A Spectrum Sharing Solution for the Efficient Use of mmWave Bands in 5G Cellular Scenarios

Rebato, Mattia; Zorzi, Michele

doi:10.1109/dyspan.2018.8610481

Cited by 12 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [101], a spectrum and bandwidth efficiency problem is formulated for spectrum and system band-sharing architecture to optimize spectrum management based on Licensed Spectrum Access (LSA). The emulation consequences revealed that the devised approach has improved SE and bandwidth efficiency with user equipment (UEs) fairness.…”

Section: ) Spectrum Efficiency-bandwidthmentioning

confidence: 99%

Toward Efficient 6G IoT Networks: A Perspective on Resource Optimization Strategies, Challenges, and Future Directions

Liwen,

Qamar,

Liaqat

et al. 2024

IEEE Access

View full text Add to dashboard Cite

The next generation (6G) wireless communication technology has super advantages in high transmission rates scenarios. Internet of Things (IoT) has been applied in recent years due to its wide connection. However, effective resource optimization methods must be analyzed to meet the high requirements of key performance indicators in 6G wireless IoT networks. This paper discusses a general investigation of the resource optimization strategies in the 6G IoT system. The study aims to find the main solutions to optimize 6G IoT network performance. First, an overall summary of current research is preferred resource optimization in latency, reliability, Energy Efficiency (EE), Spectrum Efficiency (SE), bandwidth utilization efficiency, rate, and power efficiency. Second, we propose the multi-indicator tradeoff strategies associated with the latest resource optimization approaches and investigate optimal strategies. Furthermore, we show the limitations of the current resource optimization methods and discuss the future works of resource optimization for IoT devices in 6G communication. Our survey aims to help researchers optimize 6G IoT network performance using advanced techniques.

show abstract

Section: ) Spectrum Efficiency-bandwidthmentioning

confidence: 99%

Toward Efficient 6G IoT Networks: A Perspective on Resource Optimization Strategies, Challenges, and Future Directions

Liwen,

Qamar,

Liaqat

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…are derived in [38] and [34] respectively. By relating (16) and 17into (14), after terms irrelevant to k being removed, the optimization of BICe can be rearranged as the following…”

Section: A a Bayesian-information-criteria-based Estimatormentioning

confidence: 99%

“…TVWS featuring wide bandwidth and sparse spectrum usage by PUs is particularly suitable for the implementation of CSS techniques [13]. With the evolution of communication system towards the fifth-generation, recent proposals are present that cellular services at millimeter-wave (mmWave) bands, with multiple operators potentially servicing overlapping small areas and coexisiting with other crucial wireless services, could employ a spectrum sharing and DSA model [14]. Real-time spectrum sensing for such mmWave DSA applications, where the bandwidth can span multiple gigahertz, poses larger challenges on the sampling rate, and sub-Nyquist techniques could be promising candidates.…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Subspace-Aided Compressive Spectrum Sensing Over Wideband Whitespace

Zhang

Gao

2019

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

Compressive sensing (CS) techniques have been proposed for wideband spectrum sensing applications to achieve sub-Nyquist-rate sampling. The complexity of CS recovery algorithm and the detection performance against noise are two of the main challenges of the implementation of compressive spectrum sensing (CSS). Greedy algorithms have been of particular interest in CSS due to low complexity. We firstly propose a novel spectrum sparsity estimation scheme directly from sub-Nyquist measurements, with which the computational effort of greedy pursuit algorithms can be saved and recovery performance improved. Besides, the spectrum sparsity estimates also enable hard detection of channel occupancy where threshold adaption for energy detection is avoided. Moreover, with the detected dimension of signal subspace, we propose to implement joint-block-sparse multiple-measurementvector (MMV) model of CSS whose dimension can be reduced to minimum and meanwhile a large portion of noise is removed. The proposed MMV model with noise and dimension reduction further improves the detection performance and also keeps the complexity low. Finally, we generalize the hard thresholding pursuit (HTP) algorithm to recover joint-block-sparse signals. In simulations, the detection performance and complexity of the proposed CSS scheme show striking superiority against multiple benchmarking schemes.

show abstract

“…Work in [5]- [9] discuss various approaches and challenges in beam based spectrum sharing among multiple networks.…”

Section: Introductionmentioning

confidence: 99%

Secure mmWave Spectrum Sharing with Autonomous Beam Scheduling for 5G and Beyond

Bhuyan

Zhang

et al. 2022

2022 IEEE 22nd Annual Wireless and Microwave Technology Conference (WAMICON)

View full text Add to dashboard Cite

Spectrum Sharing (SS) has seen a renewed set of initiatives in 5G with the availability of shared and unlicensed spectrum bands that can be used by multiple cellular service providers and private cellular networks. Beam based transmission, instead of the traditional sector based transmission in conjunction with the spectrum agility of the 5G New Radio (NR) has brought new opportunities to optimized sharing of spectrum. Currently in the U.S., a centralized Spectrum Access Server (SAS) is used to co-ordinate spectrum sharing among networks sharing the same spectrum band. However, SAS becomes a focal point for security attacks and a performance bottleneck. In addition, SAS relies on an Environmental Sensor Network (ESN), separate from the 5G network. Without trusted spectral occupancy information, false reporting of spectrum sensing data can create sub-optimal and unfair spectrum usage. This paper summarizes our recent research findings in using a decentralized scheme for multiple networks to securely share spectrum with autonomous beam scheduling : 1) A new stochastic network framework based on Lyapunov Optimization approach is developed to optimize scheduling at the base stations; 2) Game theoretic (GT) approach is used to formulate the distributed scheduler; 3) Another distributed scheduler with Q-learning is presented that utilizes the Reinforcement Learning (RL) approach; 4) The performance and convergence rate of these distributed solutions to use shared and unlicensed spectrum are compared with existing solutions. Conditions under which the performance of these schedulers approach the theoretical upper bound, which is the performance possible with no interference among the operators sharing the spectrum, are presented; 5) The ability of a base station to use its own user equipment as sensors, for optimal spectrum sharing with base stations in other operator networks, is demonstrated to be an effective approach.

show abstract

A Spectrum Sharing Solution for the Efficient Use of mmWave Bands in 5G Cellular Scenarios

Cited by 12 publications

References 14 publications

Toward Efficient 6G IoT Networks: A Perspective on Resource Optimization Strategies, Challenges, and Future Directions

Toward Efficient 6G IoT Networks: A Perspective on Resource Optimization Strategies, Challenges, and Future Directions

Low-Complexity Subspace-Aided Compressive Spectrum Sensing Over Wideband Whitespace

Secure mmWave Spectrum Sharing with Autonomous Beam Scheduling for 5G and Beyond

Contact Info

Product

Resources

About