The Experts below are selected from a list of 336 Experts worldwide ranked by ideXlab platform

Mohamedslim Alouini - One of the best experts on this subject based on the ideXlab platform.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    IEEE Transactions on Wireless Communications, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS)-based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs, energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for the RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer–Rao lower bound is also derived as a benchmark to evaluate the localization performance of the developed technique. The extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    arXiv: Signal Processing, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS) based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer Rao lower bound (CRLB) is also derived as a benchmark to evaluate the localization performance of the developed technique. Extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • underwater Optical sensor networks localization with limited connectivity
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    In this paper, a received signal strength (RSS) based localization technique is investigated for underwater Optical wireless sensor networks (UOWSNs) where Optical Noise sources (e.g., sunlight, background, thermal, and dark current) and channel impairments of seawater (e.g., absorption, scattering, and turbulence) pose significant challenges. Hence, we propose a localization technique that works on the noisy ranging measurements embedded in a higher dimensional space and localize the sensor network in a low dimensional space. Once the neighborhood information is measured, a weighted network graph is constructed, which contains the one-hop neighbor distance estimations. A novel approach is developed to complete the missing distances in the kernel matrix. The output of the proposed technique is fused with Helmert transformation to refine the final location estimation with the help of anchors. The simulation results show that the root means square positioning error (RMSPE) of the proposed technique is more robust and accurate compared to baseline and manifold regularization.

Nasir Saeed - One of the best experts on this subject based on the ideXlab platform.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    IEEE Transactions on Wireless Communications, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS)-based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs, energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for the RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer–Rao lower bound is also derived as a benchmark to evaluate the localization performance of the developed technique. The extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    arXiv: Signal Processing, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS) based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer Rao lower bound (CRLB) is also derived as a benchmark to evaluate the localization performance of the developed technique. Extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • underwater Optical sensor networks localization with limited connectivity
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    In this paper, a received signal strength (RSS) based localization technique is investigated for underwater Optical wireless sensor networks (UOWSNs) where Optical Noise sources (e.g., sunlight, background, thermal, and dark current) and channel impairments of seawater (e.g., absorption, scattering, and turbulence) pose significant challenges. Hence, we propose a localization technique that works on the noisy ranging measurements embedded in a higher dimensional space and localize the sensor network in a low dimensional space. Once the neighborhood information is measured, a weighted network graph is constructed, which contains the one-hop neighbor distance estimations. A novel approach is developed to complete the missing distances in the kernel matrix. The output of the proposed technique is fused with Helmert transformation to refine the final location estimation with the help of anchors. The simulation results show that the root means square positioning error (RMSPE) of the proposed technique is more robust and accurate compared to baseline and manifold regularization.

Abdulkadir Celik - One of the best experts on this subject based on the ideXlab platform.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    IEEE Transactions on Wireless Communications, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS)-based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs, energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for the RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer–Rao lower bound is also derived as a benchmark to evaluate the localization performance of the developed technique. The extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    arXiv: Signal Processing, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS) based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer Rao lower bound (CRLB) is also derived as a benchmark to evaluate the localization performance of the developed technique. Extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • underwater Optical sensor networks localization with limited connectivity
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    In this paper, a received signal strength (RSS) based localization technique is investigated for underwater Optical wireless sensor networks (UOWSNs) where Optical Noise sources (e.g., sunlight, background, thermal, and dark current) and channel impairments of seawater (e.g., absorption, scattering, and turbulence) pose significant challenges. Hence, we propose a localization technique that works on the noisy ranging measurements embedded in a higher dimensional space and localize the sensor network in a low dimensional space. Once the neighborhood information is measured, a weighted network graph is constructed, which contains the one-hop neighbor distance estimations. A novel approach is developed to complete the missing distances in the kernel matrix. The output of the proposed technique is fused with Helmert transformation to refine the final location estimation with the help of anchors. The simulation results show that the root means square positioning error (RMSPE) of the proposed technique is more robust and accurate compared to baseline and manifold regularization.

Tareq Y Alnaffouri - One of the best experts on this subject based on the ideXlab platform.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    IEEE Transactions on Wireless Communications, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS)-based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs, energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for the RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer–Rao lower bound is also derived as a benchmark to evaluate the localization performance of the developed technique. The extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • localization of energy harvesting empowered underwater Optical wireless sensor networks
    arXiv: Signal Processing, 2019
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    This paper proposes a received signal strength (RSS) based localization framework for energy harvesting underwater Optical wireless sensor networks (EH-UOWSNs), where the Optical Noise sources and channel impairments of seawater pose significant challenges on range estimation. In UOWSNs energy limitation is another major problem due to the limited battery power and difficulty to replace or recharge the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery harvest ambient energy and start communicating once they have sufficient storage of energy. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater Optical communication channel characteristics. Thereafter, block kernel matrices are computed for RSS-based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the estimation error of the shortest path for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every Optical sensor node in the network. An analytical expression for the Cramer Rao lower bound (CRLB) is also derived as a benchmark to evaluate the localization performance of the developed technique. Extensive simulations show that the proposed framework outperforms the well-known network localization techniques.

  • underwater Optical sensor networks localization with limited connectivity
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Nasir Saeed, Abdulkadir Celik, Tareq Y Alnaffouri, Mohamedslim Alouini
    Abstract:

    In this paper, a received signal strength (RSS) based localization technique is investigated for underwater Optical wireless sensor networks (UOWSNs) where Optical Noise sources (e.g., sunlight, background, thermal, and dark current) and channel impairments of seawater (e.g., absorption, scattering, and turbulence) pose significant challenges. Hence, we propose a localization technique that works on the noisy ranging measurements embedded in a higher dimensional space and localize the sensor network in a low dimensional space. Once the neighborhood information is measured, a weighted network graph is constructed, which contains the one-hop neighbor distance estimations. A novel approach is developed to complete the missing distances in the kernel matrix. The output of the proposed technique is fused with Helmert transformation to refine the final location estimation with the help of anchors. The simulation results show that the root means square positioning error (RMSPE) of the proposed technique is more robust and accurate compared to baseline and manifold regularization.

Ailing Tian - One of the best experts on this subject based on the ideXlab platform.

  • Optical Noise free image encryption based on quick response code and high dimension chaotic system in gyrator transform domain
    Optics and Lasers in Engineering, 2017
    Co-Authors: Minjie Xu, Ailing Tian
    Abstract:

    Abstract A novel Optical image encryption scheme is proposed based on quick response code and high dimension chaotic system, where only the intensity distribution of encoded information is recorded as ciphertext. Initially, the quick response code is engendered from the plain image and placed in the input plane of the double random phase encoding architecture. Then, the code is encrypted to the ciphertext with Noise-like distribution by using two cascaded gyrator transforms. In the process of encryption, the parameters such as rotation angles and random phase masks are generated as interim variables and functions based on Chen system. A new phase retrieval algorithm is designed to reconstruct the initial quick response code in the process of decryption, in which a priori information such as three position detection patterns is used as the support constraint. The original image can be obtained without any energy loss by scanning the decrypted code with mobile devices. The ciphertext image is the real-valued function which is more convenient for storing and transmitting. Meanwhile, the security of the proposed scheme is enhanced greatly due to high sensitivity of initial values of Chen system. Extensive cryptanalysis and simulation have performed to demonstrate the feasibility and effectiveness of the proposed scheme.

  • Optical Noise-free image encryption based on quick response code and high dimension chaotic system in gyrator transform domain
    Optics and Lasers in Engineering, 2017
    Co-Authors: Liansheng Sui, Ailing Tian
    Abstract:

    Abstract A novel Optical image encryption scheme is proposed based on quick response code and high dimension chaotic system, where only the intensity distribution of encoded information is recorded as ciphertext. Initially, the quick response code is engendered from the plain image and placed in the input plane of the double random phase encoding architecture. Then, the code is encrypted to the ciphertext with Noise-like distribution by using two cascaded gyrator transforms. In the process of encryption, the parameters such as rotation angles and random phase masks are generated as interim variables and functions based on Chen system. A new phase retrieval algorithm is designed to reconstruct the initial quick response code in the process of decryption, in which a priori information such as three position detection patterns is used as the support constraint. The original image can be obtained without any energy loss by scanning the decrypted code with mobile devices. The ciphertext image is the real-valued function which is more convenient for storing and transmitting. Meanwhile, the security of the proposed scheme is enhanced greatly due to high sensitivity of initial values of Chen system. Extensive cryptanalysis and simulation have performed to demonstrate the feasibility and effectiveness of the proposed scheme.