-8628; 1751-8636

Abstract Among the technologies that have made 5G wireless communication successful are non‐orthogonal multiple access (NOMA) and cooperative NOMA. The distinction is that cooperative NOMA adds coding schemes to improve performance. Nevertheless, research on cooperative NOMA has primarily used theoretical correlation‐based stochastic models (CBSM) instead of geometric‐based stochastic models (GBSM) that represent suitable channel conditions by including characteristics like path loss, delay profile, and angle of arrival in the model. This paper connects the low adoption of GBSM is due to computational challenges. Given this, it is essential to assess cooperative NOMA that employs GBSM with large antenna transmitters to meet future 5G expectations. The cooperative NOMA system's transmitter is modelled as a uniform rectangular array and a novel channel realisation is proposed for analysis. The location vector of the antenna using the physical dimension of the array is defined to reduce computational problems. Results shows that the average bit‐error performance of GBSM matches that of CBSM at the same antenna element separation, but the spatial correlation between antenna elements significantly impacts the outage probability and average achievable rates of GBSM performance. Enhanced GBSM performance by increasing antenna separation at the transmitter above one‐eighth wavelength.