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Quantization Noise Reduction by Digital Signal Processing-assisted Analog-to-digital Converter for In-band Full-duplex Systems

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In-band full-duplex (IBFD) systems are attracting attention as a key technology for ideally doubling channel capacity for beyond 5G and 6G. First, we propose an analytical model of the effect… Click to show full abstract

In-band full-duplex (IBFD) systems are attracting attention as a key technology for ideally doubling channel capacity for beyond 5G and 6G. First, we propose an analytical model of the effect of N-bit analog-to-digital converter (A/D) quantization noise on channel capacity quasi-upper limit of the desired signal at the base station of the IBFD systems. We derive averaged and peak powers of input signal to N-bit A/D and quantization noise power of N-bit A/D to formulate uplink (UL) channel capacity quasi-upper limit. Numerical analysis results by the proposed analytical model show that the UL channel capacity quasi-upper limit degrades by 16% and 80% in the 12- and 8-bit A/D, respectively. Second, we propose digital signal-processing (DSP)-assisted dual- and quad-A/Ds to reduce the quantization noise effect in IBFD systems. When A/D resolution bit is 8-bit, the proposed DSP-assisted dual- and quad-A/Ds improve the UL channel capacity quasi-upper limit by up to 92.3 and 192%, respectively, compared to conventional A/D for peak-to-average power ratio condition of 15 dB and analog self-interference (SI) cancellation capability of 30 dB. The proposed dual- and quad-A/Ds can reduce the burden on the analog SI cancellation circuitry by 6 and 12 dB, respectively.

Keywords: channel capacity; quantization; quantization noise

Journal Title: IEEE Transactions on Wireless Communications
Year Published: 2022

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