This article presents limited feedback-based precoder quantization schemes for Interference Alignment (IA) with bounded channel state information (CSI) uncertainty. Initially, this work generalizes the min-max mean sq...
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This article presents limited feedback-based precoder quantization schemes for Interference Alignment (IA) with bounded channel state information (CSI) uncertainty. Initially, this work generalizes the min-max mean squared error (MSE) framework, followed by the development of robust precoder and decoder designs based on worst case MSE minimization. The proposed precoder and decoder designs capture the effect of CSI uncertainty using a single parameter, which is independent of the CSI uncertainty in the direct links. The IA algorithms derived employing these proposed designs are shown to be globally convergent under certain conditions. Moreover, precoder quantization schemes are presented for scenarios with and without CSI uncertainty for practical implementation of these techniques in systems with limited feedback. An optimal bit allocation scheme is presented to maximize the sum rate via analysis of the rate loss upper bound. Simulation results demonstrate the improved performance of the proposed IA schemes for various scenarios considering imperfect CSI as well as limited feedback.
This paper presents two analog precoder feedback (PFB) schemes namely the simple PFB (SPFB) scheme and the reduced PFB (RPFB) scheme for interference channels. In the first scheme, each destination transmits full prec...
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This paper presents two analog precoder feedback (PFB) schemes namely the simple PFB (SPFB) scheme and the reduced PFB (RPFB) scheme for interference channels. In the first scheme, each destination transmits full precoder, while in the second one, the size of the precoder to be fed back is reduced by removing the redundant rows of the precoder matrix. This reduced feedback is particularly useful in the systems, where the number of transmit antennas are more than the number of receive antennas. These schemes have been analyzed for the cases where time slots in the feedback duration are independent of the number of users and where the time slots scale linearly with the number of users. For both these schemes, the precoder reconstruction methods are investigated using the chordal distance. For interference alignment, the rate loss upper bound analysis shows that the rate loss increases with signal-to-noise-ratio (SNR) at low SNR, while it remains constant in high SNR range. Simulation results verify that the linear sum rate scaling is preserved at high SNRs. The full precoder feedback dominates, when the source cooperation is assumed, while RPFB yields improvements over SPFB scheme, when no source cooperation is assumed and Kd time slots are utilized in either orthogonal or independent transmission case.
In this paper, we modeled the precoder feedback for interference channel as a combinatorial optimization problem. Conventionally, in limited feedback, chordal distance has been used to find the best precoder index fro...
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ISBN:
(纸本)9781509017461
In this paper, we modeled the precoder feedback for interference channel as a combinatorial optimization problem. Conventionally, in limited feedback, chordal distance has been used to find the best precoder index from the codebook. But, the brute force approach on the problem shows that higher sumrates can be achieved with the same sized codebook, i.e, the same feedback bits. Thus, in this paper, we propose a method to get better sum rates in limited feedback. The simulation results show that the proposed approach perform close to brute force approach and gives better sum rates than the approaches like chordal distance, maximizing SINR, etc.
In this paper, we compare the precoder and channel feedback in interference channel (IC) when interference alignment (IA) is used. In literature, the channel direction has been quantized and fed back in IC. Here, we c...
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ISBN:
(纸本)9781509053568
In this paper, we compare the precoder and channel feedback in interference channel (IC) when interference alignment (IA) is used. In literature, the channel direction has been quantized and fed back in IC. Here, we consider the precoder quantization and feedback (PQFB) in IC, and seek its benefits over channel feedback. The involvement of IA (where the alignment is sensitive to channel changes) and comparison of required time slots, codebook size and feedback bit rate, show that PQFB is a better choice. The theoretical rate loss for both schemes show that precoder feedback gives less loss in sum rate as compared to channel direction feedback. These results are verified with simulations.
Channel state information (CSI) feedback is a challenging issue in frequency division duplexing (FDD) massive MIMO systems. This paper studies a cooperative feedback scheme, where the users first exchange their CSI wi...
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Channel state information (CSI) feedback is a challenging issue in frequency division duplexing (FDD) massive MIMO systems. This paper studies a cooperative feedback scheme, where the users first exchange their CSI with each other through device-to-device (D2D) communications, then compute the precoder by themselves, and feedback the precoder to the base station (BS). Analytical results are derived to show that the cooperative precoder feedback is more efficient than the CSI feedback in terms of interference mitigation. To reduce the delays for CSI exchange, we develop an adaptive CSI exchange strategy based on signal subspace projection and optimal bit partition. Numerical results demonstrate that the proposed cooperative precoder feedback scheme with adaptive CSI exchange significantly outperforms the CSI feedback scheme, even under moderate delays for CSI exchange via D2D.
Virtual reality (VR)/augmented reality (AR) and its applications have attracted significant and increasing attention recently. However, the stringent quality of service (QoS) requirements and better spectral efficienc...
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ISBN:
(纸本)9781728173993
Virtual reality (VR)/augmented reality (AR) and its applications have attracted significant and increasing attention recently. However, the stringent quality of service (QoS) requirements and better spectral efficiency have posed the challenges such as higher bandwidth, lower latency and better reliability on the VR/AR communication system. This paper proposes a deep-learning-based (DL-based) precoding and feedback method for mitigating the channel interference of multi-users VR/AR environments. That is, our DL-based method uses the VR/AR channel state information (CSI) to do radio resource allocation for maximizing the millimeter-wave network throughput. Numerical results show that our DL-based design could significantly enhance the throughput.
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