TY - CHAP
T1 - Spectrum Slicing in MEC-Assisted ADVNETs
AU - Peng, Haixia
AU - Ye, Qiang
AU - Shen, Xuemin Sherman
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - In this chapter, the spectrum resource management issue is investigated under the MEC-assisted ADVNET architecture proposed in Chap. 2. Specifically, we first propose a dynamic spectrum management framework to improve spectrum resource utilization. Based on this framework, spectrum slicing, spectrum allocating, and transmit power control are then jointly considered, which can help support the increased communication data traffic and guarantee applications’ QoS requirements. Accordingly, we formulate three maximization problems to slice spectrum among BSs, allocate spectrum among AVs associated with a BS, and control transmit powers of BSs, respectively. Via linear programming relaxation and first-order Taylor series approximation, the three problems are transformed into tractable forms and then are jointly solved through an alternate concave search (ACS) algorithm. As a result, optimal results, including spectrum slicing ratios among BSs, BS-vehicle association patterns, fractions of spectrum resources allocated to AVs, and transmit powers of BSs, are obtained. The simulation results demonstrate that a high aggregate network utility can be achieved by the proposed spectrum management scheme compared with existing schemes.
AB - In this chapter, the spectrum resource management issue is investigated under the MEC-assisted ADVNET architecture proposed in Chap. 2. Specifically, we first propose a dynamic spectrum management framework to improve spectrum resource utilization. Based on this framework, spectrum slicing, spectrum allocating, and transmit power control are then jointly considered, which can help support the increased communication data traffic and guarantee applications’ QoS requirements. Accordingly, we formulate three maximization problems to slice spectrum among BSs, allocate spectrum among AVs associated with a BS, and control transmit powers of BSs, respectively. Via linear programming relaxation and first-order Taylor series approximation, the three problems are transformed into tractable forms and then are jointly solved through an alternate concave search (ACS) algorithm. As a result, optimal results, including spectrum slicing ratios among BSs, BS-vehicle association patterns, fractions of spectrum resources allocated to AVs, and transmit powers of BSs, are obtained. The simulation results demonstrate that a high aggregate network utility can be achieved by the proposed spectrum management scheme compared with existing schemes.
KW - Autonomous vehicles
KW - Multi-access edge computing
KW - NFV
KW - QoS-guaranteed service
KW - Spectrum resource allocation
UR - https://www.scopus.com/pages/publications/85127909559
U2 - 10.1007/978-3-030-96507-5_3
DO - 10.1007/978-3-030-96507-5_3
M3 - 章节
AN - SCOPUS:85127909559
T3 - Wireless Networks (United Kingdom)
SP - 53
EP - 80
BT - Wireless Networks (United Kingdom)
PB - Springer Nature
ER -