In this thesis, a novel framework for optimizing the resource allocation in a millimeter-wave-non-orthogonal multiple access (mmWave-NOMA) communication for crowded venues is proposed. Unfortunately, mmWave communications suffer from severe blockage caused by obstacles such as the human body, especially in a dense region. In this regard, a detailed method for modeling blockage events in the in-venue scenarios is introduced. Due to the line-of-sight link blockage in the highly populated regions, multiple mmWave access points are considered in different locations. The resource allocation problem in this network is expressed in the form of an optimization problem to maximize the network sum rate; however, this problem is proven to be NP-hard. In this regard, a three-stage low-complex solution is proposed to solve the problem. In the first stage, a user scheduling algorithm, i.e., modified worst connection swapping (MWCS), is proposed. Then, in the second stage, the antenna allocation problem is solved using a meta-heuristic algorithm called simulated annealing. In the third stage, to maximize the network sum rate and guarantee the quality of service constraints, a non-convex power allocation optimization problem is solved by adopting the difference of convex programming approach. The simulation results show that, under the blockage effect, the proposed mmWave-NOMA scheme performs on average23%etter than the conventional mmWave-orthogonal multiple access (OMA) scheme. In addition, the proposed solution’s performance is close to the optimal value while reducing complexity by about96%. Moreover, the number of required mmWave access points needs to be chosen based on a tradeoff between the blockage probability and co-channel interference. Millimeter-wave communications, non-orthogonal multiple access, resource allocation, human blockage, massive multiple-input multiple-output
