I. INTRODUCTIONRecently, the use of mobile wireless system became the most popular technology as a result of lots of services available in mobile cellular phone [1]. Some of these include voice call, video call, conference call, data based services and other multimedia applications. Despite the increase in number of base stations to augment high rate of subscribers, the quality of service delivery by the network providers still remains in poor state [2]. It is observed that the poor quality of services experienced could be due to several challenges experienced in the network channel [3]. On that note, it becomes paramount to identity these problems and propose solutions through research analysis.The communication channel experience Rayleigh fading as a result of obstruction to Line of Sight (LOS), resulted in reflection, absorption and scattering of transmitted signal [4], [5]. The knowledge of the propagation characteristic of a mobile radio channel is essential for designing any wireless communication system in a given region [6]. One of the most important problems of propagation environment is path loss [5]. Propagation path loss has great influence on the quality of service of a mobile communication system, the transmitted signal power get reduced with increased distance from base station to mobile station. Therefore, accurate estimation of propagation path loss is important factor for the good design and planning of mobile system [7]. The quality and coverage reliability of a wireless network design depends on the accuracy of the path loss model [4].There are many propagation path loss models proposed in previous works to predict coverage. These model are not sufficient for accurate analysis of the path loss on other terrain, the suitability of such models differs with different environment [8]. The objective of optimization is to make sure the network operates close to the original design in terms of handoff points, coverage, received signal strength and Quality of Service (QoS) [2], [3]. In order to overcome the problem of path loss, the parameters of certain models must be adjusted with reference to the targeted locations. This will enable the system achieve minimum error between Transmitted Signal Strength (TSS) Optimization is the process of obtaining the best solution to a system function efficiently as a result of the modification of existing models. The optimizations of these existing models have been carried out by many researchers in other regions, but some of them are based on Least Square (LS) method. Other optimization methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Bee Colony Algorithm (BCA), have not been commonly used relative to the reviewed literature. The particle swarm optimization uses the ideas of bird flocking and its survival of fitness by randomly chosen positions and velocities [2]. In this paper, we investigated the performance of some propagation models while appropriate modified model was developed for the terrain. PSO technique was further deploy...

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This paper describes the development of optimized model for urban outdoor coverage in Long Term Evolution (LTE) network at 2300 MHz frequency band in Port Harcourt urban region, Nigeria. Signal attenuation and fluctuation remain amongst the major channel impairments for mobile radio communication systems. This arises as a result of model incompatibility with terrain and Line of Sight (LOS) obstruction of the channel signals. Some path loss models such as Okumura-Hata, COST 231, Ericsson 999, Egli and ECC-33 models were evaluated for suitability and compared with the modified model for the environments. The models were based on data collected from LTE base stations at three geographical locations in Port Harcourt namely- Rumuokoro, Eneka and Ikwerre roads respectively. The simulation was implemented using MATLAB R2014a software. The modified model was further optimized with some selected parameters such as Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) using Particle Swarm Optimization (PSO) technique. The results obtained gave rise to 3.030dB for RMSE and 0.00162dB for MAE respectively. The results obtained from the PSO optimized model demonstrated a better performance which is suitable for cell coverage planning and smooth handoff processes.