Abstract-While designing wireless networks, it is crucial to obtain the maximum coverage by using the minimum number of transmitting antennas. This paper proposes a new algorithm for determining the minimum number of transmitting antennas as well as their appropriate locations to provide the optimized wireless coverage in the indoor environment. The proposed algorithm uses a ray-tracing method to predict the signal distribution among the sampling points in the indoor area due to one or more transmitters and the genetic algorithm (GA) incorporated with the Breath First Search (BFS) terminology to determine the minimum number of transmitters and their corresponding locations to achieve the optimum wireless coverage. The proposed method outperforms the existing method in terms of both space and time complexities. The results obtained from this study also show that the computation time using the proposed algorithm is much less than that of the existing algorithm.

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Abstract:This study proposes an efficient and accelerated Intelligent Ray-Tracing (IRT) algorithm based on Binary Angle Division (BAD) technique for radio signal prediction in indoor area. The intelligent features of the proposed IRT can skip the processing of the unnecessary signals based on the invalid region and reduce the number of candidate objects (obstacles) as well as their edges while performing ray-object intersection tests, which can make the algorithm faster as well as more accurate. The obtained results are compared with the existing indoor ray propagation methods to prove the superiority of the proposed IRT technique in terms of both computational efficiency and accuracy of signal prediction.

Blind spots (or bad sampling points) in indoor areas are the positions where no signal exists (or the signal is too weak) and the existence of a receiver within the blind spot decelerates the performance of the communication system. Therefore, it is one of the fundamental requirements to eliminate the blind spots from the indoor area and obtain the maximum coverage while designing the wireless networks. In this regard, this paper combines ray-tracing (RT), genetic algorithm (GA), depth first search (DFS), and branch-and-bound method as a new technique that guarantees the removal of blind spots and subsequently determines the optimal wireless coverage using minimum number of transmitters. The proposed system outperforms the existing techniques in terms of algorithmic complexity and demonstrates that the computation time can be reduced as high as 99% and 75%, respectively, as compared to existing algorithms. Moreover, in terms of experimental analysis, the coverage prediction successfully reaches 99% and, thus, the proposed coverage model effectively guarantees the removal of blind spots.