303 research outputs found

    Self-organized beam scheduling as an enabler for coexistence in 5G unlicensed bands

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    In order to support user data-rates of Gbps and above in the fifth generation(5G)communication systems, millimetre-wave(mm-wave) communication is proposed as one of the most important enabling technologies. In this paper, we consider the spectrum bands shared by 5G cellular base stations (BS) and some existing networks, such as WiGig and proposed a method for spectrally efficient coexistence of multiple interfering BSs through adaptive self-organized beam scheduling. These BSs might use multiple radio access technologies belonging to multiple operators and are deployed in the unlicensed bands, such as 60GHz. Different from the recently emerging coexistence scenarios in the unlicensed 5GHz band,where the proposed methods are based on omni-directional transmission, beamforming needs to be employed in mm-wave bands to combat the high path loss problem. The proposed method is concerned with this new scenario of communication in the unlicensed bands where(a)beam-forming is mandatory to combat severe path loss, (b) without optimal scheduling of beams mutual interference could be severe due to the possibility of beam-collisions, (c)unlike LTE which uses time-frequency resource blocks, a new resource, i.e., the beam direction, is used as mandatory feature. We propose in this paper a novel multi-RAT coexistence mechanism where neighbouring 5G BSs, each serving their own associated users, schedule their beam configurations in a self-organized manner such that their own utility function, e.g. spectral efficiency, is maximized. The problem is formulated as a combinatorial optimization problem and it is shown via simulations that our proposed distributed algorithms yield a comparable spectral efficiency for the entire networks as that using an exhaustive search, which requires global coordination among coexisting RATs and also has a much higher algorithmic complexity

    Planning Capacity for 5G and Beyond Wireless Networks by Discrete Fireworks Algorithm With Ensemble of Local Search Methods

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    In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wireless network consists of base stations (BSs), relay stations (RSs), and user equipment (UEs). Wireless network planning (WNP) should decide the placement of BSs and RSs to the candidate sites and decide the possible connections among them and their further connections to UEs. The objective of the planning is to minimize the hardware and operational cost while planning capacity of a 5G and beyond wireless networks. The formulated WNP is an integer programming problem. Finding an optimal solution by using exhaustive search is not practical due to the demand for high computing resources. As a practical approach, a new population-based meta-heuristic algorithm is proposed to find a high-quality solution. The proposed discrete fireworks algorithm (DFWA) uses an ensemble of local search methods: insert, swap, and interchange. The performance of the proposed DFWA is compared against the low-complexity biogeography-based optimization (LC-BBO), the discrete artificial bee colony (DABC), and the genetic algorithm (GA). Simulation results and statistical tests demonstrate that the proposed algorithm can comparatively find good-quality solutions with moderate computing resources

    Improved GWO Algorithm for UAV Path Planning on Crop Pest Monitoring

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    Agricultural information monitoring is the monitoring of the agricultural production process, and its task is to monitor the growth process of major crops systematically. When assessing the pest situation of crops in this process, the traditional satellite monitoring method has the defects of poor real-time and high operating cost, whereas the pest monitoring through Unmanned Aerial Vehicles (UAVs) effectively solves the above problems, so this method is widely used. An important key issue involved in monitoring technology is path planning. In this paper, we proposed an Improved Grey Wolf Optimization algorithm, IGWO, to realize the flight path planning of UAV in crop pest monitoring. A map environment model is simulated, and information traversal is performed, then the search of feasible paths for UAV flight is carried out by the Grey Wolf Optimization algorithm (GWO). However, the algorithm search process has the defect of falling into local optimum which leading to path planning failure. To avoid such a situation, we introduced the probabilistic leap mechanism of the Simulated Annealing algorithm (SA). Besides, the convergence factor is modified with an exponential decay mode for improving the convergence rate of the algorithm. Compared with the GWO algorithm, IGWO has the 8.3%, 16.7%, 28.6% and 39.6% lower total cost of path distance on map models with precision of 15, 20, 25 and 30 respectively, and also has better path planning results in contrast to other swarm intelligence algorithms

    Differential Evolution in Wireless Communications: A Review

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    Differential Evolution (DE) is an evolutionary computational method inspired by the biological processes of evolution and mutation. DE has been applied in numerous scientific fields. The paper presents a literature review of DE and its application in wireless communication. The detailed history, characteristics, strengths, variants and weaknesses of DE were presented. Seven broad areas were identified as different domains of application of DE in wireless communications. It was observed that coverage area maximisation and energy consumption minimisation are the two major areas where DE is applied. Others areas are quality of service, updating mechanism where candidate positions learn from a large diversified search region, security and related field applications. Problems in wireless communications are often modelled as multiobjective optimisation which can easily be tackled by the use of DE or hybrid of DE with other algorithms. Different research areas can be explored and DE will continue to be utilized in this contex

    Disaster management in industrial areas: perspectives, challenges and future research

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    Purpose: In most countries, development, growth, and sustenance of industrial facilities are given utmost importance due to the influence in the socio-economic development of the country. Therefore, special economic zones, or industrial areas or industrial cities are developed in order to provide the required services for the sustained operation of such facilities. Such facilities not only provide a prolonged economic support to the country but it also helps in the societal aspects as well by providing livelihood to thousands of people. Therefore, any disaster in any of the facilities in the industrial area will have a significant impact on the population, facilities, the economy, and threatens the sustainability of the operations. This paper provides review of such literature that focus on theory and practice of disaster management in industrial cities. Design/methodology/approach: In the paper, content analysis method is used in order to elicit the insights of the literature available. The methodology uses search methods, literature segregation and developing the current knowledge on different phases of industrial disaster management. Findings: It is found that the research is done in all phases of disaster management, namely, preventive phase, reactive phase and corrective phase. The research in each of these areas are focused on four main aspects, which are facilities, resources, support systems and modeling. Nevertheless, the research in the industrial cities is insignificant. Moreover, the modeling part does not explicitly consider the nature of industrial cities, where many of the chemical and chemical processing can be highly flammable thus creating a very large disaster impact. Some research is focused at an individual plant and scaled up to the industrial cities. The modeling part is weak in terms of comprehensively analyzing and assisting disaster management in the industrial cities. Originality/value: The comprehensive review using content analysis on disaster management is presented here. The review helps the researchers to understand the gap in the literature in order to extend further research for disaster management in large scale industrial cities.Peer Reviewe

    Disaster management in industrial areas: Perspectives, challenges and future research

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    Purpose: In most countries, development, growth, and sustenance of industrial facilities are given utmost importance due to the influence in the socio-economic development of the country. Therefore, special economic zones, or industrial areas or industrial cities are developed in order to provide the required services for the sustained operation of such facilities. Such facilities not only provide a prolonged economic support to the country but it also helps in the societal aspects as well by providing livelihood to thousands of people. Therefore, any disaster in any of the facilities in the industrial area will have a significant impact on the population, facilities, the economy, and threatens the sustainability of the operations. This paper provides review of such literature that focus on theory and practice of disaster management in industrial cities. Design/methodology/approach: In the paper, content analysis method is used in order to elicit the insights of the literature available. The methodology uses search methods, literature segregation and developing the current knowledge on different phases of industrial disaster management. Findings: It is found that the research is done in all phases of disaster management, namely, preventive phase, reactive phase and corrective phase. The research in each of these areas are focused on four main aspects, which are facilities, resources, support systems and modeling. Nevertheless, the research in the industrial cities is insignificant. Moreover, the modeling part does not explicitly consider the nature of industrial cities, where many of the chemical and chemical processing can be highly flammable thus creating a very large disaster impact. Some research is focused at an individual plant and scaled up to the industrial cities. The modeling part is weak in terms of comprehensively analyzing and assisting disaster management in the industrial cities. Originality/value: The comprehensive review using content analysis on disaster management is presented here. The review helps the researchers to understand the gap in the literature in order to extend further research for disaster management in large scale industrial cities.Scopu

    Cloud Computing Strategies for Enhancing Smart Grid Performance in Developing Countries

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    In developing countries, the awareness and development of Smart Grids are in the introductory stage and the full realisation needs more time and effort. Besides, the partially introduced Smart Grids are inefficient, unreliable, and environmentally unfriendly. As the global economy crucially depends on energy sustainability, there is a requirement to revamp the existing energy systems. Hence, this research work aims at cost-effective optimisation and communication strategies for enhancing Smart Grid performance on Cloud platforms

    Parallel hardware architecture for JPEG-LS based on domain decomposition using context sets

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    This thesis investigates the scope of parallelism of the lossless JPEG-LS encoder. The input is not taken to be the entire image anymore; instead it is streams of pixels from an image sensor in every clock cycle. So the data dependencies that already exist due to the context modelling process and the effect of incomplete image data were analyzed thoroughly here. Other approaches of parallelism in JPEG-LS (e.g. pipelined hardware or software implementations that modify the context update procedures) deviate from the standard defined by ISO/ITU. On the other hand, the proposed technique here is fully compatible to the standard. In this work, a unique pixel loading mechanism (i.e. in the form that the encoder expects them to be) was developed from the streams of pixel. Later in order to store the pixels of the same context that are yet to be processed, another unique buffering mechanism was developed. However the context distribution of individual pixel determines the maximum achievable parallelism and thus a fixed value is not guaranteed in any case. The thesis also presents a vhdl implementation of the proposed parallel JPEG-LS encoder. The target hardware for this design was an FPGA board (Virtex 5). The design was also compared with the sequential hardware implementation and other parallel implementation in terms of speed up mainly. However there were some obstacles that restricted the actual synthesis. Possible reasons behind them are discussed with further suggestions for future work
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