Dense Deployment of LoRa Networks: Expectations and Limits of Channel Activity Detection and Capture Effect for Radio Channel Access

Congduc Pham; Muhammad Ehsan

doi:10.3390/s21030825

Dense Deployment of LoRa Networks: Expectations and Limits of Channel Activity Detection and Capture Effect for Radio Channel Access

Sensors ◽

10.3390/s21030825 ◽

2021 ◽

Vol 21 (3) ◽

pp. 825

Author(s):

Congduc Pham ◽

Muhammad Ehsan

Keyword(s):

Radio Channel ◽

Design Guidelines ◽

Assessment Procedure ◽

Channel Access ◽

Capture Effect ◽

Channel Activity ◽

Activity Detection ◽

Radio Technology ◽

Clear Channel ◽

Access Mechanisms

With worldwide deployment of LoRa/LoRaWAN LPWAN networks in a large variety of applications, it is crucial to improve the robustness of LoRa channel access which is largely ALOHA-like to support environments with higher node density. This article presents extensive experiments on LoRa Channel Activity Detection and Capture Effect property in order to better understand how a competition-based channel access mechanisms can be optimized for LoRa LPWAN radio technology. In the light of these experimentation results, the contribution continues by identifying design guidelines for a channel access mechanism in LoRa and by proposing a channel access method with a lightweight collision avoidance mechanism that can operate without a reliable Clear Channel Assessment procedure. The proposed channel access mechanism has been implemented and preliminary tests show promising capabilities in increasing the Packet Delivery Rate in dense configurations.

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A Poisson Process-Based Random Access Channel for 5G and Beyond Networks

Mathematics ◽

10.3390/math9050508 ◽

2021 ◽

Vol 9 (5) ◽

pp. 508

Author(s):

Alaa Omran Almagrabi ◽

Rashid Ali ◽

Daniyal Alghazzawi ◽

Abdullah AlBarakati ◽

Tahir Khurshaid

Keyword(s):

Poisson Process ◽

Random Access ◽

Communication Technologies ◽

Channel Access ◽

Access Channel ◽

Machine Type Communications ◽

Equal Chance ◽

Random Access Channel ◽

Access Mechanisms

The 5th generation (5G) wireless networks propose to address a variety of usage scenarios, such as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). Due to the exponential increase in the user equipment (UE) devices of wireless communication technologies, 5G and beyond networks (B5G) expect to support far higher user density and far lower latency than currently deployed cellular technologies, like long-term evolution-Advanced (LTE-A). However, one of the critical challenges for B5G is finding a clever way for various channel access mechanisms to maintain dense UE deployments. Random access channel (RACH) is a mandatory procedure for the UEs to connect with the evolved node B (eNB). The performance of the RACH directly affects the performance of the entire network. Currently, RACH uses a uniform distribution-based (UD) random access to prevent a possible network collision among multiple UEs attempting to access channel resources. However, in a UD-based channel access, every UE has an equal chance to choose a similar contention preamble close to the expected value, which causes an increase in the collision among the UEs. Therefore, in this paper, we propose a Poisson process-based RACH (2PRACH) alternative to a UD-based RACH. A Poisson process-based distribution, such as exponential distribution, disperses the random preambles between two bounds in a Poisson point method, where random variables occur continuously and independently with a constant parametric rate. In this way, our proposed 2PRACH approach distributes the UEs in a probability distribution of a parametric collection. Simulation results show that the shift of RACH from UD-based channel access to a Poisson process-based distribution enhances the reliability and lowers the network’s latency.

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Fast tag identification for mobile RFID robots in manufacturing environments

Assembly Automation ◽

10.1108/aa-11-2020-0182 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Honggang Wang ◽

Ruixue Yu ◽

Ruoyu Pan ◽

Mengyuan Liu ◽

Qiongdan Huang ◽

...

Keyword(s):

Data Collection ◽

Sensor Data ◽

System Throughput ◽

Channel Activity ◽

Activity Detection ◽

Robot System ◽

Content Type ◽

Active Rfid ◽

Manufacturing Environments ◽

Uhf Band

Purpose In manufacturing environments, mobile radio frequency identification (RFID) robots need to quickly identify and collect various types of passive tag and active tag sensor data. The purpose of this paper is to design a robot system compatible with ultra high frequency (UHF) band passive and active RFID applications and to propose a new anti-collision protocol to improve identification efficiency for active tag data collection. Design/methodology/approach A new UHF RFID robot system based on a cloud platform is designed and verified. For the active RFID system, a grouping reservation–based anti-collision algorithm is proposed in which an inventory round is divided into reservation period and polling period. The reservation period is divided into multiple sub-slots. Grouped tags complete sub-slot by randomly transmitting a short reservation frame. Then, in the polling period, the reader accesses each tag by polling. When tags’ reply collision occurs, the reader tries to re-query collided tags once, and the pre-reply tags avoid collisions through random back-off and channel activity detection. Findings The proposed algorithm achieves a maximum theoretical system throughput of about 0.94, and very few tag data frame transmissions overhead. The capture effect and channel activity detection in physical layer can effectively improve system throughput and reduce tag data transmission. Originality/value In this paper, the authors design and verify the UHF band passive and active hybrid RFID robot architecture based on cloud collaboration. And, the proposed anti-collision algorithm would improve active tag data collection speed and reduce tag transmission overhead in complex manufacturing environments.

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