Name
Abstract | ||
|---|---|---|
A novel intelligent reconfigurable surface (IRS) assisted coordinated multi-point (CoMP) system is proposed. Our objective is to maximize the energy efficiency (EE) of this system by jointly optimizing base station (BS) clustering, user association, sub-carrier assignment, power allocation, and optimal design of the IRS, while satisfying the users’ quality of service requirements. Considering the amplitude and phase shift characteristics, both ideal and non-ideal IRS are investigated. The formulated problem is proved to be NP-hard. By analyzing its structure, we decouple it into the power allocation sub-problem, the BS clustering, UE association, and sub-carrier assignment sub-problem, and the reflection coefficients design sub-problem. For the power allocation sub-problem, we invoke the fractional programming to find the optimal solution. For the reflection coefficients design sub-problem of ideal IRS, the optimal solution is derived with the Lagrangian dual method. Whereas quantization-based method is employed to find the discrete phase shifts for non-ideal IRS. We finally propose a genetic algorithm (GA) to represent the potential solutions of sub-carrier assignment, and combine the other two optimization algorithms as fitness estimator in GA. Numerical results validate the feasibility, fast convergence, and the flexibility of the proposed algorithm. It shows that the proposed scheme outperform the system without IRS and that with a random initialized IRS. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TWC.2022.3142784 | IEEE Transactions on Wireless Communications |
Keywords | DocType | Volume |
CoMP,energy efficiency,fractional programming,GA,IRS | Journal | 21 |
Issue | ISSN | Citations |
7 | 1536-1276 | 0 |
PageRank | References | Authors |
0.34 | 29 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kevin J. Chen | 1 | 11 | 7.09 |
| y xie | 2 | 0 | 0.34 |
| x mu | 3 | 0 | 0.34 |
| j jia | 4 | 0 | 0.34 |
| Yuanwei Liu | 5 | 2162 | 131.65 |