Throughput and Collision Analysis of Multi-Channel Multi-Stage Spectrum Sensing Algorithms

Multi-stage sensing is a novel concept that refers to a general class of spectrum sensing algorithms that divide the sensing process into a number of sequential stages. The number of sensing stages and the sensing technique per stage can be used to optimize performance with respect to secondary user throughput and the collision probability between primary and secondary users. So far, the impact of multi-stage sensing on network throughput and collision probability for a realistic network model is relatively unexplored. Therefore, we present the first analytical framework which enables performance evaluation of different multi-channel multi-stage spectrum sensing algorithms for Opportunistic Spectrum Access networks. The contribution of our work lies in studying the effect of the following parameters on performance: number of sensing stages, physical layer sensing techniques and durations per each stage, single and parallel channel sensing and access, number of available channels, primary and secondary user traffic, buffering of incoming secondary user traffic, as well as MAC layer sensing algorithms. Analyzed performance metrics include the average secondary user throughput and the average collision probability between primary and secondary users. Our results show that when the probability of primary user mis-detection is constrained, the performance of multi-stage sensing is, in most cases, superior to the single stage sensing counterpart. Besides, prolonged channel observation at the first stage of sensing decreases the collision probability considerably, while keeping the throughput at an acceptable level. Finally, in realistic primary user traffic scenarios, using two stages of sensing provides a good balance between secondary users throughput and collision probability while meeting successful detection constraints subjected by Opportunistic Spectrum Access communication

A question of trans-boudary rivers: Legal rules, a coherent system or a vacant canyon: Towards a constructivist approach

Trans-boundary Rivers form an important context for relations between multiple sovereign states. The paper tackles the dynamics of a state’s behaviour, regarding trans-boundary Rivers, through time so that state relations are not a constant competition or cooperation. The paper responds to the behavioural changes amongst states by adopting a constructivist approach. By using constructivist approach, this paper argues that legal norms are generated through interactions and communications between states. Multiple criteria include political, geographic, economic, and legal contexts determine state relations. The Indus and Euphrates basins demonstrate how legal norms are determined by each state subject to their geographic, economic and political conditions. The paper concludes that the economic interest is a key variable towards cooperation between riparian states. The most significant message of the thesis, obviously, if the national interests of states in question are willing to explore common ground of incentives, particularly economic incentives between riparian states, then cooperation will be more likely

The Impact of Smart City Initiatives on Cities’ Local Economic Development

The problem explored in this mixed-method action research is that challenges to sustainable economic development and basic community services increase, as populations in cities and towns increase. A city is a human settlement with well-defined demarcation points. A city’s infrastructure consists of complex systems, such as sewage treatment plants, water treatment plants, police stations, fire departments, utility services, schools, libraries, business, houses, etc. A smart city, on the other hand, is an urban vision that fosters citizens’ engagement and technological integration of the city’s infrastructure. The purpose of this mixed-method action research was to identify the characteristics of a smart city and determine to what extent smart city initiatives impact economic development. Using a combative analysis methodology, the study examined five major smart cities. The research results revealed that cities apply smart solutions by focusing on 5 major areas: Economic Development, Public Safety, Energy & Environment, Infrastructure, and Transportation. The study concluded that Smart city initiatives contribute directly and indirectly to the economic growth of cities in the United States. The study indicated that smart cities are socially engaged, financially stable, business-oriented, data-driven, environmentally friendly, and energy-efficient cities. The study also concluded that smart city initiatives can alleviate cities’ challenges, thus, enhancing economic development