The Experts below are selected from a list of 144 Experts worldwide ranked by ideXlab platform
Inkyu Lee - One of the best experts on this subject based on the ideXlab platform.
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Bit allocation and pairing methods for multi user distributed antenna systems with limited Feedback
IEEE Transactions on Communications, 2014Co-Authors: Hoon Lee, Haewook Park, Eunsung Park, Inkyu LeeAbstract:In this paper, we study Bit allocation and pairing methods based on distributed zero forcing beamforming for downlink multi-user distributed antenna (DA) systems with limited Feedback. Before assigning the Feedback Bit for each DA port, we need to solve the pairing issue that determines the set of DA ports to support a user. To this end, we first analyze an upper bound of a mean rate loss between perfect channel state information systems and limited Feedback systems. Since minimizing the obtained bound is a joint optimization problem with respect to the pairing and the Bit allocation, it is difficult to identify a solution analytically. Instead, we propose a two-step algorithm that derives the pairing based on the bound of the rate loss and then obtain the non-iterative Bit allocation method independently. To further improve the performance, an enhanced Feedback Bit allocation algorithm is also proposed by applying an iterative optimization technique. In addition, we investigate a scaling law of limited Feedback systems to maintain a constant rate loss as signal-to-noise ratio increases. From simulation results, we confirm that the proposed algorithms offer about 135% performance gains over a conventional scheme for five DA port systems and verify that our analysis is well matched with the numerical results.
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Feedback Bit allocation schemes for multi user distributed antenna systems
IEEE Communications Letters, 2013Co-Authors: Eunsung Park, Heejin Kim, Haewook Park, Inkyu LeeAbstract:In this paper, we propose a Feedback Bit allocation algorithm for multi-user downlink distributed antenna systems with limited Feedback. We consider a composite fading channel with small scale fadings and path loss, and assume the case where each user is served by only one distributed antenna (DA) port while each DA port can support any number of users. In order to efficiently determine Bit allocation, we propose an iterative algorithm which minimizes an upper bound of a mean rate loss. Compared to conventional Bit allocation methods, the proposed algorithm can be applied to more general system configurations. Simulation results show that our proposed algorithm offers a performance gain of 20% over an equal Bit allocation scheme.
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Novel Feedback Bit Allocation Methods for Multi-Cell Joint Processing Systems
IEEE Transactions on Wireless Communications, 2012Co-Authors: Han-bae Kong, Young-tae Kim, Seok-hwan Park, Inkyu LeeAbstract:In this letter, we study multiple-input single-output joint processing (JP) systems with limited Feedback where base stations exchange both channel state information and their data via ideal backhaul links. In order to optimize the sum-rate performance of the JP system, we propose a new Feedback Bit allocation scheme which maximizes quantization accuracy in the presence of pathloss. The quantization accuracy is formulated by the expectation of the inner product between the actual channel vector and the quantized channel vector. First, we derive the quantization accuracy as a closed form, which compensates the phase difference of two channels. Then, the maximum quantization accuracy is achieved by searching possible Bit combinations. Simulation results show that the sum rate of our proposed Feedback Bit allocation strategy is more than twice compared to the conventional equal Bit allocation method in the three cell case.
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adaptive Bit allocation methods for multi cell joint processing systems with limited Feedback
Personal Indoor and Mobile Radio Communications, 2011Co-Authors: Young-tae Kim, Seok-hwan Park, Inkyu LeeAbstract:In this paper, we study multiple-input single-output joint processing (JP) systems with limited Feedback where two adjacent base stations exchange both channel state information and their data. To optimize the sum-rate performance of the JP system, we propose a new Feedback Bit allocation method which maximizes quantization accuracy in the presence of pathloss. The quantization accuracy is formulated by the expectation of the inner product between the actual channel vector and the quantized channel vector. In order to maximize the quantization accuracy, we employ a new method which compensates the phase difference of the two channels. Through numerical evaluations, we show that our proposed Feedback Bit allocation strategies provide about 50% performance gain in terms of the sum rate performance compared to the conventional method with the equal Bit allocation scheme.
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PIMRC - Adaptive Bit allocation methods for multi-cell joint processing systems with limited Feedback
2011 IEEE 22nd International Symposium on Personal Indoor and Mobile Radio Communications, 2011Co-Authors: Young-tae Kim, Seok-hwan Park, Inkyu LeeAbstract:In this paper, we study multiple-input single-output joint processing (JP) systems with limited Feedback where two adjacent base stations exchange both channel state information and their data. To optimize the sum-rate performance of the JP system, we propose a new Feedback Bit allocation method which maximizes quantization accuracy in the presence of pathloss. The quantization accuracy is formulated by the expectation of the inner product between the actual channel vector and the quantized channel vector. In order to maximize the quantization accuracy, we employ a new method which compensates the phase difference of the two channels. Through numerical evaluations, we show that our proposed Feedback Bit allocation strategies provide about 50% performance gain in terms of the sum rate performance compared to the conventional method with the equal Bit allocation scheme.
Merouane Debbah - One of the best experts on this subject based on the ideXlab platform.
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On Feedback Resource Allocation in Multiple-Input-Single-Output Systems Using Partial CSI Feedback
IEEE Transactions on Communications, 2015Co-Authors: Behrooz Makki, Tommy Svensson, Thomas Eriksson, Merouane DebbahAbstract:—This paper studies the problem of Feedback resource allocation in multiple-input-single-output (MISO) channels utilizing partial channel state information (CSI) Feedback. Considering low/moderate signal-to-noise ratios (SNRs), the optimal quantizers and the Feedback Bit allocation maximizing the throughput are obtained in the asymptotic case where the number of Feedback Bits increases. Moreover, the results are utilized to derive the optimal retransmission rates in the automatic repeat request (ARQ) protocols and joint CSI-ARQ schemes are proposed for the MISO setups. We show that uniform channel amplitude quantization is asymptotically optimal in terms of throughput. Also, the optimal retransmission rates of the incremental redundancy (INR) ARQ protocols follow an arithmetic progression in the exponential domain. Under certain conditions, a MISO system using quantized CSI can be mapped to a MISO or a SISO (S: single) setup using ARQ or joint CSI-ARQ Feedback in the sense that they lead to the same throughput. Finally, to maximize the throughput, the optimal number of channel direction quantization Bits should be (M − 1) times the number of amplitude quantization Bits, where M is the number of transmit antennas. Index Terms—CSI quantization, HARQ Feedback, MIMO transmission, throughput, joint phase-amplitude information Feedback, incremental redundancy (INR) ARQ.
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On Feedback Resource Allocation in Multiple-Input-Single-Output Systems Using Partial CSI Feedback
IEEE Transactions on Communications, 2015Co-Authors: Behrooz Makki, Tommy Svensson, Thomas Eriksson, Merouane DebbahAbstract:This paper studies the problem of Feedback resource allocation in multiple-input-single-output (MISO) channels utilizing partial channel state information (CSI) Feedback. Considering low/moderate signal-to-noise ratios (SNRs), the optimal quantizers and the Feedback Bit allocation maximizing the throughput are obtained in the asymptotic case where the number of Feedback Bits increases. Moreover, the results are utilized to derive the optimal retransmission rates in the automatic repeat request (ARQ) protocols and joint CSI-ARQ schemes are proposed for the MISO setups. We show that uniform channel amplitude quantization is asymptotically optimal in terms of throughput. Also, the optimal retransmission rates of the incremental redundancy (INR) ARQ protocols follow an arithmetic progression in the exponential domain. Under certain conditions, a MISO system using quantized CSI can be mapped to a MISO or a SISO (S: single) setup using ARQ or joint CSI-ARQ Feedback in the sense that they lead to the same throughput. Finally, to maximize the throughput, the optimal number of channel direction quantization Bits should be $(M-1)$ times the number of amplitude quantization Bits, where $M$ is the number of transmit antennas.
Behrooz Makki - One of the best experts on this subject based on the ideXlab platform.
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On Feedback Resource Allocation in Multiple-Input-Single-Output Systems Using Partial CSI Feedback
IEEE Transactions on Communications, 2015Co-Authors: Behrooz Makki, Tommy Svensson, Thomas Eriksson, Merouane DebbahAbstract:—This paper studies the problem of Feedback resource allocation in multiple-input-single-output (MISO) channels utilizing partial channel state information (CSI) Feedback. Considering low/moderate signal-to-noise ratios (SNRs), the optimal quantizers and the Feedback Bit allocation maximizing the throughput are obtained in the asymptotic case where the number of Feedback Bits increases. Moreover, the results are utilized to derive the optimal retransmission rates in the automatic repeat request (ARQ) protocols and joint CSI-ARQ schemes are proposed for the MISO setups. We show that uniform channel amplitude quantization is asymptotically optimal in terms of throughput. Also, the optimal retransmission rates of the incremental redundancy (INR) ARQ protocols follow an arithmetic progression in the exponential domain. Under certain conditions, a MISO system using quantized CSI can be mapped to a MISO or a SISO (S: single) setup using ARQ or joint CSI-ARQ Feedback in the sense that they lead to the same throughput. Finally, to maximize the throughput, the optimal number of channel direction quantization Bits should be (M − 1) times the number of amplitude quantization Bits, where M is the number of transmit antennas. Index Terms—CSI quantization, HARQ Feedback, MIMO transmission, throughput, joint phase-amplitude information Feedback, incremental redundancy (INR) ARQ.
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On Feedback Resource Allocation in Multiple-Input-Single-Output Systems Using Partial CSI Feedback
IEEE Transactions on Communications, 2015Co-Authors: Behrooz Makki, Tommy Svensson, Thomas Eriksson, Merouane DebbahAbstract:This paper studies the problem of Feedback resource allocation in multiple-input-single-output (MISO) channels utilizing partial channel state information (CSI) Feedback. Considering low/moderate signal-to-noise ratios (SNRs), the optimal quantizers and the Feedback Bit allocation maximizing the throughput are obtained in the asymptotic case where the number of Feedback Bits increases. Moreover, the results are utilized to derive the optimal retransmission rates in the automatic repeat request (ARQ) protocols and joint CSI-ARQ schemes are proposed for the MISO setups. We show that uniform channel amplitude quantization is asymptotically optimal in terms of throughput. Also, the optimal retransmission rates of the incremental redundancy (INR) ARQ protocols follow an arithmetic progression in the exponential domain. Under certain conditions, a MISO system using quantized CSI can be mapped to a MISO or a SISO (S: single) setup using ARQ or joint CSI-ARQ Feedback in the sense that they lead to the same throughput. Finally, to maximize the throughput, the optimal number of channel direction quantization Bits should be $(M-1)$ times the number of amplitude quantization Bits, where $M$ is the number of transmit antennas.
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Fairness, power allocation, and CSI quantization in block fading multiuser systems
EURASIP Journal on Wireless Communications and Networking, 2013Co-Authors: Behrooz Makki, Thomas ErikssonAbstract:This paper studies the fairness, power allocation, and channel state information (CSI) quantization in multiuser systems utilizing multiple Feedback Bits per user. For a given set of schedulers, we obtain the system throughput with different power allocation strategies and any combination of different fading distributions. Moreover, the system performance under user different outage probability constraints is investigated. Assuming homogenous users, as a special case, the throughput is determined for fixed and random request networks . Considering nonidentical fading channels between the transmitter and receivers, the throughput is found under the K-significant average Feedback Bit allocation technique, and two suboptimal fairness schemes are investigated which satisfy different quality-of-service requirements. The results show that using optimal power allocation, the first quantization region (QR) of each user is the only QR for which no power may be allocated. The system outage probability vanishes as the number of users goes to infinity. Users hard outage probability constraints can be satisfied at the cost of one more QR in the channel quantizer. Finally, the proposed fairness schemes are more flexible than the standard proportional fair (PF) scheduling in dealing with the throughput-fairness tradeoff. However, their superiority over PF scheduling depends on the fairness constraint.
Dacheng Yang - One of the best experts on this subject based on the ideXlab platform.
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WCNC - User-specific coordination of limited Feedback with power allocation in multi-point system
2013 IEEE Wireless Communications and Networking Conference (WCNC), 2013Co-Authors: Chi Zhang, Yongyu Chang, Dacheng YangAbstract:Coordinated multi-point transmission with limited rate Feedback has been paid much attention recently due to its ability to overcome the detrimental propagation conditions. In the limited Feedback multi-point transmission, how to allocate the appropriate Feedback Bits among the users has become a critical issue to be investigated. The existing schemes have not considered the impact of the flexible power allocation on the Feedback Bit allocation among the users. The main contribution of this paper is to propose a user-specific coordination scheme to dynamically coordinate the Feedback Bit number for each user according to the overall result of power allocation in the limited Feedback multi-point transmission. We also develop an iteration algorithm to efficiently achieve the satisfactory solution of our proposed issue. Simulation results will show the advantages of our proposed scheme.
Thomas Eriksson - One of the best experts on this subject based on the ideXlab platform.
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On Feedback Resource Allocation in Multiple-Input-Single-Output Systems Using Partial CSI Feedback
IEEE Transactions on Communications, 2015Co-Authors: Behrooz Makki, Tommy Svensson, Thomas Eriksson, Merouane DebbahAbstract:—This paper studies the problem of Feedback resource allocation in multiple-input-single-output (MISO) channels utilizing partial channel state information (CSI) Feedback. Considering low/moderate signal-to-noise ratios (SNRs), the optimal quantizers and the Feedback Bit allocation maximizing the throughput are obtained in the asymptotic case where the number of Feedback Bits increases. Moreover, the results are utilized to derive the optimal retransmission rates in the automatic repeat request (ARQ) protocols and joint CSI-ARQ schemes are proposed for the MISO setups. We show that uniform channel amplitude quantization is asymptotically optimal in terms of throughput. Also, the optimal retransmission rates of the incremental redundancy (INR) ARQ protocols follow an arithmetic progression in the exponential domain. Under certain conditions, a MISO system using quantized CSI can be mapped to a MISO or a SISO (S: single) setup using ARQ or joint CSI-ARQ Feedback in the sense that they lead to the same throughput. Finally, to maximize the throughput, the optimal number of channel direction quantization Bits should be (M − 1) times the number of amplitude quantization Bits, where M is the number of transmit antennas. Index Terms—CSI quantization, HARQ Feedback, MIMO transmission, throughput, joint phase-amplitude information Feedback, incremental redundancy (INR) ARQ.
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On Feedback Resource Allocation in Multiple-Input-Single-Output Systems Using Partial CSI Feedback
IEEE Transactions on Communications, 2015Co-Authors: Behrooz Makki, Tommy Svensson, Thomas Eriksson, Merouane DebbahAbstract:This paper studies the problem of Feedback resource allocation in multiple-input-single-output (MISO) channels utilizing partial channel state information (CSI) Feedback. Considering low/moderate signal-to-noise ratios (SNRs), the optimal quantizers and the Feedback Bit allocation maximizing the throughput are obtained in the asymptotic case where the number of Feedback Bits increases. Moreover, the results are utilized to derive the optimal retransmission rates in the automatic repeat request (ARQ) protocols and joint CSI-ARQ schemes are proposed for the MISO setups. We show that uniform channel amplitude quantization is asymptotically optimal in terms of throughput. Also, the optimal retransmission rates of the incremental redundancy (INR) ARQ protocols follow an arithmetic progression in the exponential domain. Under certain conditions, a MISO system using quantized CSI can be mapped to a MISO or a SISO (S: single) setup using ARQ or joint CSI-ARQ Feedback in the sense that they lead to the same throughput. Finally, to maximize the throughput, the optimal number of channel direction quantization Bits should be $(M-1)$ times the number of amplitude quantization Bits, where $M$ is the number of transmit antennas.
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Fairness, power allocation, and CSI quantization in block fading multiuser systems
EURASIP Journal on Wireless Communications and Networking, 2013Co-Authors: Behrooz Makki, Thomas ErikssonAbstract:This paper studies the fairness, power allocation, and channel state information (CSI) quantization in multiuser systems utilizing multiple Feedback Bits per user. For a given set of schedulers, we obtain the system throughput with different power allocation strategies and any combination of different fading distributions. Moreover, the system performance under user different outage probability constraints is investigated. Assuming homogenous users, as a special case, the throughput is determined for fixed and random request networks . Considering nonidentical fading channels between the transmitter and receivers, the throughput is found under the K-significant average Feedback Bit allocation technique, and two suboptimal fairness schemes are investigated which satisfy different quality-of-service requirements. The results show that using optimal power allocation, the first quantization region (QR) of each user is the only QR for which no power may be allocated. The system outage probability vanishes as the number of users goes to infinity. Users hard outage probability constraints can be satisfied at the cost of one more QR in the channel quantizer. Finally, the proposed fairness schemes are more flexible than the standard proportional fair (PF) scheduling in dealing with the throughput-fairness tradeoff. However, their superiority over PF scheduling depends on the fairness constraint.