In this letter, we propose a new blind source separation method, independent low-rank matrix analysis based on generalized Kullback-Leibler divergence. This method assumes a time-frequency-varying complex Poisson distribution as the source generative model, which yields convex optimization in the spectrogram estimation. The experimental evaluation confirms the proposed method's efficacy.

As RFID technology is being more widely adopted, it is fairly common to read mobile tags using RFID systems, such as packages on conveyer belt and unit loads on pallet jack or forklift truck. In RFID systems, multiple tags use a shared medium for communicating with a reader. It is quite possible that tags will exit the reading area without being read, which results in tag leaking. In this letter, a reliable tag anti-collision algorithm for mobile tags is proposed. It reliably estimates the expectation of the number of tags arriving during a time slot when new tags continually enter the reader's reading area and no tag leaves without being read. In addition, it gives priority to tags that arrived early among read cycles and applies the expectation of the number of tags arriving during a time slot to the determination of the number of slots in the initial inventory round of the next read cycle. Simulation results show that the reliability of the proposed algorithm is close to that of DFSA algorithm when the expectation of the number of tags entering the reading area during a time slot is a given, and is better than that of DFSA algorithm when the number of time slots in the initial inventory round of next read cycle is set to 1 assuming that the number of tags arriving during a time slot follows Poisson distribution.

Network Coding (NC) can improve the information transmission efficiency and throughput of data networks. Random Linear Network Coding (RLNC) is a special form of NC scheme that is easy to be implemented. However, quantifying the performance gain of RLNC over conventional Store and Forward (S/F)-based routing system, especially for wireless network, remains an important open issue. To solve this problem, in this paper, based on abstract layer network architecture, we build a dynamic random network model with Poisson distribution describing the nodes joining the network randomly for tree-based single-source multicast in MANET. We then examine its performance by applying conventional Store and Forward with FEC (S/F-FEC) and RLNC methods respectively, and derive the analytical function expressions of average packet loss rate, successful decoding ratio and throughput with respect to the link failure probability. An experiment shows that these expressions have relatively high precision in describing the performance of RLNC. It can be used to design the practical network coding algorithm for multi-hop multicast with tree-based topology in MANET and provide a research tool for the performance analysis of RLNC.

In this letter, we propose an effective cooperative caching system under the assumption that each web object is accessed randomly. Under this assumption, the access frequency per unit time is given by Poisson distribution and the probability distribution of the web object in the future is derived. Based on this probability distribution, one can obtain the criterion to allocate the web objects with more access expected to the cache servers closer to clients. It is also shown that there is a tradeoff between the precision to allocate objects and the efficiency of caching.

This letter presents a lower bound and approximation for the coverage probability of the pilot channel that can be used for a CDMA downlink design. The approximation of a compound truncated Poisson distribution is used to obtain a closed form equation for the coverage probability of the pilot channel. Computer simulations show that our lower bound curve is truly less than the empirical curve, and our proposed approximation agrees well with the empirical result.