TY - GEN
T1 - Outage Probability of Opportunistic Self-Backhauled Millimeter Wave Mobile Networks
AU - Maham, Behrouz
N1 - Funding Information:
This research was supported by the Faculty Development Competitive Research Grant (No. 240919FD3918), Nazarbayev University.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we consider a downlink self-backhauled mmWave cellular system with opportunistic selection of associated small cells, controlled by a centralized anchor base station (A-BS). We assume both backhaul and access links are modeled as Nakagami-m channels concatenate with random binary blockages. We analyze the system performance by deriving the equivalent end-to-end channel distributions. Then, the derived cumulative distribution function is used to calculate the outage probability. Finally, the simulation results show the impact of different parameters and correctness of our analytical results. It is also shown that our proposed scheme outperforms maximum ratio combining detection, in which all associated self-backhaled BSs are retransmitting the decoded user message toward the typical user equipment.
AB - In this paper, we consider a downlink self-backhauled mmWave cellular system with opportunistic selection of associated small cells, controlled by a centralized anchor base station (A-BS). We assume both backhaul and access links are modeled as Nakagami-m channels concatenate with random binary blockages. We analyze the system performance by deriving the equivalent end-to-end channel distributions. Then, the derived cumulative distribution function is used to calculate the outage probability. Finally, the simulation results show the impact of different parameters and correctness of our analytical results. It is also shown that our proposed scheme outperforms maximum ratio combining detection, in which all associated self-backhaled BSs are retransmitting the decoded user message toward the typical user equipment.
UR - https://www.scopus.com/pages/publications/85137747392
UR - https://www.scopus.com/pages/publications/85137747392#tab=citedBy
U2 - 10.1109/VTC2022-Spring54318.2022.9860393
DO - 10.1109/VTC2022-Spring54318.2022.9860393
M3 - Conference contribution
AN - SCOPUS:85137747392
T3 - IEEE Vehicular Technology Conference
BT - 2022 IEEE 95th Vehicular Technology Conference - Spring, VTC 2022-Spring - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 95th IEEE Vehicular Technology Conference - Spring, VTC 2022-Spring
Y2 - 19 June 2022 through 22 June 2022
ER -