The Experts below are selected from a list of 39627 Experts worldwide ranked by ideXlab platform
Jianjun Huang - One of the best experts on this subject based on the ideXlab platform.
-
sparsity based space time adaptive processing for airborne radar with coprime array and coprime pulse repetition interval
International Conference on Acoustics Speech and Signal Processing, 2018Co-Authors: Xiaoye Wang, Zhaocheng Yang, Jianjun HuangAbstract:In this paper, we present a sparsity-based space-time adaptive processing (STAP) algorithm with coprime array and coprime pulse repetition interval (PRI). The considered space-time coprime configuration can significantly save the cost. However, the direct STAP does not exploit the advantage of the large aperture brought by coprime configuration and the recently developed spatial-temporal smoothed-based STAP requires a large number of training snapshots. To solve these issues, we propose a sparsity-based STAP algorithm by using the spacial-temporal sparsity of clutter in Virtual Domain. Simulation results show that the proposed algorithm can obtain a much higher output signal-to-interference-plus-noise ratio and improve the convergence speed.
-
ICASSP - Sparsity-Based Space-Time Adaptive Processing for Airborne Radar with Coprime Array and Coprime Pulse Repetition Interval
2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018Co-Authors: Xiaoye Wang, Zhaocheng Yang, Jianjun HuangAbstract:In this paper, we present a sparsity-based space-time adaptive processing (STAP) algorithm with coprime array and coprime pulse repetition interval (PRI). The considered space-time coprime configuration can significantly save the cost. However, the direct STAP does not exploit the advantage of the large aperture brought by coprime configuration and the recently developed spatial-temporal smoothed-based STAP requires a large number of training snapshots. To solve these issues, we propose a sparsity-based STAP algorithm by using the spacial-temporal sparsity of clutter in Virtual Domain. Simulation results show that the proposed algorithm can obtain a much higher output signal-to-interference-plus-noise ratio and improve the convergence speed.
Xiaoye Wang - One of the best experts on this subject based on the ideXlab platform.
-
sparsity based space time adaptive processing for airborne radar with coprime array and coprime pulse repetition interval
International Conference on Acoustics Speech and Signal Processing, 2018Co-Authors: Xiaoye Wang, Zhaocheng Yang, Jianjun HuangAbstract:In this paper, we present a sparsity-based space-time adaptive processing (STAP) algorithm with coprime array and coprime pulse repetition interval (PRI). The considered space-time coprime configuration can significantly save the cost. However, the direct STAP does not exploit the advantage of the large aperture brought by coprime configuration and the recently developed spatial-temporal smoothed-based STAP requires a large number of training snapshots. To solve these issues, we propose a sparsity-based STAP algorithm by using the spacial-temporal sparsity of clutter in Virtual Domain. Simulation results show that the proposed algorithm can obtain a much higher output signal-to-interference-plus-noise ratio and improve the convergence speed.
-
ICASSP - Sparsity-Based Space-Time Adaptive Processing for Airborne Radar with Coprime Array and Coprime Pulse Repetition Interval
2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018Co-Authors: Xiaoye Wang, Zhaocheng Yang, Jianjun HuangAbstract:In this paper, we present a sparsity-based space-time adaptive processing (STAP) algorithm with coprime array and coprime pulse repetition interval (PRI). The considered space-time coprime configuration can significantly save the cost. However, the direct STAP does not exploit the advantage of the large aperture brought by coprime configuration and the recently developed spatial-temporal smoothed-based STAP requires a large number of training snapshots. To solve these issues, we propose a sparsity-based STAP algorithm by using the spacial-temporal sparsity of clutter in Virtual Domain. Simulation results show that the proposed algorithm can obtain a much higher output signal-to-interference-plus-noise ratio and improve the convergence speed.
Xingwei Wang - One of the best experts on this subject based on the ideXlab platform.
-
SVDR: A scalable Virtual Domain-based routing scheme for CCN
Computer Networks, 2018Co-Authors: Xingwei Wang, Min HuangAbstract:Abstract Content Centric Networking (CCN) is a new networking paradigm where communication pattern is shifted from host-based to content-based. It defines all resources as contents and builds Forwarding Information Base (FIB) indexed with content names instead of addresses. Hence, with the growth of content, scalability becomes the Achilles heel in CCN. To solve it, we propose the Scalable Virtual Domain-based Routing (SVDR) scheme that alleviates FIB scalability in view of memory cost and populating overhead. SVDR leverages the concept of Virtual Domain to reduce route entries maintained in FIB and puts forward a two-stage routing protocol to build FIB with light populating overhead. Moreover, the improved methods are proposed to enhance scalability of SVDR further based on the influence analysis of Virtual Domain structure on FIB load. Performance evaluation demonstrates that SVDR reduces FIB load significantly with low populating overhead.
-
TVDR: A Two-Level Virtual Domain Routing Scheme for Content-Centric Networking
IEEE Access, 2018Co-Authors: Xingwei Wang, Min HuangAbstract:In content-centric networking (CCN), the content is retrieved based on its name with the aid of in-network caching, instead of relying on IP address. Since the number of content names is several orders of magnitude higher than that of IP addresses, it presents a significant scalability challenge. Moreover, CCN caches content in every passed router, so multiple identical copies may exist among nearby routers. To address these problems, we propose two-level Virtual Domain routing (TVDR) utilizing the concept of the Virtual Domain to reduce FIB entries maintained in the network. To improve cache utilization, we introduce a new caching strategy TVDR-Membership to assign cache capacity. To demonstrate the feasibility of TVDR, We evaluate the TVDR against classical CCN and hash-based routing to assess its feasibility. Results show that TVDR effectively improves scalability and cache utilization and decreases processing delay to fetch contents.
-
ICN - VDR: A Virtual Domain-Based Routing Scheme for CCN
Proceedings of the 2nd ACM Conference on Information-Centric Networking, 2015Co-Authors: Jiachen Chen, Mayutan Arumaithurai, Xingwei WangAbstract:In this work, we propose VDR, a routing scheme based on Virtual Domains -- Domains that are not bound to physical routers -- to exploit the benefits of aggregation and hashing while overcoming their disadvantages. VDR addresses the FIB scalability issue in CCN by facilitating aggregation without compromising on the advantages of CCN such as ease of data replication and obtaining the data from a closer source. Our preliminary evaluation shows that VDR lowers the number of FIB entries present at a router significantly without compromising much on path stretch.
Zhaocheng Yang - One of the best experts on this subject based on the ideXlab platform.
-
sparsity based space time adaptive processing for airborne radar with coprime array and coprime pulse repetition interval
International Conference on Acoustics Speech and Signal Processing, 2018Co-Authors: Xiaoye Wang, Zhaocheng Yang, Jianjun HuangAbstract:In this paper, we present a sparsity-based space-time adaptive processing (STAP) algorithm with coprime array and coprime pulse repetition interval (PRI). The considered space-time coprime configuration can significantly save the cost. However, the direct STAP does not exploit the advantage of the large aperture brought by coprime configuration and the recently developed spatial-temporal smoothed-based STAP requires a large number of training snapshots. To solve these issues, we propose a sparsity-based STAP algorithm by using the spacial-temporal sparsity of clutter in Virtual Domain. Simulation results show that the proposed algorithm can obtain a much higher output signal-to-interference-plus-noise ratio and improve the convergence speed.
-
ICASSP - Sparsity-Based Space-Time Adaptive Processing for Airborne Radar with Coprime Array and Coprime Pulse Repetition Interval
2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018Co-Authors: Xiaoye Wang, Zhaocheng Yang, Jianjun HuangAbstract:In this paper, we present a sparsity-based space-time adaptive processing (STAP) algorithm with coprime array and coprime pulse repetition interval (PRI). The considered space-time coprime configuration can significantly save the cost. However, the direct STAP does not exploit the advantage of the large aperture brought by coprime configuration and the recently developed spatial-temporal smoothed-based STAP requires a large number of training snapshots. To solve these issues, we propose a sparsity-based STAP algorithm by using the spacial-temporal sparsity of clutter in Virtual Domain. Simulation results show that the proposed algorithm can obtain a much higher output signal-to-interference-plus-noise ratio and improve the convergence speed.
Min Huang - One of the best experts on this subject based on the ideXlab platform.
-
SVDR: A scalable Virtual Domain-based routing scheme for CCN
Computer Networks, 2018Co-Authors: Xingwei Wang, Min HuangAbstract:Abstract Content Centric Networking (CCN) is a new networking paradigm where communication pattern is shifted from host-based to content-based. It defines all resources as contents and builds Forwarding Information Base (FIB) indexed with content names instead of addresses. Hence, with the growth of content, scalability becomes the Achilles heel in CCN. To solve it, we propose the Scalable Virtual Domain-based Routing (SVDR) scheme that alleviates FIB scalability in view of memory cost and populating overhead. SVDR leverages the concept of Virtual Domain to reduce route entries maintained in FIB and puts forward a two-stage routing protocol to build FIB with light populating overhead. Moreover, the improved methods are proposed to enhance scalability of SVDR further based on the influence analysis of Virtual Domain structure on FIB load. Performance evaluation demonstrates that SVDR reduces FIB load significantly with low populating overhead.
-
TVDR: A Two-Level Virtual Domain Routing Scheme for Content-Centric Networking
IEEE Access, 2018Co-Authors: Xingwei Wang, Min HuangAbstract:In content-centric networking (CCN), the content is retrieved based on its name with the aid of in-network caching, instead of relying on IP address. Since the number of content names is several orders of magnitude higher than that of IP addresses, it presents a significant scalability challenge. Moreover, CCN caches content in every passed router, so multiple identical copies may exist among nearby routers. To address these problems, we propose two-level Virtual Domain routing (TVDR) utilizing the concept of the Virtual Domain to reduce FIB entries maintained in the network. To improve cache utilization, we introduce a new caching strategy TVDR-Membership to assign cache capacity. To demonstrate the feasibility of TVDR, We evaluate the TVDR against classical CCN and hash-based routing to assess its feasibility. Results show that TVDR effectively improves scalability and cache utilization and decreases processing delay to fetch contents.
