sparse vector coding (SVC) is a promising transmission scheme in ultra-reliable and low-latency communications (URLLC) scenario. Its transmission performance primarily depends on the sparsevector construction, namely...
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sparse vector coding (SVC) is a promising transmission scheme in ultra-reliable and low-latency communications (URLLC) scenario. Its transmission performance primarily depends on the sparsevector construction, namely sparse mapping. In this letter, we first demonstrate the relationship between combination-based and index redefinition (IR)-based sparse mapping of SVC, from which we conclude that the latter has obtained the shortest sparsevectors with the aid of multiple constellation allocation. There is a trade-off between sparsevector length and the number of allocated constellations to construct an SVC scheme with the optimal performance. Based on this, we propose a pairwise grouping-based SVC (PG-SVC) scheme by grouping multiple constellations in pairs to reduce the number of allocated constellations, in which the constellation allocation is determined by specific transmitted bits. This approach ensures sparsevectors of moderate length, as the number of bits determining the sparsevector length is reduced. Simulation results show that the PG-SVC scheme can achieve higher transmission reliability compared to the existing SVC schemes, especially when coding efficiency is high.
sparse superposed code (SSC) is one of the most promising techniques to support the ultra-reliable and low-latency communication (URLLC). Compared with the conventional sparsevector code (SVC), quadrature amplitude m...
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sparse superposed code (SSC) is one of the most promising techniques to support the ultra-reliable and low-latency communication (URLLC). Compared with the conventional sparsevector code (SVC), quadrature amplitude modulation (QAM) symbols are exploited to carry information bits in SSC. By such an approach, the dimension of the codebook in SSC can be significantly reduced, which results in a lower block error rate (BLER) of the multi-path matching pursuit (MMP)-based decoder. In similar spirit, a multiple-mode SSC (MSSC) is proposed to further reduce BLER. On the encoding side, the information bits are divided into three parts. The first two parts are the same as traditional SSC, while the remaining information bits are mapped as the permutation of the constellation alphabets. On the decoding side, an enhanced MMP-based decoder is developed, where the extra constellation alphabet permutation detection is realized. Simulation results reveal that the proposed MSSC outperforms the conventional SSC significantly.
A sparse superimposed vector transmission (SSVT) scheme is proposed for short-packet ultra-reliable and low-latency communications (URLLC) in high-mobility scenarios. Unlike conventional pilot-less sparsevector codin...
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A sparse superimposed vector transmission (SSVT) scheme is proposed for short-packet ultra-reliable and low-latency communications (URLLC) in high-mobility scenarios. Unlike conventional pilot-less sparse vector coding (SVC) schemes, a small number of pilots are superimposed on top of data vector in SSVT to track time-varying channels, leading to high spectral efficiency. Two joint channel estimation and data decoding algorithms, called iterative interference cancellation (IIC) and iterative data-aided (IDA), are proposed to recover data from the received signal. The IIC algorithm accurately decodes data by iteratively canceling pilot and data interference, while the IDA algorithm further refines channel estimation by treating previously decoded data as pseudo-pilots. Simulation results show that the proposed SSVT scheme significantly outperforms conventional SVC schemes in terms of block error rate (BLER), and the proposed IIC and IDA algorithms show fast convergence speed.
Ultra-reliable and low-latency communications (URLLC) partake a major role in future communication systems. A possible strong candidate for future URLLC networks is sparse vector coding (SVC), which enables a superior...
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ISBN:
(纸本)9781728172064
Ultra-reliable and low-latency communications (URLLC) partake a major role in future communication systems. A possible strong candidate for future URLLC networks is sparse vector coding (SVC), which enables a superior performance in terms of bit error rate (BER). In SVC, virtual digital domain (VDD) and compressed sensing (CS) algorithms are used to encode and decode information. In this paper, orthogonal frequency division multiplexing (OFDM)-based a novel system called orthogonal frequency division multiplexing with codebook index modulation (OFDM-CIM) and which can meet the needs of URLLC systems has been proposed. In OFDM-CIM, information bits are transmitted via both active subcarrier indices and codebook indices. As a result of computer simulations, OFDM-CIM is presented as a strong candidate for next generation communication systems.
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