28 research outputs found

    Reinforcement-based data transmission in temporally-correlated fading channels: Partial CSIT scenario

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    Reinforcement algorithms refer to the schemes where the results of the previous trials and a reward-punishment rule are used for parameter setting in the next steps. In this paper, we use the concept of reinforcement algorithms to develop different data transmission models in wireless networks. Considering temporally-correlated fading channels, the results are presented for the cases with partial channel state information at the transmitter (CSIT). As demonstrated, the implementation of reinforcement algorithms improves the performance of communication setups remarkably, with the same feedback load/complexity as in the state-of-the-art schemes.Comment: Accepted for publication in ISWCS 201

    CSI feedback in correlated slow-fading channels

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    This letter studies the effect of quantized channel state information (CSI) feedback on the average rate of correlated channels. Demonstrating the general rate optimization problem, the results are obtained for both delayed and delay-free feedback conditions under different short- and long-term power allocation strategies. We also evaluate the effect of adaptive CSI quantization on the channel average rate. Analytical and numerical results show that exploiting the channel memory not only increases the forward channel data transmission efficiency but also can lead to dramatic feedback rate reduction

    Throughput Analysis for Multi-Point Joint Transmission with Quantized CSI Feedback

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    This paper addresses the problem of limited CSI feedback in coordinated multi-point (CoMP) networks. Specifically, the system throughput is obtained for block-fading CoMP channels with quantized CSI feedback, and the effect of feedback bit allocation on the system throughput is investigated for different user locations and fading distributions. The analytical and simulation results show that substantial throughput increment is achieved via CoMP joint transmission with very limited number of feedback bits per base station. The effect of optimal bit allocation becomes more important for the user that is located in the CoMP cluster edge areas. Also, the standard Zonal-sampling scheme provides the best bit allocation strategy in many cases, maximizing the system throughput

    Interference management using one bit feedback

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    This paper studies the performance of quasi-static spectrum sharing networks utilizing one bit interference indicator feedback. Assuming no channel state information at the transmitters, the channel average rate is obtained under different power allocation strategies. Simulation results show that interference indicator feedback leads to considerable rate increment even with no transmitter channel state information

    Interference-free spectrum sharing using a sequential decoder at the primary user

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    Recently, substantial attention has been paid to improve the spectral efficiency of communication setups using different spectrum sharing techniques. This paper studies the ergodic achievable rate of spectrum sharing channels in the case where the primary licensed user is equipped with a sequential decoder, while there is no connection between the transmitters. Assuming Rayleigh block-fading channels, the unlicensed user ergodic achievable rate is obtained under an extremely hard constraint where no interference is tolerated by the licensed user receiver. Simulation results show that using sequential decoders there is considerable potential for data transmission of the unlicensed user with no performance degradation of the licensed user. Moreover, in contrast to previously proposed schemes, the network sum rate increases by implementation of sequential decoders

    Power allocation in repetition time diversity hybrid automatic repeat request feedback

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    This paper addresses the problem of optimal power allocation for hybrid automatic repeat request (HARQ) feedback over slowly-fading channels. We mainly focus on the repetition time diversity HARQ scheme where the results are obtained for both continuous and bursting communication models. Moreover, the effect of an outage probability constraint on the system data transmission efficiency is studied under different transmission power constraints. Simulation results show that 1) for Nakagami fading channels, the optimal HARQ-based (re)transmission powers maximizing the system throughput should be decreasing in every (re)transmission round, 2) higher rates are achieved in the continuous communication, when compared with the bursting model, and 3) HARQ feedback leads to considerable performance improvement even in outage-limited conditions

    Optimization of Training and Feedback Overhead for Beamforming over Block Fading Channels

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    We examine the capacity of beamforming over a single-user, multi-antenna link taking into account the overhead due to channel estimation and limited feedback of channel state information. Multi-input single-output (MISO) and multi-input multi-output (MIMO) channels are considered subject to block Rayleigh fading. Each coherence block contains LL symbols, and is spanned by TT training symbols, BB feedback bits, and the data symbols. The training symbols are used to obtain a Minimum Mean Squared Error estimate of the channel matrix. Given this estimate, the receiver selects a transmit beamforming vector from a codebook containing 2B2^B {\em i.i.d.} random vectors, and sends the corresponding BB bits back to the transmitter. We derive bounds on the beamforming capacity for MISO and MIMO channels and characterize the optimal (rate-maximizing) training and feedback overhead (TT and BB) as LL and the number of transmit antennas NtN_t both become large. The optimal NtN_t is limited by the coherence time, and increases as L/logLL/\log L. For the MISO channel the optimal T/LT/L and B/LB/L (fractional overhead due to training and feedback) are asymptotically the same, and tend to zero at the rate 1/logNt1/\log N_t. For the MIMO channel the optimal feedback overhead B/LB/L tends to zero faster (as 1/log2Nt1/\log^2 N_t).Comment: accepted for IEEE Trans. Info. Theory, 201
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