The Khatri-Rao(KR) subspace method is a high resolution method for direction-of-arrival(DOA) estimation.Combined with 2q level nested array,the KR subspace method can detect O(N2q) sources with N sensors.However,the method cannot be applicable to Gaussian sources when q is equal to or greater than 2 since it needs to use 2q-th order cumulants.In this work,a novel approach is presented to conduct DOA estimation by constructing a fourth order difference co-array.Unlike the existing DOA estimation method based on the KR product and 2q level nested array,the proposed method only uses second order statistics,so it can be employed to Gaussian sources as well as non-Gaussian sources.By exploiting a four-level nested array with N elements,our method can also identify O(N4) sources.In order to estimate the wideband signals,the proposed method is extended to the wideband scenarios.Simulation results demonstrate that,compared to the state of the art KR subspace based methods,the new method achieves higher resolution.
Information-centric networking （ICN） proposes a content-centric paradigm which has some attractive advantages, such as network load reduction, low dissemination latency, and energy efficiency. In this paper, based on the analytical model of ICN with receiver-driven transport protocol employing least-recently used （LRU） replacement policy, we derive expressions to compute the average content delivery time of the requests＇ arrival sequence of a single cache, and then we extend the expressions to a cascade of caches＇ scenario. From the expressions, we know the quantitative relationship among the delivery time, cache size and bandwidth. Our results, analyzing the trade-offs between performance and resources in ICN, can be used as a guide to design ICN and to evaluation its performance.
WANG Guo-qingHUANG TaoLIU JiangCHEN Jian-yaLIU Yun-jie
Content center networking （CCN） is one of the most promising future network architectures. Current researches on CCN routing scheme mainly focus on finding the best single routing path, which may induce to low usage of the in-network caches. In order to overcome this problem, a reverse trace routing （RTR） scheme is proposed in this paper, in which Interest packet is sent to the edge-cache along with the reverse trace of the corresponding former Data packet. By doing this, the Interest packets will have better chances to be routed to the promising in-network caches before reaching the source server, which could increase the in-network hit rate, while decrease the server stress. The simulation results show clearly that the RTR scheme decreases the source server load, while reducing the mean hops of entire data retrieval process under certain circumstances.
One of the key research fields of content-centric networking （CCN） is to develop more efficient cache replacement policies to improve the hit ratio of CCN in-network caching. However, most of existing cache strategies designed mainly based on the time or frequency of content access, can not properly deal with the problem of the dynamicity of content popularity in the network. In this paper, we propose a fast convergence caching replacement algorithm based on dynamic classification method for CCN, named as FCDC. It develops a dynamic classification method to reduce the time complexity of cache inquiry, which achieves a higher caching hit rate in comparison to random classification method under dynamic change of content popularity. Meanwhile, in order to relieve the influence brought about by dynamic content popularity, it designs a weighting function to speed up cache hit rate convergence in the CCN router. Experimental results show that the proposed scheme outperforms the replacement policies related to least recently used （LRU） and recent usage frequency （RUF） in cache hit rate and resiliency when content popularity in the network varies.
