Back to Search
Start Over
Improving Performance of the Typical User in the Indoor Cooperative NOMA Millimeter Wave Networks with Presence of Walls.
- Source :
- EAI Endorsed Transactions on Industrial Networks & Intelligent Systems; 2024, Vol. 11 Issue 2, p1-15, 15p
- Publication Year :
- 2024
-
Abstract
- The beyond 5G millimeter-wave cellular network system is expected to provide high-quality service in indoor areas. Due to the high density of obstacles, cooperative communication techniques are employed to improve the user's desired signal power by finding more than one appropriate station to serve that user. While the conventional system utilizes additional equipment such as Reconfigurable Intelligent Surfaces (RIS) and relays to enable cooperative features, the paper introduces a new network paradigm that utilizes the second nearest Base Station (BS) of the typical user as the Decode and Forward (DF) relay. Thus, depending on the success of decoding the message from the user's serving BS or the second nearest BS, the typical user can work with or without assistance from the relay, whose operation follows the discipline of the power-domain NOMA technique. In the case of relay assistance, the Maximum Ratio Combining technique is utilized by the typical user to combine the desired signals. To examine the performance of the proposed system, the Nakagamim and the newly developed path loss model, which considers the density of walls and their properties, are adopted to derive the coverage probability of the user with and without relay assistance. The closedform expressions of this performance metric are derived using Gauss quadrature and Welch-Satterthwaite approximation. Through analytical and simulation results, it is seen that the proposed system can improve the user coverage probability by up to 10%. [ABSTRACT FROM AUTHOR]
- Subjects :
- MILLIMETER waves
POISSON processes
POINT processes
5G networks
Subjects
Details
- Language :
- English
- ISSN :
- 24100218
- Volume :
- 11
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- EAI Endorsed Transactions on Industrial Networks & Intelligent Systems
- Publication Type :
- Academic Journal
- Accession number :
- 176826036
- Full Text :
- https://doi.org/10.4108/eetinis.v11i2.5156