Search

In this paper, the biophysically plausible neuron model i.e. the Hodgkin-Huxley neuron model has been implemented in the field programmable gate arrays (FPGAs) by employing Altera DSP Builder. The action potential generated by Hodgkin-Huxley neurons implemented in FPGA has been compared with the numerical prediction, leading to a good agreement between them. It is believed that this approach could greatly speed up simulations of both highly complex single neuron model and network of neurons.

The 1-DOA estimation algorithm is used to estimate azimuth of signals. DML (Determined Maximum Likelihood) is a kind of algorithm for parameter estimation of determined narrowband signals, which theoretically has advantages of high precise as well as high suppression to strong noise and coherent signals. However, there are problems of high computation complexity and local convergence. Therefore, the algorithm named FPSO-DML (Fission Particle Swarm Optimization-DML) is put forward in this paper, which could get accurately global optimum root of DML function at a cost of low computation. Then, the wideband signal is decomposed into narrowband signal at different frequency by FFB, which is used to estimate 1-DOA by FPSO-DML algorithm. Simulations prove that the RMSE curve of proposed algorithm approach CRB of DML algorithm, and having strong ability of tolerating coherent wideband signals.

The number of cooperative sensors to use is a compromise between sensing performance and resources usage efficiency. The definition of the optimal cooperative sensor set is given out firstly and then a greedy selection algorithm for the optimal cooperative sensor set is proposed which can use fewest cooperative sensors to maximize the resources usage efficiency, while still having enough for the sensing performance constraints. Analysis and numerical results illustrate the effectiveness and reliability of the proposed selection algorithm.

The problem of sensor set selection for cooperative spectrum sensing in cognitive radio networks is considered in this paper. The cooperative gain of the newly added cooperative sensor decreases and converges to zero as the number of cooperative sensors increases, but the consumption of system resources grows approximately linearly with the number of cooperative sensors, therefore, the number of cooperative sensors to use is a compromise between sensing performance and resources usage efficiency. A greedy based cooperative sensor set selecting algorithm is proposed which can use a threshold acquired by compromising between sensing performance and resources usage efficiency to select a cooperative sensor set. Numerical results illustrate the effectiveness and reliability of the proposed sensor set selecting algorithm.

Although the method of cooperative spectrum sensing can greatly improve the sensing performance, the consumption of system resources will increase as the number of cooperative sensors increases, therefore, the number of cooperative sensors to use is a compromise between sensing performance and consumption of system resources. Firstly, based on the expression for the probability of detection, a sensor set selecting method is proposed; then, a confidence based trustless sensor detecting method is presented to delete the trustless sensors from CRN which would add negative effect on the sensor set selecting method; lastly, based on the two methods above, a confidence based sensor set selecting algorithm is proposed, which not only effectively delete the trustless sensors from CRN but also use fewest cooperative sensors to minimize the consumption of system resources, while still having enough for the sensing performance requirements. Analysis and numerical results illustrate the effectiveness and reliability of the proposed algorithm.

The number of sensors to use for cooperative sensing is a compromise between sensing performance and consumption of system resources. Firstly, the definition of optimal sensor set (OptSS) is given out. Then an optimal selecting method of OptSS is acquired. Lastly, a sub optimal adaptive selecting algorithm of OptSS based on greedy with a lower complexity is proposed, which not only obtains the near-optimal solution rapidly, but also adapts to the variety of dynamic network topologies. Analysis and simulation results demonstrate the effectiveness and reliability of the proposed greedy adaptive sensor set selecting al-gorithm.

For the sake of enhancing stability of least squares constrant modulus equalization algorithm( LSCMA), combining recursive least-squares (RLS) and using robust estimation (RE) from Application Maths, the paper puts forward an new sort of semi-blind constant modulus equalization algorithm that names SB-MRLS-LSCMA.The simulation indicates that the algorithm improves the performance of convergence and stability of the equalizer comparing to traditional LSCMA and several other semi-blind algorithm. And the algorithm can be good for restraining multi-pathway and Rayleigh fading.

Traditional chip LMMSE algorithm has unbearable computational complexity for MIMO HSDPA (high speed downlink packet access) owing to multiple antennas. In order to reduce computational complexity, SMW theorem is used in LMMSE, and furthermore a pilot cancellation module is added. A PC-ILMMSE (pilot cancellation iterative LMMSE) algorithm is proposed. Theoretic analysis and computer simulations show that performance of PC-ILMMSE is superior to traditional LMMSE. But calculation of PC-ILMMSE is much lower than LMMSE

A novel signal recognition and signature code acquisition (SR/CA) method is proposed for DS-SS systems with frequency offset. Based on existing SR/CA methods, the new soft SR/CA method introduces double decision thresholds and an automatic frequency control (AFC) loop. The performance analysis and double thresholds set criteria are discussed. Numerical results show that the soft SR/CA method provides better detection performance, while false alarm probability hardly increases.

The purpose of this paper is to propose a modified explicit rate indication for congestion avoidance (MERICA) scheme for ATM networks. This modified scheme belongs to the class of closed-loop rate-based congestion control scheme. Three aspects are modified for making the scheme to adapt to various traffic types of ATM networks. First, the VBR and CBR traffics are considered. Second, a new congestion eliminating scheme is shown. Third, a new BECN mechanism for available bit rate (ABR) sources is presented. In the simulation model, two environments, LAN and WAN, are simulated to illustrate the performance factors, including the link utilization, the average waiting time, the fairness, and the loss rate. The simulation results show that the link utilization of MERICA performs well; meanwhile, its average delay and fairness are also better than other explicit rate congestion control mechanisms. Furthermore, the most attractive advantage is that MERICA has no loss in LAN and WAN environments.

This paper presents a new load balancing policy in heterogeneous distributed systems. All nodes in this system connected in point-to-point may have different service rates, and each node can serve not only external arrival tasks but also the tasks migrated from the other nodes. The scheduler takes into account the threshold value, based on the ratio of service rates, and the current queue length in determining whether one task shall be migrated to the other node or left for the local node. A Markov process model is used to describe the behavior of the heterogeneous distributed system under the proposed policies. The model is then solved by using the matrix-geometric solution technique. Performance of the policy is compared to that of the generic load balancing policy, no load balancing policy, and the ideal load balancing policy. The results show that the proposed policy is better and closer to the ideal load balancing policy. >

The congestion control scheme which prevents the network from congestion for ATM (asynchronous transfer mode) networks is presented. The proposed congestion scheme consists of two parts: a Markov chain model and a bandwidth allocation method. The Markov chain model is presented to estimate the quality of service of ATM networks, while the bandwidth allocation mechanism is to decide whether the anticipated connection can be accepted. From the simulation and analysis, the result shows that this congestion control scheme can not only multiplex the sources with heterogeneous traffic but also maintain a satisfactory level of the quality of service.

We propose a new gray relational measurement whose gray relational coefficient is called the gray relational coefficient of order k. Gray relational coefficient of order 1 is the traditional gray relational coefficient. With this new gray relational measurement, we can compute the gray relational matrix of order k for variables of systems. If k is large enough, the matrix would show the clusters of variables and the result is objective.