Wuyang Zhou

The Ginibre Point Process as a Model for Wireless Networks With Repulsion

The spatial structure of transmitters in wireless networks plays a key role in evaluating mutual interference and, hence, performance. Although the Poisson point process (PPP) has been widely used to model the spatial configuration of wireless networks, it is not suitable for networks with repulsion. The Ginibre point process (GPP) is one of the main examples of determinantal point processes that can be used to model random phenomena where repulsion is observed. Considering the accuracy, tractability, and practicability tradeoffs, we introduce and promote the β-GPP, which is an intermediate class between the PPP and the GPP, as a model for wireless networks when the nodes exhibit repulsion. To show that the model leads to analytically tractable results in several cases of interest, we derive the mean and variance of the interference using two different approaches: the Palm measure approach and the reduced second-moment approach, and then provide approximations of the interference distribution by three known probability density functions. In addition, to show that the model is relevant for cellular systems, we derive the coverage probability of a typical user and find that the fitted β-GPP can closely model the deployment of actual base stations in terms of coverage probability and other statistics.

Heterogeneous Cellular Network Models With Dependence

Due to its tractability, a multitier model of mutually independent Poisson point processes (PPPs) for heterogeneous cellular networks (HCNs) has recently been attracting much attention. However, in reality, the locations of the BSs, within each tier and across tiers, are not fully independent. Accordingly, in this paper, we propose two HCN models with inter-tier dependence (Case 1) and intra-tier dependence (Case 2), respectively. In Case 1, the macro-base station (MBS) and the pico-base station (PBS) deployments follow a Poisson point process (PPP) and a Poisson hole process (PHP), respectively. Under this setup and conditioning on a fixed serving distance (distance between a user and its nearest serving BS), we derive bounds on the outage probabilities of both macro and pico users. We also use a fitted Poisson cluster process to approximate the PHP, which is shown to provide a good approximation of the interference and outage statistics. In Case 2, the MBSs and the PBSs follow a PPP and an independent Matern cluster process, respectively. Explicit expressions of the interference and the outage probability are derived first for fixed serving distance and second with random distance, and we derive the outage performance, the per-user capacity, and the area spectral efficiency (ASE) for both cases. It turns out that the proposed Case 2 model is a more appropriate and accurate model for a HCN with hotspot regions than the multitier independent PPP model since the latter underestimates some key performance metrics, such as the per-user capacity and the ASE, by a factor of 1.5 to 2. Overall, the two models proposed provide good tradeoffs between the accuracy, tractability, and practicability.

Large-Girth Nonbinary QC-LDPC Codes of Various Lengths

In this paper, we construct nonbinary quasi-cyclic low-density parity-check (QC-LDPC) codes whose parity check matrices consist of an array of square sub-matrices which are either zero matrices or circulant permutation matrices. We propose a novel method to design the shift offset values of the circulant permutation sub-matrices, so that the code length can vary while maintaining a large girth. Extensive Monte Carlo simulations demonstrate that the obtained codes of a wide range of rates (from 1/2 to 8/9) with length from 1000 to 10000 bits have very good performance over both AWGN and Rayleigh fading channels. Furthermore, the proposed method is extended to design multiple nonbinary QC-LDPC codes simultaneously where each individual code can achieve large girth with variable lengths. The proposed codes are appealing to practical adaptive systems where the block length and code rate need to be adaptively adjusted depending on traffic characteristics and channel conditions.

Spray and wait routing based on position prediction in opportunistic networks

For opportunistic networks, we propose a new routing protocol named PPSW, which exploits the benefit of the polynomial interpolation prediction of mobile nodes positions. This scheme can deliver the message faster with appropriate opportunities. Specifically, in wait phase, relay can forward message to another one moving closer to destination, instead of waiting to encounter the destination itself. Simulation results show that PPSW achieves about 20% improvement compared with Spray and Wait protocol in delivery rate and delay performance.

Proportional-fair downlink resource allocation in OFDMA-based relay networks

In this paper, we consider resource allocation with proportional fairness in the downlink orthogonal frequency division multiple access relay networks, in which relay nodes operate in decode-and-forward mode. A joint optimization problem is formulated for relay selection, subcarrier assignment and power allocation. Since the formulated primal problem is nondeterministic polynomial time-complete, we make continuous relaxation and solve the dual problem by Lagrangian dual decomposition method. A near-optimal solution is obtained using Karush-Kuhn-Tucker conditions. Simulation results show that the proposed algorithm provides superior system throughput and much better fairness among users comparing with a heuristic algorithm.

Throughput-optimal user association in energy harvesting relay-assisted cellular networks

We study the user association problem targeting on the throughput optimization for energy harvesting (EH) relay-assisted cellular networks where the base stations (BSs) are powered by grid power and the relay stations (RSs) are powered by renewable energy. Since the harvested energy of RS is stochastic and not always large enough, our challenge is how to match the user association with the energy arrival rate of RS so as to maximize the throughput of the network. For this purpose, we propose a dynamic bias based user association policy which means the user is associated with the BS/RS that provides the strongest-biased-average-received-power, and maximize the throughput by optimizing the bias with different energy constraints. Using tools from stochastic geometry and continuous time Markov chain (CTMC), we first formulate the problem as a throughput-optimal and energy-constrained problem with respect to the bias. Then, by solving the optimization problem, we derive the closed expression of the optimal bias maximizing the throughput. Numerical results show that our dynamic bias based user association policy can always outperform that without bias, especially when the RSs are energy-limited.

A heterogeneous cellular network model with inter-tier dependence

In heterogeneous cellular networks (HCNs), the macrocell network is usually assumed to be overlaid by multiple independent tiers of small cells. However, in reality, the locations of the base stations (BSs) belonging to different tiers are not fully independent. Accordingly, in this paper, we propose a two-tier HCN model with inter-tier dependence, where the macro-BS (MBS) and the pico-BS (PBS) deployments follow a Poisson point process (PPP) and a Poisson hole process (PHP), respectively. Under this setup, we derive bounds on the outage probabilities of both macro users and pico users, and then use a fitted Poisson cluster process to approximate the PHP, which is shown to provide a good approximation of the interference and outage. The results show that the model with inter-tier dependence appears closer to the real deployment than the two extremes with full regularity (the triangular lattice) and complete randomness (the PPP). An important conclusion is that significant gains can be obtained if PBSs are deployed smartly (away from MBSs).

Energy-Friendly Network Selection in Heterogeneous Wireless Networks

Mobile terminals in heterogeneous wireless networks continuously undergo network selection within the initial access process and handover process. In order for a mobile terminal to be connected to a network in the best possible way in terms of QoS performance and energy consumption, this paper presents a novel method that takes into account user preferences, network conditions, QoS and energy consumption requirements in order to select the optimal network which achieves the best balance between performance and energy consumption. The proposed network selection method incorporates the use of fuzzy logic because of the available sources of information from different radio access technology (RAT) are qualitatively interpreted and heterogeneous in nature, and adopts different energy consumption metrics for real-time and non-real-time applications. Finally, simulations confirm our schemes suitability and effectiveness.

Resource Allocation for OFDMA System Based on Genetic Algorithm

In traditional resource allocation for OFDMA, the packet scheduling and subcarriers allocation are optimized independently. In order to improve the whole system performance, a resource allocation algorithm based on genetic algorithm was proposed, in which the packet scheduling and subcarriers allocation are optimized jointly. To maximize system throughput and guarantee fairness among users, the proposed algorithm uses stochastic approximation methods to control the parameter in scheduling; meanwhile uses a genetic algorithm to solve the subcarriers allocation problem. It is demonstrated in the simulation result that the proposed algorithm can improve the system performance in terms of throughput, packet loss rate, packet delay and fairness.

Outage Analysis of Distributed Scheme on Opportunistic Relaying with Limited CSI

In this letter, we propose a distributed scheme on opportunistic amplify-and-forward (AF) relaying to minimize the system outage probability with low feedback overhead. Only the subset of relays report the calculated outage probability information to the source based on the outage probability threshold with the limited channel state information (CSI). We present the approximate expressions for the system outage probability under two scenarios, the statistical CSI and the statistical quantized CSI of the relay-destination links, respectively. Numerical results indicate that the derived analytic results are reasonable and the outage performance is better for the statistical quantized CSI case with acceptable feedback cost.