Advanced spectrum sharing in 5G cognitive heterogeneous networks

Yang, Chungang; Li, Jiandong; Guizani, Mohsen; Anpalagan, Alagan; Elkashlan, Maged

doi:10.1109/mwc.2016.7462490

Cited by 114 publications

(78 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, the wireless link efficiency is approaching the fundamental limit with the development of the multiple-inputmultiple-output and orthogonal frequency division multiplexing technologies. As such, a heterogeneous network (HetNet) is emerging as a promising network architecture to improve the network capacity [3]- [5] .…”

Section: Introductionmentioning

confidence: 99%

Deep Reinforcement Learning-Based Modulation and Coding Scheme Selection in Cognitive Heterogeneous Networks

Zhang

Tan

Liang

et al. 2019

IEEE Trans. Wireless Commun.

126

View full text Add to dashboard Cite

We consider a cognitive heterogeneous network (HetNet), in which multiple pairs of secondary users adopt sensing-based approaches to coexist with a pair of primary users on a certain spectrum band. Due to imperfect spectrum sensing, secondary transmitters (STs) may cause interference to the primary receiver (PR) and make it difficult for the PR to select a proper modulation and/or coding scheme (MCS). To deal with this issue, we exploit deep reinforcement learning (DRL) and propose an intelligent MCS selection algorithm for the primary transmission. To reduce the system overhead caused by MCS switchings, we further introduce a switching cost factor in the proposed algorithm. Simulation results show that the primary transmission rate of the proposed algorithm without the switching cost factor is 90% ∼ 100% of the optimal MCS selection scheme, which assumes that the interference from the STs is perfectly known at the PR as prior information, and is 30% ∼ 100% higher than those of the benchmark algorithms. Meanwhile, the proposed algorithm with the switching cost factor can achieve a better balance between the primary transmission rate and system overheads than both the optimal algorithm and benchmark algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Deep Reinforcement Learning-Based Modulation and Coding Scheme Selection in Cognitive Heterogeneous Networks

Zhang

Tan

Liang

et al. 2019

IEEE Trans. Wireless Commun.

126

View full text Add to dashboard Cite

show abstract

“…In addition, other spectrum sharing schemes such as spectrum trading, leasing, mobility and harvesting have been studied in order to enhance spectral efficiency as well as energy efficiency of future wireless networks [10]. Moreover, Software Defined Networking (SDN)-based approach can be applied to manage the spectral opportunities dynamically based on the distributed inputs reported from heterogeneous nodes of 5G networks [16].…”

Section: A Motivationmentioning

confidence: 99%

“…Another promising solution to address the problem of spectrum scarcity is to enhance the utilization of available radio frequency bands by employing Dynamic Spectrum Sharing (DSS) mechanisms [10][11][12][13]. This solution is motivated by the fact that a significant amount of licensed radio spectrum remains under-utilized in the spatial and temporal domains, and thus it aims to address the paradox between the spectrum shortage and under-utilization.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Sharma

Bogale

et al. 2018

IEEE Commun. Surv. Tutorials

213

View full text Add to dashboard Cite

Full-Duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth generation (5G) of wireless communications due to its advantages including potential doubling of the capacity, reduced end-to-end and feedback delays, improved network secrecy and efficiency, and starting with a detailed overview of FD-enabled DSS, we provide a comprehensive survey of recent advances in this domain. We then highlight several potential techniques for enabling FD operation in DSS wireless systems. Subsequently, we propose a novel communication framework to enable CST in DSS systems by employing a power control-based SI mitigation scheme and carry out the throughput performance analysis of this proposed framework. Finally, we discuss some open research issues and future directions with the objective of stimulating future research efforts in the emerging FD-enabled DSS wireless systems.

show abstract

“…Several spectrum sharing schemes have been recommended to enhance the spectrum efficiency by allowing utilization of unused or underutilized spectrum temporally and geographically. 10 However, these schemes actually involve not only spectrum sharing but also economic transactions between various parties, thus introducing spectrum trading. By definition, spectrum trading is the mechanism of buying and selling the rights of spectrum frequencies.…”

Section: Introductionmentioning

confidence: 99%

Matching theory as enabler of efficient spectrum management in 5G networks

Tsirakis

López-Aguilera

Agapiou

et al. 2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

This paper analyzes the spectrum trading problem in virtualized fifth generation networks to enhance the network performance with respect to the spectrum utilization. The problem is modeled as a many‐to‐many matching game with utility‐based preferences and determines the matching between mobile network operators and mobile virtual network operators. The two proposed versions of utility functions for each set aim at maximizing the satisfaction of both sets with conflicting interests and improving the overall spectrum efficiency. In the simulation evaluation, the proposed scheme is compared with three different schemes in terms of the system utility, individual, and pair matching satisfaction. We also investigate the scalability aspects, the strategy plan impact on the matching performance of our proposed scheme, and at the same time, we attempt to make appropriate assumptions closer to reality. Our proposed scheme shows much better performance than the other schemes achieving a quite high level of satisfaction for the matching result on both sets.

show abstract

Advanced spectrum sharing in 5G cognitive heterogeneous networks

Cited by 114 publications

References 14 publications

Deep Reinforcement Learning-Based Modulation and Coding Scheme Selection in Cognitive Heterogeneous Networks

Deep Reinforcement Learning-Based Modulation and Coding Scheme Selection in Cognitive Heterogeneous Networks

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Matching theory as enabler of efficient spectrum management in 5G networks

Contact Info

Product

Resources

About