No abstract

The use of extremely high frequency (EHF) or millimeter-wave (mmWave) band has attracted significant attention for the next generation wireless access networks. As demonstrated by recent measurements, mmWave frequencies render themselves quite sensitive to "blocking" caused by obstacles like foliage, humans, vehicles, etc. However, there is a dearth of analytical models for characterizing such blocking and the consequent effect on the signal reliability. In this paper, we propose a novel, general, and tractable model for characterizing the blocking caused by humans (assuming them to be randomly located in the environment) to mmWave propagation as a function of system parameters like transmitter-receiver locations and dimensions, as well as density and dimensions of humans. Moreover, the proposed model is validated using a ray-launcher tool. Utilizing the proposed model, the blockage probability is shown to increase with human density and separation between the transmitter-receiver pair. Furthermore, the developed analysis is shown to demonstrate the existence of a transmitter antenna height that maximizes the received signal strength, which in turn is a function of the transmitter-receiver distance and their dimensions.

This paper analyzes the capacity of a wireless relay network composed of a large number of nodes that operate in an amplify-and-forward mode and that divide into a fixed number of levels. The capacity computation relies on the study of products of large random matrices, whose limiting eigenvalue distribution is computed via a set of recursive equations.

No abstract

Responding to the unprecedented challenges imposed by the 5G communications ecosystem, emerging heterogeneous network architectures allow for improved integration between multiple radio access technologies. When combined with advanced cloud infrastructures, they bring to life a novel paradigm of heterogeneous cloud radio access network (H-CRAN). The novel H-CRAN architecture opens door to improved network-wide management, including coordinated cross-cell radio resource allocation. In this paper, emphasizing the lack of theoretical performance analysis, we specifically address the problem of cooperative radio resource management in H-CRAN by providing a comprehensive mathematical methodology for its realtime performance optimization. Our approach enables flexible balance between throughput and fairness metrics, as may be desired by the network operator, and demonstrates attractive benefits when compared against the state-of-the-art multiradio resource allocation strategies. The resulting algorithms are suitable for efficient online implementation, which principal feasibility is confirmed by our proof-of-concept prototype.INDEX TERMS Heterogeneous network, cloud infrastructure, heterogeneous cloud radio access network, cooperative radio resource management, mathematical methodology, prototyping.