Abstract
The paper proposes a joint blind iterative Self-Interference (SI) cancellation, propagation channel estimation and decoding algorithm in Full-Duplex (FD) transmissions via feedback of channel estimates and decoded messages combined with the process of Digital Self-Interference Cancellation (DSIC). Different from the conventional algorithm, the proposed blind algorithm simultaneously estimates the self-interference and propagation channels and decodes messages in each decoding iteration of 5G Quasi-Cyclic Low Density Parity Check (QC-LDPC) codes. The temporary propagation channel estimate and decoded message are fed back to improve the self-interference cancellation and also the channel estimation as well as decoding in the next iteration. The results show that the proposed algorithm outperforms the conventional algorithm, especially at high signal to noise ratio (SNR) and small number of symbols, and requires much less processing time and computational complexity while achieving the convergence performance. The results also show that the proposed algorithm is less sensitive to SI level than the conventional algorithm. The paper further proposes a partial feedback scheme, which only use few feedback symbols for channel estimation, to significantly reduce the processing time and computational complexity while maintaining the performance. These good properties seem quite suitable for a use of this proposed blind iterative algorithm for short-length packet FD transmissions in Internet-of-Things (IoT) applications and green communications.
Highlights
I N the era of 5G wireless communications, associated with Internet-of-Things (IoT) support, in order to enable many new devices to communicate and to be able to make autonomous decision by deploying diverse technologies and connecting massive devices [1]–[3]: two main services are targeting which are ultra-Reliable Low-Latency communications and massive Machine-Type Communications [4]
We investigate joint iterative channel estimation and decoding algorithms in FD transmissions in the digital domain via feedback of channel estimates and decoded messages combined with the process of Digital Self-Interference Cancellation (DSIC)
We further propose a partial feedback scheme which only use a partial number of modulated symbols in feedback loop for channel estimation processes and it can significantly reduce the processing time and computational complexity while maintaining the convergence performance; The remaining of this paper is organized as follows
Summary
I N the era of 5G wireless communications, associated with Internet-of-Things (IoT) support, in order to enable many new devices to communicate and to be able to make autonomous decision by deploying diverse technologies and connecting massive devices [1]–[3]: two main services are targeting which are ultra-Reliable Low-Latency communications (uRLLC) and massive Machine-Type Communications. We further propose a partial feedback scheme which only use a partial number of modulated symbols in feedback loop for channel estimation processes and it can significantly reduce the processing time and computational complexity while maintaining the convergence performance; The remaining of this paper is organized as follows. Notations KNRMEα hXY hXX v[k] v[n] v(t) vv ̃ ∗ λ i j dv dc Meaning Information length Code word length Code rate Modulation order Frame length after modulation Partial feedback coefficient Channel gain vector between X and Y Self-interference channel gain vector k-th bit of signal vector v in bit domain n-th symbols of signal vector v in discrete time domain Signal v in continuous time domain Estimation value of v Residual value of v Convolution operator Forget factor of RLS algorithm Index of joint iterative iterations Index of 5G QC-LDPC decoding iterations Average degree of the variable nodes Average degree of the check nodes
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