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

Coverage Analysis and Resource Allocation in Heterogeneous Networks

The focus of this thesis is the analysis and design of multi-tier heterogenous networks (HetNets) with large density of access points (APs) located without a deterministic structure. We use stochastic geometry, specifically Poisson point processes (PPPs), to capture the randomness in AP locations. To differentiate their structural characteristics, APs are categorized into different tiers, each modeled by a PPP. The problem of cell association and resource allocation in a HetNet is considered from two different points of view: when the user is i) mobile and ii) stationary. To incorporate mobility in coverage analysis for mobile users, we derive the probability of handoff in an irregular multi-tier HetNet. To account for the service degradation due to handoffs, we propose a linear cost function, and use this to associate high speed users to upper tiers (e.g., macrocells) with a lower AP density. For stationary users, we first derive the statistical distribution of the load, and the minimum bandwidth required to meet an outage constraint in a multi-tier HetNet. This result is most useful for system design by relating the required spectrum to choices of network parameters. We then consider the dual problem with the objective of maximizing the overall rate coverage with orthogonal spectrum allocation across tiers given a total available bandwidth. We tackle this problem in two different phases: 1) load distribution and spectrum partitioning across tiers; 2) resource allocation across the APs and users within one tier. For analytical tractability in the former, we approximate the load of each AP by its mean, and derive the optimum tier association and fraction of spectrum to be allocated to each tier. In the latter, to account for different loads at each AP, we develop a hierarchical algorithm to allocate the available spectrum across the APs according to their load and to users according to their data rate demand. The latter benefits from adaptive power allocation and dynamic spectrum allocation across APs.Ph.D

Suboptimal Rate Adaptive Resource Allocation for Downlink OFDMA Systems

This paper aims to study the performance of low complexity adaptive resource allocation in the downlink of OFDMA systems with fixed or variable rate requirements (with fairness consideration). Two suboptimal resource allocation algorithms are proposed using the simplifying assumption of transmit power over the entire bandwidth. The objective of the first algorithm is to maximize the total throughput while maintaining rate proportionality among the users. The proposed suboptimal algorithm prioritizes the user with the highest sensitivity to the subcarrier allocation, and the variance over the subchannel gains is used to define the sensitivity of each user. The second algorithm concerns rate adaptive resource allocation in multiuser systems with fixed rate constraints. We propose a suboptimal joint subchannel and power allocation algorithm which prioritizes the users with the highest required data rates. The main feature of this algorithm is its low complexity while achieving the rate requirements