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IJSTR >> Volume 9 - Issue 9, September 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Channel And Power Allocation For Mm-Wave Device-To-Device-Enabled Vehicular Networks

[Full Text]

 

AUTHOR(S)

Filbert Onkundi Ombongi, Heywood Ouma Absaloms, Philip Langat Kibet

 

KEYWORDS

mm-wave, D2D, vehicle-to-everything, 5G, Vehicle-to-Vehicle

 

ABSTRACT

The demand for higher data rate services has led to the emergence of 5G wireless networks to offer the limitations of the current cellular communication technologies. The millimeter-wave (mm-wave) communication technologies have evolved into direct Device-to-Device (D2D) single-hop or multi-hop communications. Direct D2D communication can easily be integrated into vehicular communication networks such as vehicle-to-everything (V2X) to offer high-speed data connectivity, very low latency, and reliable services. However, the implementation of D2D enabled vehicular communication networks are characterized by an architecture that causes misalignment of the mm-wave beams from the vehicles thereby causing mutual interference. The mm-wave communication is also having a challenge of high propagation losses, sensitivity to blockage, and directivity. In this regard, the coexistence of cellular users, D2D users together with the vehicular users’ calls for strict QoS requirements since there is the high mobility of the vehicles and the presence of mutual interference. This paper formulates a matching theory-based Hungarian algorithm to perform channel and power allocation that takes into consideration the high rate of channel fluctuations, interference, and latency constraints in the high mobility environment. The proposed Hungarian algorithm was simulated in MATLAB by applying 3GPP TR 37.885 and 38.901 specifications. The Hungarian algorithm is compared with the max-min algorithm. The Hungarian algorithm was found to have a 10.8% better performance than the max-min algorithm when the maximum spectrum efficiency was considered. When the minimum spectrum efficiency was considered the Hungarian algorithm was 17.35% better than the max-min algorithm.

 

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