Interference and Outage in Clustered Wireless Ad Hoc Networks (0706.2434v1)

Abstract: In the analysis of large random wireless networks, the underlying node distribution is almost ubiquitously assumed to be the homogeneous Poisson point process. In this paper, the node locations are assumed to form a Poisson clustered process on the plane. We derive the distributional properties of the interference and provide upper and lower bounds for its CCDF. We consider the probability of successful transmission in an interference limited channel when fading is modeled as Rayleigh. We provide a numerically integrable expression for the outage probability and closed-form upper and lower bounds.We show that when the transmitter-receiver distance is large, the success probability is greater than that of a Poisson arrangement. These results characterize the performance of the system under geographical or MAC-induced clustering. We obtain the maximum intensity of transmitting nodes for a given outage constraint, i.e., the transmission capacity (of this spatial arrangement) and show that it is equal to that of a Poisson arrangement of nodes. For the analysis, techniques from stochastic geometry are used, in particular the probability generating functional of Poisson cluster processes, the Palm characterization of Poisson cluster processes and the Campbell-Mecke theorem.

• The paper introduces Poisson cluster process modeling to capture realistic node clustering in wireless ad hoc networks, improving interference analysis over traditional models.
• It derives novel bounds for interference and outage probabilities under Rayleigh fading, revealing a heavy-tailed interference distribution.
• The study quantifies clustering gain and transmission capacity, offering actionable insights for designing more robust wireless networks.

Analysis of Interference and Outage in Clustered Wireless Ad Hoc Networks

This paper by Ganti and Haenggi presents an extensive paper of the dynamics of interference and outage probabilities in clustered wireless ad hoc networks with a focus on Poisson cluster processes as the underlying distribution model for node locations. The research elucidates how this choice deviates from the more traditional homogeneous Poisson point process (PPP) model assumed in most previous studies, highlighting the significance and applicability of such models in real-world communication scenarios where node distribution oftentimes exhibits clustering due to geographical or protocol-induced factors.

Key Contributions

1. Poisson Cluster Process Modeling: The authors model node distribution using the Poisson cluster process, which better reflects scenarios with geographical clustering or MAC protocol-induced clustering. They detail the characterization of such processes via stochastic geometry tools, specifically leveraging the probability generating functional and Palm distributions.
2. Interference Characterization: The paper derives bounds for the complementary cumulative distribution function (CCDF) of interference using novel theoretical tools. It highlights the heavy-tailed nature of interference distributions under certain conditions and path-loss models, showing how it contrasts with interference models based on standard PPP setups.
3. Outage Probability and Success Metrics: The work provides numerical integration expressions and closed-form bounds for outage probabilities under Rayleigh fading. Notably, the paper introduces the concept of clustering gain, a metric comparing success probabilities between clustered processes and homogeneously distributed node models like PPPs. The authors find through this metric that clustering can improve success probabilities, especially at larger transmitter-receiver distances.
4. Transmission Capacity Analysis: A notable contribution of the paper is the analysis of transmission capacity under clustered scenarios. The results suggest that the transmission capacity of clustered networks can match that of Poisson networks under certain conditions. They also elaborate on bounds and capacity scaling laws, which are particularly relevant for networks employing spread-spectrum techniques like DS-CDMA and FH-CDMA.

Implications and Future Directions

The theoretical findings of this paper have profound implications for designing and evaluating the performance of ad hoc and mobile wireless networks. By recognizing the role of clustered node distributions, this research enables more accurate modeling of network operations and interference management strategies. The insights regarding the clustering gain are particularly valuable for network design, aiding practitioners in deciding when to leverage clustering to optimize link success probabilities and overall network capacity.

Future research directions could explore further the impact of different clustering models and distributions in diverse environments, including urban landscapes with dynamic node mobility. Additionally, applying these theoretical insights to practical and simulation-based studies can help validate and refine the models further.

By substantiating the potential advantages of clustered arrangements under certain conditions, this paper opens a pathway to improved real-world ad hoc networking strategies, potentially influencing future design standards and protocol developments in wireless communication systems.