Abstract
Maritime explorations may suffer from unwanted situations such as delays, insecurity, congestions, and collisions, etc., which may arise from severe environmental conditions. Thus, there is a need to develop proper techniques that will improve the overall quality of service (QoS) of marine users. This work aims to address the limitations of wireless transmissions over maritime communication systems using channel estimation (CE) by designing and verifying the performances of two estimators named inter-symbol interference/average noise reduction (ISI/ANR) and reweighted error-reducing (RER) for aggrandizing the quality of nautical radio transmissions. To show that adopting accurate and stable CE methods can considerably increase the QoS requirements of marine networks, the performances of the proposed estimators are analysed in comparison to traditional methods under signal propagations assuming both line of sight (Rician) and Non-line of sight (Rayleigh) conditions. The adoption of a reweighting attractor in addition to the introduction of a variable leakage factor controlled log-sum penalty function to our proposed RER estimator provides additional stability for the estimation of oceanographic channels. Results obtained highlight that the proposed estimator demonstrates a performance gain of over 1 dB at a data rate of 100 bps under severe fading environments in comparison to the customary RLS technique. At an MSE of 10−2, the RER method under slow fading channels show a performance gain of about 1 dB when compared to the traditional RLS method while similarly showing superiority gain of about 0.6 dB over RLS method assuming fast fading Rayleigh channel conditions.
Highlights
T HE paradigm of internet of things (IoT) can be described as a fascinating system of interconnected computing devices with crucial application scenarios in the fast emerging fifth generation (5G) networks and beyond [1]
We propose two novel channel estimation (CE) techniques for improving the performances of maritime communication systems named reweighted error-reducing (RER) and inter-symbol interference/average noise reduction (ISI/ANR) CE that both attempt to improve the performance of conventional schemes such as maximum likelihood (ML) based estimation and recursive least squares (RLS) techniques in order to reduce the CE error of the maritime communication network using combinational techniques that involve summing the instantaneous square error with a log-sum penalty which is subsequently realised by the normalisation of the Manhattan distance of the system channel impulse response (CIR)
It can be observed that the relative CE performances of the estimation schemes when signals propagate under slow fading channel environmental conditions are noticeably superior in comparison to system performances of corresponding channels that are characterised by fast fading CIR scenarios
Summary
T HE paradigm of internet of things (IoT) can be described as a fascinating system of interconnected computing devices with crucial application scenarios in the fast emerging fifth generation (5G) networks and beyond [1] This indispensable paradigm is essential in applications ranging from smart societies, industrial applications and security etc. The maritime industry in is faced with numerous binding constraints which may arise from either anthropogenic or naturogenic conditions like delivery and traffic clearance delays, environmental degradation (oil and toxic waste spillages), congestion control management, insecurity and inefficient road networks [2] These maritime limitations can be mitigated by deploring the IoT in what is know as the internet of maritime things (IoMT), where sensors are positioned at strategic locations to enhance the monitoring of maritime environments in addition to the prevention of disaster occurrences.
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