The Experts below are selected from a list of 5805 Experts worldwide ranked by ideXlab platform

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

  • power efficient radio resource allocation for low medium altitude aerial platform based td lte networks
    Vehicular Technology Conference, 2012
    Co-Authors: Liqiang Zhao, Chi Zhang, Hailin Zhang, Lajos Hanzo
    Abstract:

    In order to provide an increased capacity, throughput and QoS guarantee for terrestrial users in emergency scenarios, a low-medium-altitude aerial platform based time-Division-Duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Additionally a power-efficient radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game. Our simulation results demonstrate that the proposed algorithm imposes an attractive tradeoff between the achievable throughput and the power consumption while ensuring fairness among users.

  • radio resource allocation for low medium altitude aerial platform based td lte networks against disaster
    Vehicular Technology Conference, 2012
    Co-Authors: Liqiang Zhao, Fumiyuki Adachi, Chi Zhang, Hailin Zhang
    Abstract:

    In order to provide an increased capacity for voice users in emergency scenarios, a low-medium-altitude aerial platform based time-Division-Duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Furthermore, a novel radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game to provide real-time voice communications with as many users as possible. Our simulation results demonstrate that compared with the traditional radio resource management algorithms, the proposed algorithm achieves the largest capacity, i.e., the number of serviced users.

Liqiang Zhao - One of the best experts on this subject based on the ideXlab platform.

  • power efficient radio resource allocation for low medium altitude aerial platform based td lte networks
    Vehicular Technology Conference, 2012
    Co-Authors: Liqiang Zhao, Chi Zhang, Hailin Zhang, Lajos Hanzo
    Abstract:

    In order to provide an increased capacity, throughput and QoS guarantee for terrestrial users in emergency scenarios, a low-medium-altitude aerial platform based time-Division-Duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Additionally a power-efficient radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game. Our simulation results demonstrate that the proposed algorithm imposes an attractive tradeoff between the achievable throughput and the power consumption while ensuring fairness among users.

  • radio resource allocation for low medium altitude aerial platform based td lte networks against disaster
    Vehicular Technology Conference, 2012
    Co-Authors: Liqiang Zhao, Fumiyuki Adachi, Chi Zhang, Hailin Zhang
    Abstract:

    In order to provide an increased capacity for voice users in emergency scenarios, a low-medium-altitude aerial platform based time-Division-Duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Furthermore, a novel radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game to provide real-time voice communications with as many users as possible. Our simulation results demonstrate that compared with the traditional radio resource management algorithms, the proposed algorithm achieves the largest capacity, i.e., the number of serviced users.

Shi Jin - One of the best experts on this subject based on the ideXlab platform.

  • sparse bayesian learning for the time varying massive mimo channels acquisition and tracking
    IEEE Transactions on Communications, 2019
    Co-Authors: Shun Zhang, Feifei Gao, Shi Jin
    Abstract:

    The low-rank property of the channel covariances can be adopted to reduce the overhead of the channel training in massive MIMO systems. In this paper, with the help of the virtual channel representation, we apply such property to both time-Division Duplex and frequency-Division Duplex systems, where the time-varying channel scenarios are considered. First, we formulate the dynamic massive MIMO channel as one sparse signal model. Then, an expectation maximization-based sparse Bayesian learning framework is developed to learn the model parameters of the sparse virtual channel. Specifically, the Kalman filter (KF) and the Rauch–Tung–Striebel smoother are utilized to track the model parameters of the uplink (UL) spatial sparse channel in the expectation step. During the maximization step, a fixed-point theorem-based algorithm and a low-complex searching method are constructed to recover the temporal varying characteristics and the spatial signatures, respectively. With the angle reciprocity, we recover the downlink (DL) model parameters from the UL ones. After that, the KF with the reduced dimension is adopt to fully exploit the channel temporal correlations to enhance the DL/UL virtual channel tracking accuracy. A monitoring scheme is also designed to detect the change of model parameters and trigger the relearning process. Finally, we demonstrate the efficacy of the proposed schemes through the numerical simulations.

  • a unified transmission strategy for tdd fdd massive mimo systems with spatial basis expansion model
    IEEE Transactions on Vehicular Technology, 2017
    Co-Authors: Hongxiang Xie, Shun Zhang, Feifei Gao, Shi Jin
    Abstract:

    This paper proposes a unified transmission strategy for multiuser time Division Duplex (TDD)/frequency Division Duplex (FDD) massive multiple-input–multiple-output (MIMO) systems, including uplink (UL)/downlink (DL) channel estimation and user scheduling for data transmission. With the aid of antenna array theory and array signal processing, we build a spatial basis expansion model (SBEM) to represent the UL/DL channels with far fewer parameter dimensions. Hence, both the UL and DL channel estimations of multiusers can be carried out with a small amount of training resource, which significantly reduces the training overhead and feedback cost. Meanwhile, the pilot contamination problem in the UL training is immediately relieved by exploiting the spatial information of users. To enhance the spectral efficiency, we also design a greedy user scheduling scheme during the data transmission period. Compared with existing low-rank models, the newly proposed SBEM offers an alternative for channel acquisition without the need for channel statistics and can be applied to both TDD and FDD systems. Various numerical results are provided to corroborate the proposed studies.

  • a full space spectrum sharing strategy for massive mimo cognitive radio systems
    IEEE Journal on Selected Areas in Communications, 2016
    Co-Authors: Hongxiang Xie, Feifei Gao, Bolei Wang, Shi Jin
    Abstract:

    In this paper, we introduce a new spatial spectrum-sharing strategy for massive multiple-input multiple-output (MIMO) cognitive radio (CR) systems. Different from the conventional MIMO CR system, CR terminals can be discriminated by their angular information with the help of high spatial resolution of massive antennas at CR base station (CBS). Moreover, the discrete Fourier transform can be applied to efficiently obtain such angular information thanks to the massive antennas, again. We then formulate a 2-D spatial basis expansion model to represent the uplink/downlink channels of CRs with reduced parameter dimensions, which immediately alleviates the general headaches of massive MIMO systems, such as uplink pilot contamination and downlink training overhead. Moreover, we present a full-space coverage concept by employing two CBSs at the adjacent sides of each cell, which diminishes the sheltering effect from the primary radio. We also design two greedy CR scheduling algorithms for the dual CBSs to improve the spectral efficiency and enhance the scheduling probability of CRs. Since the proposed strategy exploits angular information and since the angle reciprocity holds for two frequency carriers with moderate distance, the proposed strategy is applied for both time Division Duplex and frequency Division Duplex systems.

  • ul dl channel estimation for tdd fdd massive mimo systems using dft and angle reciprocity
    Vehicular Technology Conference, 2016
    Co-Authors: Hongxiang Xie, Shun Zhang, Feifei Gao, Shi Jin
    Abstract:

    This paper proposes a novel channel estimation scheme for the multiuser massive multiple-input multiple-output (MIMO) systems. A discrete Fourier transform (DFT) aided spatial basis expansion model (SBEM) is first introduced to represent the uplink (UL)/downlink (DL) channels with much few parameter dimensions by exploiting the physical characteristics of the uniform linear array (ULA). With SBEM, pilot contamination in the UL training can be relieved by user scheduling exploiting their spatial information. Moreover, the UL spatial information can help to simplify the DL training based on the angle reciprocity. Compared to existing low-rank models, the newly proposed SBEM does not need any information of channel statistics and is suitable for both time Division Duplex (TDD) and frequency Division Duplex (FDD) systems. Moreover, the proposed method can be efficiently deployed by the fast Fourier transform (FFT) followed by linear estimator. Various numerical results are provided to corroborate the proposed studies.

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

  • power efficient radio resource allocation for low medium altitude aerial platform based td lte networks
    Vehicular Technology Conference, 2012
    Co-Authors: Liqiang Zhao, Chi Zhang, Hailin Zhang, Lajos Hanzo
    Abstract:

    In order to provide an increased capacity, throughput and QoS guarantee for terrestrial users in emergency scenarios, a low-medium-altitude aerial platform based time-Division-Duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Additionally a power-efficient radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game. Our simulation results demonstrate that the proposed algorithm imposes an attractive tradeoff between the achievable throughput and the power consumption while ensuring fairness among users.

  • radio resource allocation for low medium altitude aerial platform based td lte networks against disaster
    Vehicular Technology Conference, 2012
    Co-Authors: Liqiang Zhao, Fumiyuki Adachi, Chi Zhang, Hailin Zhang
    Abstract:

    In order to provide an increased capacity for voice users in emergency scenarios, a low-medium-altitude aerial platform based time-Division-Duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Furthermore, a novel radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game to provide real-time voice communications with as many users as possible. Our simulation results demonstrate that compared with the traditional radio resource management algorithms, the proposed algorithm achieves the largest capacity, i.e., the number of serviced users.

Lajos Hanzo - One of the best experts on this subject based on the ideXlab platform.