The Experts below are selected from a list of 23661 Experts worldwide ranked by ideXlab platform

Ahmed H Tewfik - One of the best experts on this subject based on the ideXlab platform.

  • non blocking scheme for blind network assisted diversity multiple access in synchronous channels
    IEEE Transactions on Wireless Communications, 2020
    Co-Authors: Naeem Akl, Ahmed H Tewfik
    Abstract:

    We design a Blind Network-Assisted Diversity Multiple Access (BNDMA) method for resolving packet Collisions in synchronous packet-switched networks. As opposed to typical BNDMA schemes, the method operates in non-blocking mode. Idle transmitters at the start of a Collision Resolution interval may join the set of active transmitters and contact the receiver before the end of the interval. A naive queuing analysis of the proposed scheme is exponentially complex in the size of the network. We carry out a computationally efficient analysis of the network throughput and queuing delay. We show that the suggested scheme reduces the queuing delay of the buffered packets at the transmitters without sacrificing the maximum throughput achieved by standard BNDMA. Further insights are derived from the numerical experiments.

  • Collision Resolution and interference elimination in multiaccess communication networks
    European Signal Processing Conference, 2017
    Co-Authors: Naeem Akl, Ahmed H Tewfik
    Abstract:

    We define a multiaccess communication scheme that effectively eliminates interference and resolves Collisions in many-to-one and many-to-many communication scenarios. Each transmitter is uniquely identified by a coding vector. Using these vectors, all signals issued from a specific transmitter will be aligned along a unique dimension at all receivers hearing this transmission. This dimension is characteristic of the transmitter. It also lies within a signal-and-noise subspace that is orthogonal to the noise-only subspace at the receiver. Signals along each dimension of the signal-and-noise subspace can be extracted separately using the properties of the Vandermonde matrix. The decoding algorithm is thus able to asymptotically achieve full network capacity at high signal-to-noise ratio (SNR) compared to 50% and 36.79% asymptotic throughputs for interference alignment and Ethernet respectively. Synchronization is assumed between the transmitters and the receiver(s). The number of transmitters is not necessarily known to each receiver.

  • Collision Resolution and interference elimination in multiaccess communication networks
    arXiv: Networking and Internet Architecture, 2017
    Co-Authors: Naeem Akl, Ahmed H Tewfik
    Abstract:

    We define a multiaccess communication scheme that effectively eliminates interference and resolves Collisions in many-to-one and many-to-many communication scenarios. Each transmitter is uniquely identified by a steering vector. All signals issued from a specific transmitter will be steered into the same single-dimensional or double-dimensional subspace at all receivers hearing this transmission. This subspace is orthogonal to the noise subspace at a receiver and the signals within the subspace can be extracted using the root-MUSIC method. At high SNR, local channel knowledge and strict synchronization, the algorithm asymptotically achieves full network capacity on condition that a channel remains constant within a single time slot. Without synchronization, the worst case asymptotic performance is still greater than the $50\%$ throughput achieved by Collision Resolution algorithms and interference management techniques like interference alignment.

Naeem Akl - One of the best experts on this subject based on the ideXlab platform.

  • non blocking scheme for blind network assisted diversity multiple access in synchronous channels
    IEEE Transactions on Wireless Communications, 2020
    Co-Authors: Naeem Akl, Ahmed H Tewfik
    Abstract:

    We design a Blind Network-Assisted Diversity Multiple Access (BNDMA) method for resolving packet Collisions in synchronous packet-switched networks. As opposed to typical BNDMA schemes, the method operates in non-blocking mode. Idle transmitters at the start of a Collision Resolution interval may join the set of active transmitters and contact the receiver before the end of the interval. A naive queuing analysis of the proposed scheme is exponentially complex in the size of the network. We carry out a computationally efficient analysis of the network throughput and queuing delay. We show that the suggested scheme reduces the queuing delay of the buffered packets at the transmitters without sacrificing the maximum throughput achieved by standard BNDMA. Further insights are derived from the numerical experiments.

  • Collision Resolution and interference elimination in multiaccess communication networks
    European Signal Processing Conference, 2017
    Co-Authors: Naeem Akl, Ahmed H Tewfik
    Abstract:

    We define a multiaccess communication scheme that effectively eliminates interference and resolves Collisions in many-to-one and many-to-many communication scenarios. Each transmitter is uniquely identified by a coding vector. Using these vectors, all signals issued from a specific transmitter will be aligned along a unique dimension at all receivers hearing this transmission. This dimension is characteristic of the transmitter. It also lies within a signal-and-noise subspace that is orthogonal to the noise-only subspace at the receiver. Signals along each dimension of the signal-and-noise subspace can be extracted separately using the properties of the Vandermonde matrix. The decoding algorithm is thus able to asymptotically achieve full network capacity at high signal-to-noise ratio (SNR) compared to 50% and 36.79% asymptotic throughputs for interference alignment and Ethernet respectively. Synchronization is assumed between the transmitters and the receiver(s). The number of transmitters is not necessarily known to each receiver.

  • Collision Resolution and interference elimination in multiaccess communication networks
    arXiv: Networking and Internet Architecture, 2017
    Co-Authors: Naeem Akl, Ahmed H Tewfik
    Abstract:

    We define a multiaccess communication scheme that effectively eliminates interference and resolves Collisions in many-to-one and many-to-many communication scenarios. Each transmitter is uniquely identified by a steering vector. All signals issued from a specific transmitter will be steered into the same single-dimensional or double-dimensional subspace at all receivers hearing this transmission. This subspace is orthogonal to the noise subspace at a receiver and the signals within the subspace can be extracted using the root-MUSIC method. At high SNR, local channel knowledge and strict synchronization, the algorithm asymptotically achieves full network capacity on condition that a channel remains constant within a single time slot. Without synchronization, the worst case asymptotic performance is still greater than the $50\%$ throughput achieved by Collision Resolution algorithms and interference management techniques like interference alignment.

Wei Zhang - One of the best experts on this subject based on the ideXlab platform.

  • a Collision Resolution protocol for random access in massive mimo
    IEEE Journal on Selected Areas in Communications, 2021
    Co-Authors: Lin Bai, Jinho Choi, Jiexun Liu, Wei Zhang
    Abstract:

    In 5G and beyond wireless scenarios, it is expected to support tremendous amount of communicating machines. With an exponential increase of machine-to-machine (M2M) system deployments, efficient approaches to massive access by a large number of devices are to be studied. In this paper, we propose a massive multiple-input multiple-output (MIMO) based grant-free random access (RA) with Resolution of preamble Collision for massive access. Based on the channel hardening and favorable propagation characteristics of massive MIMO, collided signals processed at the base station (BS) can be viewed as a variation of superposition modulation, and are to be recovered by successive interference cancellation (SIC) techniques. Besides, taking into consideration the effect of pass loss and fractional power control (FPC), analytic expressions of success probability of the proposed Collision Resolution with conjugate beamforming (CB) and zero-forcing beamforming (ZFB) are derived. With simulation results, we verify the analyses and show that the proposed protocol can resolve most preamble Collisions.

  • multiple delay estimation for Collision Resolution in non orthogonal random access
    IEEE Transactions on Vehicular Technology, 2020
    Co-Authors: Lin Bai, Jinho Choi, Rui Han, Jianwei Liu, Wei Zhang
    Abstract:

    In machine-type communications (MTC), contention-based random access is employed to support a number of MTC devices with a limited number of resource blocks (RBs). Since multiple active devices may transmit signals in the same RB or channel, the Collision caused by the presence of multiple signals is inevitable and the detection of Collision becomes important. Furthermore, if the arrival time and the number of multiple signals can be estimated, successive interference cancellation (SIC) can be employed in time domain to improve the throughput. In this paper, we focus on the estimation of round-trip delays (RTD) of multiple signals in non-orthogonal random access (NORA) based on the maximum likelihood (ML) criterion. Since the computational complexity of the ML approach is high, we propose a low-complexity approach based on variational inference, which is widely used in machine learning. We also show that the number of signals can be reliably estimated from the estimated RTDs.

Jinho Choi - One of the best experts on this subject based on the ideXlab platform.

  • a Collision Resolution protocol for random access in massive mimo
    IEEE Journal on Selected Areas in Communications, 2021
    Co-Authors: Lin Bai, Jinho Choi, Jiexun Liu, Wei Zhang
    Abstract:

    In 5G and beyond wireless scenarios, it is expected to support tremendous amount of communicating machines. With an exponential increase of machine-to-machine (M2M) system deployments, efficient approaches to massive access by a large number of devices are to be studied. In this paper, we propose a massive multiple-input multiple-output (MIMO) based grant-free random access (RA) with Resolution of preamble Collision for massive access. Based on the channel hardening and favorable propagation characteristics of massive MIMO, collided signals processed at the base station (BS) can be viewed as a variation of superposition modulation, and are to be recovered by successive interference cancellation (SIC) techniques. Besides, taking into consideration the effect of pass loss and fractional power control (FPC), analytic expressions of success probability of the proposed Collision Resolution with conjugate beamforming (CB) and zero-forcing beamforming (ZFB) are derived. With simulation results, we verify the analyses and show that the proposed protocol can resolve most preamble Collisions.

  • multiple delay estimation for Collision Resolution in non orthogonal random access
    IEEE Transactions on Vehicular Technology, 2020
    Co-Authors: Lin Bai, Jinho Choi, Rui Han, Jianwei Liu, Wei Zhang
    Abstract:

    In machine-type communications (MTC), contention-based random access is employed to support a number of MTC devices with a limited number of resource blocks (RBs). Since multiple active devices may transmit signals in the same RB or channel, the Collision caused by the presence of multiple signals is inevitable and the detection of Collision becomes important. Furthermore, if the arrival time and the number of multiple signals can be estimated, successive interference cancellation (SIC) can be employed in time domain to improve the throughput. In this paper, we focus on the estimation of round-trip delays (RTD) of multiple signals in non-orthogonal random access (NORA) based on the maximum likelihood (ML) criterion. Since the computational complexity of the ML approach is high, we propose a low-complexity approach based on variational inference, which is widely used in machine learning. We also show that the number of signals can be reliably estimated from the estimated RTDs.

  • Machine Learning Enabled Preamble Collision Resolution in Distributed Massive MIMO
    IEEE Transactions on Communications, 2026
    Co-Authors: Jie Ding, Pei Liu, Jinho Choi
    Abstract:

    Preamble Collision is a bottleneck that impairs the performance of random access (RA) user equipment (UE) in grant-free RA (GFRA). In this paper, by leveraging distributed massive multiple input multiple output (mMIMO) together with machine learning, a novel machine learning based framework solution is proposed to address the preamble Collision problem in GFRA. The key idea is to identify and employ the neighboring access points (APs) of a collided RA UE for its data decoding rather than all the APs, so that the mutual interference among collided RA UEs can be effectively mitigated. To this end, we first design a tailored deep neural network (DNN) to enable the preamble multiplicity estimation in GFRA, where an energy detection (ED) method is also proposed for performance comparison. With the estimated preamble multiplicity, we then propose a K-means AP clustering algorithm to cluster the neighboring APs of collided RA UEs and organize each AP cluster to decode the received data individually. Simulation results show that a decent performance of preamble multiplicity estimation in terms of accuracy and reliability can be achieved by the proposed DNN, and confirm that the proposed schemes are effective in preamble Collision Resolution in GFRA, which are able to achieve a near-optimal performance in terms of uplink achievable rate per collided RA UE, and offer significant performance improvement over traditional schemes.

Lin Bai - One of the best experts on this subject based on the ideXlab platform.

  • a Collision Resolution protocol for random access in massive mimo
    IEEE Journal on Selected Areas in Communications, 2021
    Co-Authors: Lin Bai, Jinho Choi, Jiexun Liu, Wei Zhang
    Abstract:

    In 5G and beyond wireless scenarios, it is expected to support tremendous amount of communicating machines. With an exponential increase of machine-to-machine (M2M) system deployments, efficient approaches to massive access by a large number of devices are to be studied. In this paper, we propose a massive multiple-input multiple-output (MIMO) based grant-free random access (RA) with Resolution of preamble Collision for massive access. Based on the channel hardening and favorable propagation characteristics of massive MIMO, collided signals processed at the base station (BS) can be viewed as a variation of superposition modulation, and are to be recovered by successive interference cancellation (SIC) techniques. Besides, taking into consideration the effect of pass loss and fractional power control (FPC), analytic expressions of success probability of the proposed Collision Resolution with conjugate beamforming (CB) and zero-forcing beamforming (ZFB) are derived. With simulation results, we verify the analyses and show that the proposed protocol can resolve most preamble Collisions.

  • multiple delay estimation for Collision Resolution in non orthogonal random access
    IEEE Transactions on Vehicular Technology, 2020
    Co-Authors: Lin Bai, Jinho Choi, Rui Han, Jianwei Liu, Wei Zhang
    Abstract:

    In machine-type communications (MTC), contention-based random access is employed to support a number of MTC devices with a limited number of resource blocks (RBs). Since multiple active devices may transmit signals in the same RB or channel, the Collision caused by the presence of multiple signals is inevitable and the detection of Collision becomes important. Furthermore, if the arrival time and the number of multiple signals can be estimated, successive interference cancellation (SIC) can be employed in time domain to improve the throughput. In this paper, we focus on the estimation of round-trip delays (RTD) of multiple signals in non-orthogonal random access (NORA) based on the maximum likelihood (ML) criterion. Since the computational complexity of the ML approach is high, we propose a low-complexity approach based on variational inference, which is widely used in machine learning. We also show that the number of signals can be reliably estimated from the estimated RTDs.