Packet-Size Optimization for Multiple-Input Multiple-Output Cognitive Radio Sensor Networks-Aided Internet of Things

Majumdar, Chitradeep; Lee, Doohwan; Patel, Aaqib; Merchant, S. N.; Desai, U.B.

doi:10.1109/access.2017.2687083

Cited by 17 publications

(12 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All in all, the derivation of optimal transmission policies can be considered an active research area that encompasses classic IoT networks. For example, in [33,34], packet size is found to have an important effect on IoT cognitive radio sensor networks and is consequently optimized to maximize network performance.…”

Section: Research On Optimal Transmission Policiesmentioning

confidence: 99%

Performance optimization of LoRa nodes for the future smart city/industry

Sandoval

García-Sánchez

2019

J Wireless Com Network

View full text Add to dashboard Cite

The application of long-range communication technologies such as LoRa to certain environments like smart cities/industries is a natural step forward towards the future IoT. However, the strict limitations imposed in some countries on the duty cycle of ISM bands can jeopardize this technological progress. To overcome this and, at the same time, improve IoT nodes' transmission and power efficiency, a novel mathematical model has been derived. Its numerical analysis leads to a closed-form formula that characterizes node performance in terms of its transmission policy. The maximization of this formula-required to increase node performance-is then posed as an optimization problem whose solution yields smart transmission policies that maximize throughput while limiting energy consumption. The results achieved under this approach are compared to those obtained using the ADR algorithm (the most extended mechanism for choosing transmission parameters in LoRaWAN networks) and to random/conservative policies to further highlight the benefits of the proposal. Results reveal that the proposed method outperforms ADR by 33.20%, the conservative policy by 91.81%, and the random policy by 238.8%.

show abstract

Section: Research On Optimal Transmission Policiesmentioning

confidence: 99%

Performance optimization of LoRa nodes for the future smart city/industry

Sandoval

García-Sánchez

2019

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…Majumdar and others proposed a multiple input-, multiple output-based, cognitive radio sensor network architecture for futuristic technologies, such as the IoT and machine-to-machine communications [28]. Raza and others presented a detailed discussion on design objectives, challenges, and solutions, for industrial wireless sensor networks [29].…”

Section: Related Workmentioning

confidence: 99%

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

Bayrakdar

2019

ETRI Journal

View full text Add to dashboard Cite

A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.

show abstract

“…Transmission is made more reliable since they reduce congestion and excessive packet loss [2]. "Cognitive Radio Sensor Networks (CRSNs) are the state-of-the-art communication paradigm for power constrained short range data communication" [3]. To practically realize CRSNs, the optimum packet size must be addressed since most of the optimum packet sizes available are meant for WSNs and/or CRNs and are not optimal for CRSNs [4].…”

Section: Introductionmentioning

confidence: 99%

“…To practically realize CRSNs, the optimum packet size must be addressed since most of the optimum packet sizes available are meant for WSNs and/or CRNs and are not optimal for CRSNs [4]. CRSNs are one of the possible technologies implemented for the Internet of Things (IoT) and other future machine-to-machine-based applications most of which are delay sensitive and power constrained [3]. The optimal packet size of CRSNs for maximizing energy efficiency is studied in [4].…”

Section: Introductionmentioning

confidence: 99%

A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks

Muwonge

Pei

Otim

et al. 2020

Sensors

View full text Add to dashboard Cite

To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the impact of transmission rate, transmission power or transmission delay alone, the complexity is aggravated by the simultaneous consideration of all these three variables jointly in addition to a channel selection variable, since it creates a non-convex problem. Our objective is to jointly optimize the three major variables; transmission power, rate and delay under constraints of Bit Error Rate (BER), interference and other channel limitations. We analyze how total power, rate and delay vary with packet size, network size, BER and interference. The resulting problem is solved using a branch-and-cut polyhedral approach. For simulation of results, we use MATLAB together with the state-of-the-art BARON software. It is observed that an increase in packet size generally leads to an increase in total rate, total power and total transmission delay. It is also observed that increasing the number of secondary users on the channel generally leads to an increased power, delay and rate.

show abstract

Packet-Size Optimization for Multiple-Input Multiple-Output Cognitive Radio Sensor Networks-Aided Internet of Things

Cited by 17 publications

References 40 publications

Performance optimization of LoRa nodes for the future smart city/industry

Performance optimization of LoRa nodes for the future smart city/industry

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks

Contact Info

Product

Resources

About