Downlink Asynchronous Non-Orthogonal Multiple Access With Quantizer Optimization

Zou, Xun; Ganji, Mehdi; Jafarkhani, Hamid

doi:10.1109/lwc.2020.2998407

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…As explained in Appendix A, the rate loss in Region II.C is due to incorrect user ordering. Hence, the rate loss expression in (38) (…”

Section: Appendix Ementioning

confidence: 99%

“…The availability of the quantized channel gains instead of perfect channel state information (CSI) creates the following two major issues. First, the quantized channel gains can result in a severe rate loss [37], [38]. This phenomenon is more harmful when the quantized channel gains inaccurately change the order of NOMA users.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, researchers have investigated the impact of limited feedback on NOMA [37], [38], [40]- [43]. In NOMA with low feedback (e.g., one-bit or two-bit feedback), the limited feedback is used for user ordering [40]- [43].…”

Section: Introductionmentioning

confidence: 99%

“…It is demonstrated that a low feedback NOMA under the assumption of directional transmission in sub-6 GHz massive MIMO and millimeter wave can achieve an outage probability close to that of full CSI NOMA. In [38], a scalar quantizer is deployed for precise channel gain quantization to attain fairness among users. None of work has considered the impact of incorrect user ordering due to the limited feedback in their studies.…”

Section: Introductionmentioning

confidence: 99%

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Rate Loss Analysis of Reconfigurable Intelligent Surface-Aided NOMA With Limited Feedback

Almasi,

Jafarkhani

2024

IEEE Open J. Commun. Soc.

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The design of feedback channels in frequency division duplex (FDD) systems is a major challenge because of the limited available feedback bits. We consider non-orthogonal multiple access (NOMA) systems that incorporate reconfigurable intelligent surfaces (RISs). In limited feedback RIS-aided NOMA systems, the RIS-aided channel and the direct channel gains should be quantized and fed back to the transmitter. We investigate the rate loss of the overall RIS-aided NOMA systems suffering from quantization errors under Rayleigh and Rician fading channel models. We first consider random vector quantization for the overall RIS-aided channel and identical uniform quantizers for the direct channel gains. We then obtain an upper bound for the rate loss in Rayleigh fading, due to the quantization error, as a function of the number of feedback bits and the size of RIS. In addition, we determine the channel gain values for which NOMA is advantageous under full channel state information (CSI) but not with the quantized feedback. We perform a similar analysis assuming Rician models by approximating the extremely complicated probability density function (pdf) of a RIS-aided double-Rician channel. Our numerical results indicate that, for a small RIS size, the sum rate performance of the limited feedback system approaches that of the system with full CSI as the number of feedback bits increases. However, as the size of RIS enlarges, the sum rate improvement slows down. Further, by increasing the number of feedback bits and the transmit power, the probability that NOMA should be chosen over OMA increases.

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“…As explained in Appendix A, the rate loss in Region II.C is due to incorrect user ordering. Hence, the rate loss expression in (38) (…”

Section: Appendix Ementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Rate Loss Analysis of Reconfigurable Intelligent Surface-Aided NOMA With Limited Feedback

Almasi,

Jafarkhani

2024

IEEE Open J. Commun. Soc.

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“…In the case of multiple users, a mismatch between the quantized CSIT and the channel realization leads to a loss of the achievable rate at high signal-to-noise ratio (SNR) due to interference. To overcome the rate degradation, several methods have been studied [14]- [24]. The quantization error can be made small by simply increasing the number of feedback bits [14]- [18].…”

mentioning

confidence: 99%

Robust Precoding Designs for Multiuser MIMO Systems With Limited Feedback

Zhou,

Zhang,

Debbah

et al. 2024

IEEE Trans. Wireless Commun.

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It has been well known that the achievable rate of multiuser multiple-input multiple-output systems with limited feedback is severely degraded by quantization errors when the number of feedback bits is not sufficient. To overcome such a rate degradation, we propose new robust precoding designs which can compensate for the quantization errors. In this paper, we first analyze the achievable rate of traditional precoding designs for limited feedback systems. Then, we obtain an approximation of the second-order statistics of quantized channel state information. With the aid of the derived approximation, we propose robust precoding designs in terms of the mean square error (MSE) with conditional expectation in non-iterative and iterative fashions. For the non-iterative precoding design, we study a robust minimum MSE (MMSE) precoding algorithm by extending a new channel decomposition. Also, in the case of iterative precoding, we investigate a robust weighted MMSE (WMMSE) precoding to further improve the achievable rate. Simulation results show that the proposed precoding schemes yield significant improvements over traditional precoding designs.

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Achievable rate analysis of a generalized uplink asynchronous non-orthogonal multiple access with MSK-type signals

Dang

et al. 2022

Digital Signal Processing

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Downlink Asynchronous Non-Orthogonal Multiple Access With Quantizer Optimization

Cited by 5 publications

References 9 publications

Rate Loss Analysis of Reconfigurable Intelligent Surface-Aided NOMA With Limited Feedback

Rate Loss Analysis of Reconfigurable Intelligent Surface-Aided NOMA With Limited Feedback

Robust Precoding Designs for Multiuser MIMO Systems With Limited Feedback

Achievable rate analysis of a generalized uplink asynchronous non-orthogonal multiple access with MSK-type signals

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