Analysis and Optimization of Cellular Network with Burst Traffic

In this paper, we analyze the performance of cellular networks and study the optimal base station (BS) density to reduce the network power consumption. In contrast to previous works with similar purpose, we consider Poisson traffic for users' traffic model. In such situation, each BS can be viewed as M/G/1 queuing model. Based on theory of stochastic geometry, we analyze users' signal-to-interference-plus-noise-ratio (SINR) and obtain the average transmission time of each packet. While most of the previous works on SINR analysis in academia considered full buffer traffic, our analysis provides a basic framework to estimate the performance of cellular networks with burst traffic. We find that the users' SINR depends on the average transmission probability of BSs, which is defined by a nonlinear equation. As it is difficult to obtain the closed-form solution, we solve this nonlinear equation by bisection method. Besides, we formulate the optimization problem to minimize the area power consumption. An iteration algorithm is proposed to derive the local optimal BS density, and the numerical result shows that the proposed algorithm can converge to the global optimal BS density. At the end, the impact of BS density on users' SINR and average packet delay will be discussed.Comment: This paper has been withdrawn by the author due to missuse of queue model in Section Fou

5G Ultra-dense networks with non-uniform Distributed Users

User distribution in ultra-dense networks (UDNs) plays a crucial role in affecting the performance of UDNs due to the essential coupling between the traffic and the service provided by the networks. Existing studies are mostly based on the assumption that users are uniformly distributed in space. The non-uniform user distribution has not been widely considered despite that it is much closer to the real scenario. In this paper, Radiation and Absorbing model (R&A model) is first adopted to analyze the impact of the non-uniformly distributed users on the performance of 5G UDNs. Based on the R&A model and queueing network theory, the stationary user density in each hot area is investigated. Furthermore, the coverage probability, network throughput and energy efficiency are derived based on the proposed theoretical model. Compared with the uniformly distributed assumption, it is shown that non-uniform user distribution has a significant impact on the performance of UDNs.Comment: 14 pages, 10 figure

Cognitive and Energy Harvesting-Based D2D Communication in Cellular Networks: Stochastic Geometry Modeling and Analysis

While cognitive radio enables spectrum-efficient wireless communication, radio frequency (RF) energy harvesting from ambient interference is an enabler for energy-efficient wireless communication. In this paper, we model and analyze cognitive and energy harvesting-based D2D communication in cellular networks. The cognitive D2D transmitters harvest energy from ambient interference and use one of the channels allocated to cellular users (in uplink or downlink), which is referred to as the D2D channel, to communicate with the corresponding receivers. We investigate two spectrum access policies for cellular communication in the uplink or downlink, namely, random spectrum access (RSA) policy and prioritized spectrum access (PSA) policy. In RSA, any of the available channels including the channel used by the D2D transmitters can be selected randomly for cellular communication, while in PSA the D2D channel is used only when all of the other channels are occupied. A D2D transmitter can communicate successfully with its receiver only when it harvests enough energy to perform channel inversion toward the receiver, the D2D channel is free, and the $\mathsf{SINR}$ at the receiver is above the required threshold; otherwise, an outage occurs for the D2D communication. We use tools from stochastic geometry to evaluate the performance of the proposed communication system model with general path-loss exponent in terms of outage probability for D2D and cellular users. We show that energy harvesting can be a reliable alternative to power cognitive D2D transmitters while achieving acceptable performance. Under the same $\mathsf{SINR}$ outage requirements as for the non-cognitive case, cognitive channel access improves the outage probability for D2D users for both the spectrum access policies.Comment: IEEE Transactions on Communications, to appea

Partially-Distributed Resource Allocation in Small-Cell Networks

We propose a four-stage hierarchical resource allocation scheme for the downlink of a large-scale small-cell network in the context of orthogonal frequency-division multiple access (OFDMA). Since interference limits the capabilities of such networks, resource allocation and interference management are crucial. However, obtaining the globally optimum resource allocation is exponentially complex and mathematically intractable. Here, we develop a partially decentralized algorithm to obtain an effective solution. The three major advantages of our work are: 1) as opposed to a fixed resource allocation, we consider load demand at each access point (AP) when allocating spectrum; 2) to prevent overloaded APs, our scheme is dynamic in the sense that as the users move from one AP to the other, so do the allocated resources, if necessary, and such considerations generally result in huge computational complexity, which brings us to the third advantage: 3) we tackle complexity by introducing a hierarchical scheme comprising four phases: user association, load estimation, interference management via graph coloring, and scheduling. We provide mathematical analysis for the first three steps modeling the user and AP locations as Poisson point processes. Finally, we provide results of numerical simulations to illustrate the efficacy of our scheme.Comment: Accepted on May 15, 2014 for publication in the IEEE Transactions on Wireless Communication