Performance analysis of cooperative diversity in land mobile satellite systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2013.Land Mobile Satellite Systems (LMSS) generally differ from other terrestrial wireless systems. The LMSS exhibit unique characteristics with regard to the physical layer, interference scenarios, channel impairements, propagation delay, link characteristics, service coverage, user and satellite mobility etc. Terrestrial wireless systems have employed the spatial diversity or MIMO (Multiple Input Multiple Output) technique in addressing the problem of providing uninterrupted service delivery to all mobile users especially in places where non-Line-of-Sight (NLoS) condition is prevalent (e.g. urban and suburban environments). For the LMSS, cooperative diversity has been proposed as a valuable alternative to the spatial diversity technique since it does not require the deployment of additional antennas in order to mitigate the fading effects. The basis of cooperative diversity is to have a group of mobile terminals sharing their antennas in order to generate a “virtual” multiple antenna, thus obtaining the same effects as the conventional MIMO system. However, the available cooperative diversity schemes as employed are based on outdated channel quality information (CQI) which is impracticable for LMSS due to its peculiar characteristics and its particularly long propagation delay. The key objective of this work is therefore to develop a cooperative diversity technology model which is most appropriate for LMSS and also adequately mitigates the outdated CQI challenge. To achieve the objective, the feasibility of cooperative diversity for LMSS was first analyzed by employing an appropriate LMSS channel model. Then, a novel Predictive Relay Selection (PRS) cooperative diversity scheme for LMSS was developed which adequately captured the LMSS architecture. The PRS cooperative scheme developed employed prediction algorithms, namely linear prediction and pattern-matching prediction algorithms in determining the future CQI of the available relay terminals before choosing the most appropriate relay for cooperation. The performance of the PRS cooperative diversity scheme in terms of average output SNR, outage probability, average channel capacity and bit error probability were simulated, then numerically analyzed. The results of the PRS cooperative diversity model for LMSS developed not only showed the gains resulting from introducing cooperative techniques in satellite communications but also showed improvement over other cooperative techniques that based their relay selection cooperation on channels with outdated quality information (CQI). Finally, a comparison between the results obtained from the various predictive models considered was carried out and the best prediction model was recommended for the PRS cooperation

Predictive relay-selection cooperative diversity in land mobile satellite systems

Cooperative diversity protocols promise a new dimension of diversity that provides better communication by engaging nearby relays in forming a ‘virtual’ array of antennas for combined signal transmission. The current incremental cooperative diversity algorithms incrementally select best relay(s) to cooperate based on the channel quality reported by the relays. However, the algorithms do not take into consideration the fact that the chosen best relay(s) at estimation may not always be best at the time of communication. This is due to the time delay between the relay selection and its transmission of signal (problem of outdated Channel Quality Information). To solve this problem, the concept of channel prediction is introduced and employed whereby each relay determines a predicted value of its Channel Quality Information (CQI) based on its past measurements. The paper therefore develops a novel predictive relay-selection (PRS) cooperative diversity model which seeks to improve Land Mobile Satellite (LMS) communication through prediction protocols. In the model, the chosen best relay is the one with the best predicted CQI value instead of the traditional outdated one. Performance analysis of outage probability and average bit error probability for the newly developed PRS cooperation shows that the PRS cooperation is better than direct and outdated CQI relay communication.http://onlinelibrary.wiley.com/doi/10.1002/sat.11182017-03-31hb2016Electrical, Electronic and Computer Engineerin

Improving link failure restoration in next-generation wireless sensor networks

Next-generation wireless sensor networks (xWSN) have applications in many emerging wireless technologies, such as fifth-generation, internet-of-things, device-to-device communications, e-health, e-agriculture, etc. For most of these xWSN applications, network reliability and robustness against failures are crucial considerations. In this paper, an appropriate network restoration model is developed to help achieve network protection and/or restoration for xWSN in the event of link failures. In the model, effective network restoration is achieved by investigating efficient pre-configured-cycle (p-cycle)-based restoration solutions for the xWSN. Furthermore, to achieve significant improvement in the capacity efficiency of the p-cycle solutions realised, the concepts of p-cycle selectivity, load redistribution and the use of single p-cycles for double failure restoration are investigated and incorporated in the network restoration design. The restoration model developed, alongside the various improvement concepts incorporated, is shown to achieve better performance in terms of average path length and total capacity cost when compared with similar restoration models for modern wireless communication applications.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Univerity of Pretoria, South Africa.http://www.elsevier.com/locate/arrayhj2022Electrical, Electronic and Computer Engineerin

Solving resource allocation problems in cognitive radio networks : a survey

Cognitive radio networks (CRN), in their quest to become the preferred next-generation wireless communication paradigm, will depend heavily on their ability to efficiently manage the limited resources at their disposal in meeting the demands of their numerous users and driving their operations. As a result, a considerable amount of research work has been recently dedicated to investigating and developing resource allocation (RA) models that capture the essentials of CRN. The various ideas put forward by researchers to address RA problems in CRN have been somewhat diverse, and somehow, there seem to be no links that bring cohesion and clarity of purpose and ideas. To address this problem and bridge the gap, in this paper, a comprehensive study on the prevalent techniques developed for addressing RA problems in CRN is carried out, with an intent to put some structure, relevance and meaning to the various solution approaches. The solution models are therefore grouped and/or classified based on certain outstanding criteria, and their strengths and weaknesses highlighted. Open-ended problems are identified, and suggestions for improving solution models are given. The study therefore gives good directions for further investigations on developing RA solutions in CRN.http://www.hindawi.com/journals/wcnam2017Electrical, Electronic and Computer Engineerin

Resource allocation in heterogeneous buffered cognitive radio networks

Resources available for operation in cognitive radio networks (CRN) are generally limited, making it imperative for efficient resource allocation (RA) models to be designed for them. However, in most RA designs, a significant limiting factor to the RA’s productivity has hitherto been mostly ignored, the fact that different users or user categories do have different delay tolerance profiles. To address this, in this paper, an appropriate RA model for heterogeneous CRN with delay considerations is developed and analysed. In themodel, the demands of users are first categorised and then, based on the distances of users fromthe controlling secondary user base station and with the assumption that the users are mobile, the user demands are placed in different queues having different service capacities and the resulting network is analysed using queueing theory. Furthermore, to achieve optimality in the RA process, an important concept is introduced whereby some demands fromone queue aremoved to another queue where they have a better chance of enhanced service, thereby giving rise to the possibility of an improvement in the overall performance of the network. The performance results obtained from the analysis, particularly the blocking probability and network throughput, show that the queueing model incorporated into the RA process can help in achieving optimality for the heterogeneous CRN with buffered data.http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1530-8677am2017Electrical, Electronic and Computer Engineerin

Optimal resource allocation solutions for heterogeneous cognitive radio networks

Cognitive Radio Networks (CRN) are currently gaining immense recognition as the most-likely next-generation wireless communication paradigm, because of their enticing promise of mitigating the spectrum scarcity and/or underutilisation challenge. Indisputably, for this promise to ever materialise, CRN must of necessity devise appropriate mechanisms to judiciously allocate their rather scarce or limited resources (spectrum and others) among their numerous users. ‘Resource Allocation (RA) in CRN', which essentially describes mechanisms that can effectively and optimally carry out such allocation, so as to achieve the utmost for the network, has therefore recently become an important research focus. However, in most research works on RA in CRN, a highly significant factor that describes a more realistic and practical consideration of CRN has been ignored (or only partially explored), i.e., the aspect of the heterogeneity of CRN. To address this important aspect, in this paper, RA models that incorporate the most essential concepts of heterogeneity, as applicable to CRN, are developed and the imports of such inclusion in the overall networking are investigated. Furthermore, to fully explore the relevance and implications of the various heterogeneous classifications to the RA formulations, weights are attached to the different classes and their effects on the network performance are studied. In solving the developed complex RA problems for heterogeneous CRN, a solution approach that examines and exploits the structure of the problem in achieving a less-complex reformulation, is extensively employed. This approach, as the results presented show, makes it possible to obtain optimal solutions to the rather difficult RA problems of heterogeneous CRN.http://www.elsevier.com/locate/dcanam2017Electrical, Electronic and Computer Engineerin

Resource allocation optimisation in heterogeneous cognitive radio networks

Cognitive radio networks (CRN) have been tipped as one of the most promising paradigms for next generation wireless communication, due primarily to its huge promise of mitigating the spectrum scarcity challenge. To help achieve this promise, CRN develop mechanisms that permit spectrum spaces to be allocated to, and used by more than one user, either simultaneously or opportunistically, under certain preconditions. However, because of various limitations associated with CRN, spectrum and other resources available for use in CRN are usually very scarce. Developing appropriate models that can efficiently utilise the scarce resources in a manner that is fair, among its numerous and diverse users, is required in order to achieve the utmost for CRN. 'Resource allocation (RA) in CRN' describes how such models can be developed and analysed. In developing appropriate RA models for CRN, factors that can limit the realisation of optimal solutions have to be identified and addressed; otherwise, the promised improvement in spectrum/resource utilisation would be seriously undermined. In this thesis, by a careful examination of relevant literature, the most critical limitations to RA optimisation in CRN are identified and studied, and appropriate solution models that address such limitations are investigated and proffered. One such problem, identified as a potential limitation to achieving optimality in its RA solutions, is the problem of heterogeneity in CRN. Although it is indeed the more realistic consideration, introducing heterogeneity into RA in CRN exacerbates the complex nature of RA problems. In the study, three broad classifications of heterogeneity, applicable to CRN, are identified; heterogeneous networks, channels and users. RA models that incorporate these heterogeneous considerations are then developed and analysed. By studying their structures, the complex RA problems are smartly reformulated as integer linear programming problems and solved using classical optimisation. This smart move makes it possible to achieve optimality in the RA solutions for heterogeneous CRN. Another serious limitation to achieving optimality in RA for CRN is the strictness in the level of permissible interference to the primary users (PUs) due to the activities of the secondary users (SUs). To mitigate this problem, the concept of cooperative diversity is investigated and employed. In the cooperative model, the SUs, by assisting each other in relaying their data, reduce their level of interference to PUs significantly, thus achieving greater results in the RA solutions. Furthermore, an iterative-based heuristic is developed that solves the RA optimisation problem timeously and efficiently, thereby minimising network complexity. Although results obtained from the heuristic are only suboptimal, the gains in terms of reduction in computations and time make the idea worthwhile, especially when considering large networks. The final problem identified and addressed is the limiting effect of long waiting time (delay) on the RA and overall productivity of CRN. To address this problem, queueing theory is investigated and employed. The queueing model developed and analysed helps to improve both the blocking probability as well as the system throughput, thus achieving significant improvement in the RA solutions for CRN. Since RA is an essential pivot on which the CRN's productivity revolves, this thesis, by providing viable solutions to the most debilitating problems in RA for CRN, stands out as an indispensable contribution to helping CRN realise its much-proclaimed promises.Thesis (PhD)--University of Pretoria, 2017.Electrical, Electronic and Computer EngineeringPhDUnrestricte

Quality of service provisioning through resource optimisation in heterogeneous cognitive radio sensor networks

Recently, cognitive radio sensor networks (CRSN) have evolved as a result of the introduction of cognitive capabilities to conventional wireless sensor networks. In most CRSN designs, secondary users and/or sensor nodes are permitted, under certain constraints, to use the limited resources of a primary network. One major challenge with CRSN is how to optimally appropriate and use the limited resources available in driving their communication demands. To overcome this challenge, in this paper, we develop a resource allocation (RA) model that is capable of achieving a target quality of service (QoS) demand for the heterogeneous CRSN, despite the huge resource constraints imposed on the network. The RA problem developed is a complex optimisation problem. We analyse and solve the complex RA problem using the optimisation approaches of integer linear programming, Lagrangian duality and by a heuristic. We then study the performance of the RA model for the different solution approaches investigated. The results obtained are used to establish the optimality-complexity trade-off, which is a critical criterion for QoS decision-making in practical CRSN applications.The SENTECH Chair in BWMC at the University of Pretoria.http://www.elsevier.com/locate/comcomhj2022Education Innovatio

Resource optimisation in 5G and Internet-of-Things networking

Fifth generation (5G), the currently evolving communication standard, promises better performance in terms of capability, capacity, speed, latency, etc. than recent technologies such as WiMax, LTE and LTE-Advanced. Similarly, the internet-of-things (IoT), the newly developing internet computing paradigm, has the potential for providing seamless, efficient human-device and device-device communication and connectivity. Both 5G and IoT technologies are definite key players in achieving a smart, interconnected world. However, one great limitation is that the resources needed to drive 5G and IoT technologies are extremely limited. To address this challenge, efficient solution models that optimise the use of the scarce resources are required. In this paper, an investigation into the various optimisation approaches that are being explored for addressing resource problems in 5G and IoT is carried out. The solution approaches are categorised and strengths and weaknesses are revealed, while new and exciting research directions are discussed. One of the research areas identified, namely, the aspect of spectrum availability, is addressed. In addressing the spectrum scarcity problem of 5G and IoT, a solution model is developed whereby an allotted spectrum is employed by two networks simultaneously. The results obtained from the analysis show that with such arrangement, a marked improvement in resource usage and overall productivity of the 5G and IoT network is achievable.The Advanced Sensor Networks SARChi Chair program, co-hosted by University of Pretoria (UP) and Council for Scientific and Industrial Research (CSIR), through the National Research Foundation (NRF) of South Africa.http://link.springer.com/journal/112772021-01-01hj2020Electrical, Electronic and Computer Engineerin

Network restoration in wireless sensor networks for next-generation applications

This paper investigates highly efficient network restoration models for wireless sensor networks (WSNs) to be deployed for next-generation (xG) applications. The developed network restoration models are designed with two main goals in mind. The first goal is to optimize network resource utilization, and the second is to protect the network against failures. In realizing the goal of optimizing resource usage, a peculiar feature of WSNs is exploited, namely, their ability to remain in active service even when one or more of their active elements (sensor nodes and/or connecting links) fail. To achieve the second goal of network protection, we leverage the advantage of p-cycle-based restoration solutions - the fact that they can provide ring-like recovery speeds with mesh-like capacity efficiencies - in developing optimal p-cycle restoration models that provide sufficient protection for the network against both link and node failures. In the restoration models developed, we employ a selection process that jointly considers the shortest lengths, best topologies, and capacity requirements of the available p-cycles in achieving new capacity-optimal p-cycle-based restoration solutions for the network. Comparative results obtained show that our developed selection-based capacity-efficient p-cycle restoration solutions for WSNs outperform other similar approaches for both network realization and protection, making them particularly ideal for xG applications.The Advanced Sensor Networks SARChI Chair program, co-hosted by the University of Pretoria (UP) and Council for Scientific and Industrial Research (CSIR), through the National Research Foundation (NRF) of South Africa.https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7361hj2019Electrical, Electronic and Computer Engineerin