Search

In this paper, a receiving scheme for intermediate frequency (IF) signals enhanced by stochastic resonance (SR) is proposed. The proposed scheme mitigates the reception failure of these signals, which can occur in radio and communication systems under extremely low signal-to-noise ratio (SNR). The SR mechanism for enhancing sinusoidal signals is analyzed. An analytic solution with time parameters of the Fokker-Planck Equation (FPE) is obtained by introducing the decision time from the non-autonomous FPE into an autonomous one. A quadratic polynomial receiving structure for sinusoidal signals enhanced by SR is proposed by comparing the characteristics of energy detection and matched filter detection. And the polynomial coefficients of the quadratic system are obtained by maximizing the deflection. Based on the idea of “the average of N samples”and the assumption of Gaussian distribution approximation under the law of large numbers, a quadratic polynomial receiving scheme for sinusoidal signals enhanced by SR is proposed. The conclusions are as below: 1) when the noise intensity is constant, the smaller the correlation time, the bigger the local SNR around the IF frequency due to the better performance of the low-pass filter; 2) The error bit ratio of the quadratic polynomial receiver is less than 1 × 10-2 when N = 20 and the SNR is above -14 dB, which can be applied to the military emergency communication under extremely low SNR. Experiment verifies the theory.

Data admission control is an important issue in wireless sensor networks (WSNs) because of the limited transmission coverage area and the limited battery capability of each sensor node. To achieve the optimum benefit of the sensor network, a reward when a data package arriving at a sensor is accepted (not rejected) for transmission is considered, but a holding cost per unit time for the accepted data package waiting in the sensor for transmission is also incurred. For the sensor with sleep and active phases, a dynamic data admission control model is developed in this paper. By constructing a suitable Markov decision process (MDP), we verify that the optimal admission control policy of when to admit or reject an arriving data packet is a control limit policy, in order to achieve the maximum expected a discounted reward in the sleep and active phase, respectively. Furthermore, we provide a formula for how to calculate the upper bound of these threshold values. For the identified model with the optimal expected discount reward, the energy consumption of the sensors in active and sleep phases, as well as the energy consumption switching from active to sleep per unit time and vice versa is investigated. Extensive simulation is implemented. The results show that the problem is effectively solved by an optimal scheme with high energy efficiency. The results of this paper can be applied to designing optimal sensor nodes in wireless sensor networks.

Wireless sensor networks (WSNs) are being applied widely for data collection, especially to carry out the mission-critical tasks. Therefore, one of the most challenging tasks of mission-critical sensors and sensor networks is the development of energy efficient (EE) routing protocols. Comparing with flat routing protocols, more EE can be achieved in hierarchical routing protocols. In this paper, we propose an enhanced balanced energy efficient network-integrated super-heterogeneous (E-BEENISH) routing protocol, by analyzing communication energy consumption of the clusters and a large range of energy levels in heterogeneous WSNs. E-BEENISH is based on weighted election probabilities of each node to become a cluster head according to the remaining energy and the distance from the sink to the node. Moreover, we also study the impact of the heterogeneity of nodes in terms of energy. Studying the sensitivity of our stable election protocol, we conclude heterogeneity parameters capturing energy imbalance in the network and find that the E-BEENISH yields the longer stability region for the suitable weight of energy and distance. Our results show by simulation that the E-BEENISH can improve system lifetime by an order of magnitude compared to obtained using current clustering protocols, which is crucial for many applications.