Energy Efficient Resource Allocation for MSCA Enabled CoMP in HetNets

Chen, Jian; Ma, Ziye; Liu, Yuanwei; Jia, Jie; Wang, Xingwei

doi:10.1109/tvt.2022.3142075

Cited by 7 publications

(1 citation statement)

References 45 publications

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“…In conjunction with the services in 5G, the subcarrier and the resource block selection were adjusted in [8], while the overhead constraints on subcarrier activation and deactivation were also considered. Considering the energy efficiency optimization of the 5G base station, Chen jointly optimized the selection of sub‐carriers with multiple CA and the power distribution of multi‐point access coordinated by the coordinated multi‐point (CoMP) in [9]. The issue of power allocation and subcarrier selection is decoupled, and the optimal solution is obtained by genetic algorithm (GA).…”

Section: Literal Review and Background Workmentioning

confidence: 99%

On the performance of non‐contiguous carrier aggregation in presence of subspectral errors

et al. 2023

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Carrier aggregation can not only increase communication bandwidth, but also improve spectrum efficiency and communication security. Considering the non‐contiguous multi‐subspectrum aggregation for the spectrum division transmission of arbitrary signal, the paper analyzes the performance impact on the demodulation of aggregated signal in the presence of subspectral amplitude and phase errors in receiver. The theoretical bit‐error rates (BER) of quaternary phase‐shift keying and M‐ary phase‐shift keying are derived to clarify the subspectrum synchronization accuracy requirements in non‐contiguous carrier aggregation. In addition, two adaptive equalizers requiring no pilot overhead are introduced to correct the distortion of aggregated signal caused by the subspectral errors. Both algorithms need no estimation of synchronization error but also have the tracking capability of phase error even with subspectral carrier error. Simulation results show the reliability of the theoretical BER performance and the excellent performance of the equalization algorithms.

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Section: Literal Review and Background Workmentioning

confidence: 99%