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

Bernard Ssajjabbi Muwonge,Tingrui Pei,Fred Mayambala,Julianne Sansa Otim

doi:10.3390/s20174907

Bernard Ssajjabbi Muwonge, Tingrui Pei + Show 2 more

Open Access

https://doi.org/10.3390/s20174907

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Abstract

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.

Highlights

The transmission medium in Wireless Sensor Networks (WSNs) is under-utilized due to the bursty traffic resulting from the network’s event-driven communication [1]
The results that are obtained are used to demonstrate the effect of joint optimization of transmission power, transmission rate and transmission delay in a CRWSN
We have jointly optimized three variables namely; transmission rate, transmission power and transmission delay needed by the secondary users (SUs) to transmit in a Cognitive Radio Sensor Networks (CRSNs) amidst a number of constraints including interference, Bit Error Rate (BER), boundary constraints on the variables, channel power and rate constraints

Summary

Introduction

The transmission medium in Wireless Sensor Networks (WSNs) is under-utilized due to the bursty traffic resulting from the network’s event-driven communication [1]. The scarce, yet underutilized resources must be efficiently allocated for better utilization. Unlike WSNs, cognitive radio sensor nodes are intelligent and can access multiple redundant channels. This enables them address some challenges of WSNs that traditionally employ fixed spectrum allocation and are constrained in communication resources and processing capacity. 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]

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Conclusion