Efficient Link Scheduling in Wireless Networks Under Rayleigh-Fading and Multiuser Interference

Yu, Jiguo; Yu, Kan; Yu, Dongxiao; Liu, Weifeng; Cheng, Xiuzhen; Chen, Honglong; Cheng, Wei

doi:10.1109/twc.2020.2994998

Cited by 29 publications

(25 citation statements)

References 41 publications

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“…Similar assumption was also applied in the previous works (e.g. [3], [5], [6]). However, their works were unsatisfactory to provide a better scheduling performance which refers to scheduling more concurrent links in a single slot for the MLS, and using less slots to schedule all links for the SLS.…”

Section: Introductionmentioning

confidence: 81%

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Efficient Link Scheduling Solutions for the Internet of Things Under Rayleigh Fading

Cheng

et al. 2021

IEEE/ACM Trans. Networking

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Link scheduling is an appealing solution for ensuring the reliability and latency requirements of Internet of Things (IoT). Most existing results on the link scheduling problem were based on the graph or SINR (Signal-to-Interference-plus-Noise-Ratio) models, which ignored the impact of the random fading gain of the signals strength. In this paper, we address the link scheduling problem under the Rayleigh fading model. Both Shortest Link Scheduling (SLS) and Maximum Link Scheduling (MLS) problems are studied. In particular, we show that a set of links can be activated simultaneously under Rayleigh fading model if all link SINR constraints are satisfied. Based on the analysis of previous Link Diversity Partition (LDP) algorithm, we propose an Improved LDP (ILDP) algorithm and a centralized algorithm by localizing the global interference (denoted by CLT), building on which we design a distributed CLT algorithm (denoted by RCRDCLT) that converges to a constant approximation factor of the optimum with the time complexity of O(ln n), where n is the number of links. Furthermore, executing repeatedly RCRDCLT can solve the SLS with an approximation factor of Θ(ln n). Extensive simulations indicate that CLT is more effective than previous six popular link scheduling algorithms, and RCRDCLT has the lowest time complexity while only losses a constant fraction of the optimum schedule.

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Section: Introductionmentioning

confidence: 81%

“…However, the model leads to the design and analysis of link scheduling algorithms more challenging and difficult in return. Consequently, there are few works focusing on link scheduling subject to Rayleigh fading constraint (e.g., [3]- [6]).…”

Section: Introductionmentioning

confidence: 99%

Efficient Link Scheduling Solutions for the Internet of Things Under Rayleigh Fading

Cheng

et al. 2021

IEEE/ACM Trans. Networking

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“…The height and the effective height of the vehicle are expressed as

and

. The velocity of light in free space is represented by c. The Rayleigh fading model is a common model that can represent multipath fading in real-world environments [ 48 , 49 ]. In this work, multipath fading is modeled as Rayleigh fading to represent the LA city environment, which follows the exponential distribution with unit mean.…”

Section: Proposed Ml-based Cell Selection Strategymentioning

confidence: 99%

Enhancing 5G Small Cell Selection: A Neural Network and IoV-Based Approach

Alablani

Arafah

2021

Sensors

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The ultra-dense network (UDN) is one of the key technologies in fifth generation (5G) networks. It is used to enhance the system capacity issue by deploying small cells at high density. In 5G UDNs, the cell selection process requires high computational complexity, so it is considered to be an open NP-hard problem. Internet of Vehicles (IoV) technology has become a new trend that aims to connect vehicles, people, infrastructure and networks to improve a transportation system. In this paper, we propose a machine-learning and IoV-based cell selection scheme called Artificial Neural Network Cell Selection (ANN-CS). It aims to select the small cell that has the longest dwell time. A feed-forward back-propagation ANN (FFBP-ANN) was trained to perform the selection task, based on moving vehicle information. Real datasets of vehicles and base stations (BSs), collected in Los Angeles, were used for training and evaluation purposes. Simulation results show that the trained ANN model has high accuracy, with a very low percentage of errors. In addition, the proposed ANN-CS decreases the handover rate by up to 33.33% and increases the dwell time by up to 15.47%, thereby minimizing the number of unsuccessful and unnecessary handovers (HOs). Furthermore, it led to an enhancement in terms of the downlink throughput achieved by vehicles.

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“…Experimental work conducted in Manhattan [19] found that Rayleigh fading can be a useful model in heavily built-up city centers where there is no line of sight between the transmitter and receiver and many buildings and other objects attenuate, reflect, refract, and diffract the signals. In recent years, the Rayleigh fading model has been considered in numerous research works, such as [20,21,22,23,24].…”

Section: Introductionmentioning

confidence: 99%

Shortest Link Scheduling in Wireless Networks Under The Rayleigh Fading Model

Huang

et al. 2021

Preprint

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Many shortest link scheduling algorithms adopt non-fading SINR interference model, which assumes that the received signal power will always remain determinate as long as the transmission power of the corresponding sender is fixed. In fact, because environment always influences the propagation of radio signals, the received signal power is by no means a certain value. Rayleigh fading is a statistical model for radio signals propagation. It assumes that the strength of a signal on a receiver is a random variable, varying with the Rayleigh distribution. This paper proposes a shortest link scheduling algorithm under the Rayleigh fading model (SLSRF). The SLSRF partitions the wireless network area into hexagons and colors the hexagons with 3 different colors such that two neighboring hexagons have different colors. The senders of the links scheduled simultaneously are arranged in hexagons with the same color. The correctness of the SLSRF is proved through theoretical analysis, and the efficiency is illustrated by elaborate simulations. Our simulation results demonstrate that the schedule delay of SLSRF is less than that of some results under the non-fading SINR interference model. Furthermore, we extend the SLSRF to a distributed version, which is suitable for large wireless networks.

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Efficient Link Scheduling in Wireless Networks Under Rayleigh-Fading and Multiuser Interference

Cited by 29 publications

References 41 publications

Efficient Link Scheduling Solutions for the Internet of Things Under Rayleigh Fading

Efficient Link Scheduling Solutions for the Internet of Things Under Rayleigh Fading

Enhancing 5G Small Cell Selection: A Neural Network and IoV-Based Approach

Shortest Link Scheduling in Wireless Networks Under The Rayleigh Fading Model

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