Analytical Model for Outdoor Millimeter Wave Channels using Geometry-Based Stochastic Approach

The severe bandwidth shortage in conventional microwave bands has spurred the exploration of the millimeter wave (MMW) spectrum for the next revolution in wireless communications. However, there is still lack of proper channel modeling for the MMW wireless propagation, especially in the case of outdoor environments. In this paper, we develop a geometry-based stochastic channel model to statistically characterize the effect of all the first-order reflection paths between the transmitter and receiver. These first-order reflections are generated by the single-bounce of signals reflected from the walls of randomly distributed buildings. Based on this geometric model, a closed-form expression for the power delay profile (PDP) contributed by all the first-order reflection paths is obtained and then used to evaluate their impact on the MMW outdoor propagation characteristics. Numerical results are provided to validate the accuracy of the proposed model under various channel parameter settings. The findings in this paper provide a promising step towards more complex and practical MMW propagation channel modeling.Comment: Accepted to appear in IEEE Transactions on Vehicular Technolog

Beam Based Stochastic Model of the Coverage Probability in 5G Millimeter Wave Systems

Communications using frequency bands in the millimeter-wave range can play a key role in future generations of mobile networks. By allowing large bandwidth allocations, high carrier frequencies will provide high data rates to support the ever-growing capacity demand. The prevailing challenge at high frequencies is the mitigation of large path loss and link blockage effects. Highly directional beams are expected to overcome this challenge. In this paper, we propose a stochastic model for characterizing beam coverage probability. The model takes into account both line-of-sight and first-order non-line-of-sight reflections. We model the scattering environment as a stochastic process and we derive an analytical expression of the coverage probability for any given beam. The results derived are validated numerically and compared with simulations to assess the accuracy of the model

Millimeter Wave Outdoor Cellular Networks: Stochastic Geometry Channel Modeling And Performance Analysis

Future cellular networks will use millimeter wave (MMW) spectrum to enable extremely high data rates. Although this spectrum offers numerous significant performance improvements in wireless networks, MMW frequencies also have unique propagation characteristics and hardware constraints, which require revisiting the prior channel modeling and system design. In this thesis, we develop a geometry-based stochastic channel model to characterize the effect of the first-order reflection paths. We consider random locations, sizes and orientations of buildings and derive a closed-form expression for the power delay profile contributed by the first-order reflection paths. We show that wireless networks can benefit from buildings in the communication area, as the external building surfaces render reflection paths whose signal powers are comparable to that of the direct path. Dense base station (BS) deployments are required to overcome the signal losses due to blockages, which unfortunately introduce additional interference at the receiver. We propose a BS coordination scheme to improve the user performance in the dense MMW cellular networks. We derive expressions for the signal-to-interference and noise ratio (SINR) coverage probability and area spectral efficiency (ASE) by incorporating the peculiarity characteristics of MMW communications. Our results show a significant improvement in performance in terms of SINR coverage probability and ASE. In this thesis, we also investigate the uplink performance of the MMW cellular networks. We model the locations of users as of a Poisson cluster process and develop an analytical expression to evaluate the SINR coverage probability. We study the performances of a typical BS for two association strategies, i.e., the closest-selection (CS) and the strongest-selection (SS). Our results show that regarding SINR coverage probability, the SS strategy outperforms the CS strategy in the environment with dense blockages

Novel improvements of empirical wireless channel models and proposals of machine-learning-based path loss prediction models for future communication networks.

Doctoral Degree. University of KwaZulu-Natal, Durban.Path loss is the primary factor that determines the overall coverage of networks. Therefore, designing reliable wireless communication systems requires accurate path loss prediction models. Future wireless mobile systems will rely mainly on the super-high frequency (SHF) and the millimeter-wave (mmWave) frequency bands due to the massively available bandwidths that will meet projected users’ demands, such as the needs of the fifth-generation (5G) wireless systems and other high-speed multimedia services. However, these bands are more sensitive and exhibit a different propagation behavior compared to the frequency bands below 6 GHz. Hence, improving the existing models and developing new models are vital for characterizing the wireless communication channel in both indoor and outdoor environments for future SHF and mmWave services. This dissertation proposes new path loss and LOS probability models and efficiently improves the well-known close-in (CI) free space reference distance model and the floating-intercept (FI) model. Real measured data was taken for both line-of-sight (LOS) and non-line-of-sight (NLOS) communication scenarios in a typical indoor corridor environment at three selected frequencies within the SHF band, namely 14 GHz, 18 GHz, and 22 GHz. The research finding of this work reveals that the proposed models have better performance in terms of their accuracy in fitting real measured data collected from measurement campaigns. In addition, this research studies the impact of the angle of arrival and the antenna heights on the current and improved CI and FI models. The results show that the proposed improved models provide better stability and sensitivity to the change of these parameters. Furthermore, the mean square error between the models and their improved versions was presented as another proof of the superiority of the proposed improvement. Moreover, this research shows that shadow fading’s standard deviation can have a notable reduction in both the LOS and NLOS scenarios (especially in the NLOS), which means higher precision in predicting the path loss compared to the existing standard models. After that, the dissertation presents investigations on high-ordering the dependency of the standard CI path loss model on the distance between the transmitting and the receiving antennas at the logarithmic scale. Two improved models are provided and discussed: second-order CI and third-order CI models. The main results reveal that the proposed two models outperform the standard CI model and notable reductions in the shadow fading’s standard deviation values as the model’s order increases, which means that more precision is provided. This part of the dissertation also provides a trade-off study between the model’s accuracy and simplicity