Node Transmission Probability Research Articles

Stability Region and Transmission Control of Multi-Cell Aloha Networks

As one of the most representative random-access schemes, slotted Aloha has been adopted in various wireless communication networks. A multi-cell Aloha network may easily become unstable as the inter-cell interference grows if the traffic input rates and transmission probabilities of nodes are not properly regulated. Yet how to stabilize a multi-cell Aloha network has remained largely unknown. To address the above open issue, an analytical framework is proposed in this paper for multi-cell Aloha networks to characterize the stability region of traffic input rates and operating region of transmission probabilities of nodes for achieving network stability. Specifically, the inter-cell interference level is captured by the overlapping ratio of each cell, and shown to be a key factor that determines the stability performance. For a two-cell Aloha network, the stability region of input rates and complete operating regions of transmission probabilities are obtained as functions of the overlapping ratios of cells. For the general <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -cell case, a transmission control algorithm is further proposed to stabilize the network only based on the local information exchange between neighboring cells, with effectiveness demonstrated through simulations.

Distributed Scheduling With Centralized Coordination for Scalable Wireless Mesh Networking

A coordinated carrier sense multiple access (C-CSMA) scheme is developed to schedule packet transmissions in multihop wireless networks. It integrates distributed scheduling and centralized coordination at different time scales. At a small time scale, a distributed scheduling algorithm, which is incorporated into CSMA, runs on each node to determine key parameters for CSMA. These parameters are optimized by ensuring multiple network attributes, i.e., average link date rate, node transmission probability, and the conditional probability of a link being selected for transmission, approaching their corresponding optimal values at a large time scale, e.g., a few seconds. Such optimal values are obtained from a centralized algorithm running on a portal node. The algorithm collects topology, link, and traffic information from the network at a large time scale and determines the attributes above to fulfill the optimal tradeoff between throughput and fairness. Since the distributed algorithm is shepherded by the centralized algorithm, C-CSMA has high scalability: first, it achieves long-term optimal performance with low information collection overhead; second, it schedules packet transmissions in a distributed way and responds quickly to changes in networks. It is proved that network attributes resulting from the distributed scheduling algorithm converge to optimal values provided by the centralized algorithm. Simulation experiments demonstrate that the convergence speed is fast. Moreover, extensive simulation results show that C-CSMA achieves much higher throughput, better fairness, and lower delay than existing scheduling schemes under different carrier sensing thresholds and traffic conditions.

Impact of Age Violation Probability on Neighbor Election-Based Distributed Slot Access in Wireless Ad Hoc Networks

In this paper, we propose an analytical model of neighbor election-based distributed slot access by considering the relationship between the age of information (AoI) and the slot access process of nodes in wireless ad hoc networks. A node first maintains the information updates from its neighbors by relaying and receiving messages and determines message transmission slots by holding elections with its relevant competing neighbors. We first find out and analyze the interaction relationship between the transmission probability of nodes, the competing probability of neighbor nodes, and the violation probability that AoI exceeds the timeliness threshold of the neighbor election. Next, we obtain the approximated expression of the competing probability and the age violation probability based on the comprehensive analysis of the neighbor election process. Numerical and simulation results show that our approximation is tighter than the one in the literature and also provides insights into enhancing the design of network-aware distributed multiple access schemes.

A Theoretical Framework for Random Access: Stability Regions and Transmission Control

As one of the two fundamental types of multiple access, random access has been widely adopted in various communication networks, and expected to play an increasingly central role owing to the rising popularity of Machine-to-Machine (M2M) communications. Despite decades of successful applications, the theory of random access has long been underdeveloped, with key fundamental issues unresolved. Among them, stability of random-access networks is the most long-standing one that has received continuous attention for almost half a century. The challenge lies in establishing an analytical framework where the coupled service processes of nodes’ queues can be characterized. In this paper, by extending our previously proposed analytical framework from the symmetric scenario to the general one, we tackle three open questions: 1) How to characterize the coupled service rates of nodes? 2) How to determine the stability region of input rates, only within which the network can be stabilized? 3) For given input rates within the stability region, how to tune the transmission probabilities of nodes to stabilize the network? We demonstrate that the key to characterizing the coupled service rates lies in properly establishing and solving the fixed-point equations of steady-state probabilities of successful transmission of Head-of-Line (HOL) packets of nodes. For the stability region of input rates, which closely depends on the definition of stability, two types of stability, i.e., queue-stability and throughput-stability, are considered, and both stability regions are shown to be determined by the sufficient and necessary condition of the existence of positive real roots of the fixed-point equations. To characterize the operating regions of transmission probabilities, constraints need to be further developed to ensure that the network operates at the specific steady-state point. The analysis shows that to stabilize the network, the transmission probabilities of nodes can be tuned only based on their long-term traffic input rates. Although the main results are illustrated based on Aloha with Constant Backoff, discussions on how to incorporate a general backoff function and other features of random access are also presented.

Spatiotemporal Medium Access Control for Wireless Powered IoT Networks

We study a wireless powered Internet-of-Things (IoT) network, which consists of spatially distributed energy harvesting (EH) nodes and a hybrid access point (HAP). The energy requirements of exponentially increasing IoT nodes could be fulfilled using the wireless EH. However, the spatiotemporal diversity may affect the performance of wireless EH networks due to the arbitrary information transmissions and varying amount of harvesting energy. In this article, we propose a new access control mechanism based on frame-slotted ALOHA considering the spatiotemporal diversity of nodes for distributed wireless powered IoT networks. In the proposed scheme, the nodes efficiently utilize the available time and power resources to enhance the achievable network throughput. The varying amount of harvested energy due to the harvesting duration and random distance from the power beacon (PB) affects the network performance. The contending nodes for a shared channel, randomly choose slots in a slotted frame, harvest energy, and transmit information using the harvested energy. We analyze the transmission probability of nodes affected by fading channel gains and formulate an optimization problem to find the optimal frame size for the contending number of nodes to maximize the achievable network throughput. The proposed scheme enhances the achievable throughput up to 12.5% and energy efficiency up to 20% over the conventional scheme.

Comments on “Interference-Based Capacity Analysis of Vehicular Ad Hoc Networks”

A new effective interference-based capacity model was proposed for vehicular ad hoc network safety message broadcast scenario in M. Ni et al. ( Commun. Lett. , vol. 19, no. 4, pp. 621–624, Apr. 2015). This letter is a reconsideration and extension of the model in Ni et al. . First, we point out that the analysis in Ni et al. is incomplete and show a new derivation of the node transmission probability and the SIR distribution accounting for the impact of asynchronous timing of hidden terminals and all possible interference occurrence cases. Second, the analysis is extended to the derivation of other important quality of service metrics, such as packet reception probability, packet reception ratio, and transmission capacity. The proposed analysis is cross validated by MATLAB, PYTHON, and NS2 simulations.

Fairness-Constrained Maximum Sum Rate of Multi-Rate CSMA Networks

This paper presents the sum rate analysis of a saturated $M$ -group multi-rate carrier sense multiple access network, where nodes in different groups have distinct packet transmission rates. An explicit expression of the network sum rate is derived, based on which the maximum sum rate is obtained by optimizing the transmission probabilities of nodes. It is found that to achieve the maximum sum rate, only the group of nodes with the largest transmission rate is allowed to access the channel, which leads to severe unfairness. To ensure certain fairness, two constraints, namely, throughput fairness (TF) and data-rate fairness (DF), are proposed, with which each node acquires a target proportion of the network throughput and the network sum rate, respectively. Explicit expressions of the network maximum sum rate with TF and DF are derived, which show that by including the fairness constraints, the network maximum sum rate becomes inferior to that without fairness constraints as long as there is difference in the transmission rates of nodes. The analysis is further applied to IEEE 802.11 networks, where the optimal initial backoff window sizes of nodes to achieve the network maximum sum rates with both fairness constraints are derived.

Lifetime Maximization Routing Based on Genetic Algorithm for Wireless Sensor Networks

To prolong network lifetime, lifetime maximization routing based on genetic algorithm (GALMR) for wireless sensor networks is proposed. Energy consumption model and node transmission probability are used to calculate the total energy consumption of nodes in a data gathering cycle. Then, lifetime maximization routing is formulated as maximization optimization problem. The select, crosss, and mutation operations in genetic algorithm are used to find the optimal network lifetime and node transmission probability. Simulation results show that GALMR algorithm are convergence and can prolong network lifetime. Under certain conditions, GALMR outperforms PEDAP-PA, LET, Sum-w and Ratio-w algorithms.