The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Giuseppe Caire - One of the best experts on this subject based on the ideXlab platform.

  • Joint User Selection, Power Allocation, and Precoding Design With Imperfect CSIT for Multi-Cell MU-MIMO Downlink Systems
    IEEE Transactions on Wireless Communications, 2020
    Co-Authors: Jiwook Choi, Songnam Hong, Giuseppe Caire
    Abstract:

    In this paper, a new optimization framework is presented for the joint design of user selection, power allocation, and precoding in Multi-Cell Multi-user Multiple-input Multiple-output (MU-MIMO) systems when imperfect channel state information at transmitter (CSIT) is available. By representing the joint optimization variables in a higher-dimensional space, the weighted sum-spectral efficiency maximization is formulated as the maximization of the product of Rayleigh quotients. Although this is still a non-convex problem, a computationally efficient algorithm, referred to as generalized power iteration precoding (GPIP), is proposed. The algorithm converges to a stationary point (local maximum) of the objective function and therefore it guarantees the first-order optimality of the solution. By adjusting the weights in the weighted sum-spectral efficiency, the GPIP yields a joint solution for user selection, power allocation, and downlink precoding. The GPIP can be extended to the Multi-Cell scenario where cooperative base stations perform joint user-Cell selection and design their precodes by taking into account the inter-Cell interference by sharing global imperfect CSIT. System-level simulations show the gains of the proposed approach with respect to conventional user selection and linear downlink precoding.

  • joint user selection power allocation and precoding design with imperfect csit for Multi Cell mu mimo downlink systems
    arXiv: Information Theory, 2019
    Co-Authors: Jiwook Choi, Namyoon Lee, Songnam Hong, Giuseppe Caire
    Abstract:

    In this paper, a new optimization framework is presented for the joint design of user selection, power allocation, and precoding in Multi-Cell Multi-user Multiple-input Multiple-output (MU-MIMO) systems when imperfect channel state information at transmitter (CSIT) is available. By representing the joint optimization variables in a higher-dimensional space, the weighted sum-spectral efficiency maximization is formulated as the maximization of the product of Rayleigh quotients. Although this is still a non-convex problem, a computationally efficient algorithm, referred to as generalized power iteration precoding (GPIP), is proposed. The algorithm converges to a stationary point (local maximum) of the objective function and therefore it guarantees the first-order optimality of the solution. By adjusting the weights in the weighted sum-spectral efficiency, the GPIP yields a joint solution for user selection, power allocation, and downlink precoding. The GPIP is also extended to a Multi-Cell scenario, where cooperative base stations perform joint user selection and design their precoding vectors by sharing global yet imperfect CSIT within the cooperative BSs. System-level simulations show the gains of the proposed approach with respect to conventional user selection and linear downlink precoding.

  • secure massive mimo transmission with an active eavesdropper
    IEEE Transactions on Information Theory, 2016
    Co-Authors: Yongpeng Wu, Robert Schober, Derrick Wing Kwan Ng, Chengshan Xiao, Giuseppe Caire
    Abstract:

    In this paper, we investigate secure and reliable transmission strategies for Multi-Cell Multi-user massive Multiple-input Multiple-output systems with a Multi-antenna active eavesdropper. We consider a time-division duplex system where uplink training is required and an active eavesdropper can attack the training phase to cause pilot contamination at the transmitter. This forces the precoder used in the subsequent downlink transmission phase to implicitly beamform toward the eavesdropper, thus increasing its received signal power. Assuming matched filter precoding and artificial noise (AN) generation at the transmitter, we derive an asymptotic achievable secrecy rate when the number of transmit antennas approaches infinity. For the case of a single-antenna active eavesdropper, we obtain a closed-form expression for the optimal power allocation policy for the transmit signal and the AN, and find the minimum transmit power required to ensure reliable secure communication. Furthermore, we show that the transmit antenna correlation diversity of the intended users and the eavesdropper can be exploited in order to improve the secrecy rate. In fact, under certain orthogonality conditions of the channel covariance matrices, the secrecy rate loss introduced by the eavesdropper can be completely mitigated.

Gayan Amarasuriya Aruma Baduge - One of the best experts on this subject based on the ideXlab platform.

  • reverse tdd based massive mimo systems with underlay spectrum sharing
    IEEE Transactions on Wireless Communications, 2019
    Co-Authors: Dhanushka Kudathanthirige, Gayan Amarasuriya Aruma Baduge
    Abstract:

    Multi-Cell Multi-user underlay spectrum-sharing massive Multiple-input Multiple-output systems operating with reverse time division duplexing (R-TDD) are investigated. By primarily aiming at fully mitigating intra-Cell pilot contamination and coherent interference, in the proposed R-TDD scheme, the primary/secondary systems are allowed to operate only in the opposite transmission directions. In order to establish fundamental performance limits, the secondary transmit power constraints and achievable rates are derived in the presence of training-based channel estimation. Thereby, the joint detrimental effects of spatial correlation, beamforming uncertainty, and inter-/intra-Cell coherence interference due to pilot contamination are quantified and compared against the conventional TDD (C-TDD) counterpart. A max–min optimal power control policy is designed, and thereby, the common achievable rates and power control coefficients are derived. It is shown that by invoking R-TDD, the secondary power constraints and sum rates can be made to become asymptotically independent of primary interference threshold. Thus, the secondary system can be operated with its maximum average transmit power, independent of the primary system without hindering its asymptotically achievable rates by the virtue of the inherent intra-Cell coherent interference mitigation benefit of the R-TDD. By exploiting the pilot decontamination feature of R-TDD, the achievable rates of primary/secondary systems can be significantly boosted, compared to the underlay spectrum sharing with C-TDD.

  • Wireless Energy Harvesting in Cognitive Massive MIMO Systems With Underlay Spectrum Sharing
    IEEE Wireless Communications Letters, 2017
    Co-Authors: Hayder Al-hraishawi, Gayan Amarasuriya Aruma Baduge
    Abstract:

    The achievable sum rate of a wireless-powered Multi-Cell/Multi-user cognitive radio massive Multiple-input Multiple-output system with underlay spectrum sharing is investigated. The secondary user nodes can harvest energy from the primary user transmissions, and then access and utilize the primary network spectrum for information transmission. The signal-to-interference-plus-noise ratio and achievable sum rate are derived for two specific antenna configurations: 1) unlimited base-station antenna arrays and 2) limited base-station antenna arrays. Furthermore, the optimal time-switching factor and the energy-rate trade-off are quantified in closed-form. The asymptotic analysis reveals that the secondary system can be operated by using its maximum harvested energy when the number of primary base-station antennas grows without bound without hindering the primary transmission.

Lingjia Liu - One of the best experts on this subject based on the ideXlab platform.

  • Multi Cell Multi user massive fd mimo downlink precoding and throughput analysis
    IEEE Transactions on Wireless Communications, 2019
    Co-Authors: Rubayet Shafin, Lingjia Liu
    Abstract:

    In this paper, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex Multi-Cell Multi-user massive full-dimension MIMO network. Utilizing channel reciprocity, DL channel state information feedback is eliminated and the DL Multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through the estimation of signal parameters via rotational invariance technique. Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. The simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced Multi-user MIMO precoding and power allocation strategy outperforms the existing zero-forcing-based massive MIMO strategies.

  • Multi Cell Multi user massive fd mimo downlink precoding and throughput analysis
    arXiv: Information Theory, 2018
    Co-Authors: Rubayet Shafin, Lingjia Liu
    Abstract:

    In this paper, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex (TDD) Multi-Cell Multi-user massive Full-Dimension MIMO (FD-MIMO) network. Utilizing channel reciprocity, DL channel state information (CSI) feedback is eliminated and the DL Multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through estimation of signal parameters via rotational invariance technique (ESPRIT). Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. Simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced Multi-user MIMO precoding and power allocation strategy outperforms existing zero-forcing based massive MIMO strategies.

Qingqing Wu - One of the best experts on this subject based on the ideXlab platform.

  • joint optimization of user association subchannel allocation and power allocation in Multi Cell Multi association ofdma heterogeneous networks
    arXiv: Signal Processing, 2020
    Co-Authors: Feng Wang, Wen Chen, Hongying Tang, Qingqing Wu
    Abstract:

    Heterogeneous network is a novel network architecture proposed in Long-Term-Evolution~(LTE), which highly increases the capacity and coverage compared with the conventional networks. However, in order to provide the best services, appropriate resource management must be applied. In this paper, we consider the joint optimization problem of user association, subchannel allocation, and power allocation for downlink transmission in Multi-Cell Multi-association Orthogonal Frequency Division Multiple Access (OFDMA) heterogeneous networks. To solve the optimization problem, we first divide it into two subproblems: 1) user association and subchannel allocation for fixed power allocation; 2) power allocation for fixed user association and subchannel allocation. Subsequently, we obtain a locally optimal solution for the joint optimization problem by solving these two subproblems alternately. For the first subproblem, we derive the globally optimal solution based on graph theory. For the second subproblem, we obtain a Karush-Kuhn-Tucker (KKT) optimal solution by a low complexity algorithm based on the difference of two convex functions approximation (DCA) method. In addition, the Multi-antenna receiver case and the proportional fairness case are also discussed. Simulation results demonstrate that the proposed algorithms can significantly enhance the overall network throughput.

Rubayet Shafin - One of the best experts on this subject based on the ideXlab platform.

  • Multi Cell Multi user massive fd mimo downlink precoding and throughput analysis
    IEEE Transactions on Wireless Communications, 2019
    Co-Authors: Rubayet Shafin, Lingjia Liu
    Abstract:

    In this paper, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex Multi-Cell Multi-user massive full-dimension MIMO network. Utilizing channel reciprocity, DL channel state information feedback is eliminated and the DL Multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through the estimation of signal parameters via rotational invariance technique. Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. The simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced Multi-user MIMO precoding and power allocation strategy outperforms the existing zero-forcing-based massive MIMO strategies.

  • Multi Cell Multi user massive fd mimo downlink precoding and throughput analysis
    arXiv: Information Theory, 2018
    Co-Authors: Rubayet Shafin, Lingjia Liu
    Abstract:

    In this paper, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex (TDD) Multi-Cell Multi-user massive Full-Dimension MIMO (FD-MIMO) network. Utilizing channel reciprocity, DL channel state information (CSI) feedback is eliminated and the DL Multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through estimation of signal parameters via rotational invariance technique (ESPRIT). Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. Simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced Multi-user MIMO precoding and power allocation strategy outperforms existing zero-forcing based massive MIMO strategies.