Performance Analysis and Optimization of CRNs Based on Fixed Feedback Probability Mechanism with Two Classes of Secondary Users

In this paper, we conduct a research based on the classified secondary users (SUs). SUs are divided into two categories: higher-priority SU1 and lower-priority SU2, and two types of users generate two types of packets, respectively. Due to the lowest spectrum usage rights of SU2 packets, the SU2 packets’ transmission is easily interrupted by other packets with higher rights. With the purpose of controlling the SU2 packets’ retransmission behavior, we introduce two system parameters, namely, feedback threshold T and feedback probability q. When the amount of SU2 packets in the buffer reaches the feedback threshold T, the interrupted SU2 packets either enter the buffer with probability q for retransmission or leave the channel by probability 1−q, where q is a fixed parameter. We construct a three-dimensional Markov model based on the presented retransmission control mechanism and derive some important performance indicators of SU2 packets based on the one-step transfer probability matrix and steady-state distribution. Then, we analyze the impact of some key parameters on the performance indicators through numerical experiments. Finally, we establish a cost function and use particle swarm optimization algorithm to optimize the feedback threshold and feedback probability.

A Cluster Based Localization Scheme with Partition Handling for Mobile Underwater Acoustic Sensor Networks

Many applications of underwater sensor networks (UWSNs), such as target tracking, reconnaissance and surveillance, and marine life monitoring require information about the geographic locations of the sensed data. This makes the localization of sensor nodes a crucial part of such underwater sensing missions. In the case of mobile UWSNs, the problem becomes challenging, not only due to a need for the periodic tracking of nodes, but also due to network partitioning as a result of the pseudo-random mobility of nodes. In this work, we propose an energy efficient solution for localizing nodes in partitioned networks. Energy consumption is minimized by clustering unlocalized partitioned nodes and allowing only clusterheads to carry out a major part of the localization procedure on behalf of the whole cluster. Moreover, we introduce a retransmission control scheme that reduces energy consumption by controlling unnecessary transmission. The major design goal of our work is to maximize localization coverage while keeping communication overheads at a minimum, thus achieving better energy efficiency. The major contributions of this paper include a clustering technique for localizing partitioned nodes and a retransmission control strategy that reduces unnecessary transmissions.

Opportunistic Routing Using Prioritized Forwarders with Retransmission Control

In ad hoc networks, broadcast-based forwarding protocols called opportunistic routing have been proposed. In general backoff-based opportunistic routing protocols, each receiver autonomously makes a forwarding decision using a random backoff time based on logical distance. However, each potential forwarder must wait for the expiration of the backoff timer before the packet forwarding. Moreover, they cannot gain forwarding path diversity in sparse environments. In this paper, we propose a novel forwarder selection method for opportunistic routing. In the proposed method, a terminal called, a prioritized forwarder, and which is selected from among neighbours and can forward packets without using the backoff time. In addition, we integrate a hop-by-hop retransmission control in the proposed method, which improves the packet transmission success rate in sparse environments. We evaluate the proposed method in comparison with the conventional protocols in computer simulations.