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Deep learning recently shows strong competitiveness to improve polar code decoding. However, suffering from prohibitive training and computation complexity, the conventional deep neural network (DNN) is only possible for very short code length. In this paper, the main problems of deep learning in decoding are well solved. We first present the multiple scaled belief propagation (BP) algorithm, aiming...
With the aid of a storage-release mechanism named key-keysmith, an implementation approach based on chemical reaction networks (CRNs) for synchronous sequential logic is proposed. This design approach, which stores logic information in keysmith and releases it through key, primarily focuses on the underlying state transitions behind the required logic rather than the electronic circuit representation...
Sparse-code multiple-access (SCMA) is a novel multiplexing method to increase the capacity of wireless communication systems. By giving users non-orthogonal codebook with few non-zero entries, the SCMA approach can highly improve the spectral efficiency, compared with traditional orthogonal ones such as CDMA, with tolerable detection complexity. Therefore, it has been considered as an option for 5G...
Advances in convolutional neural network (CNN) have aroused great interests all over the world. Despite the fact that the amount of convolutions in CNNs is proportional to that of layers, people tend to pursue more remarkable performance by exploiting a deep convolution neural network (DCNN), leading to large area occupation. With the deeper process involved in large-scale integrated circuits, circuit...
In this paper, belief propagation (BP) detection based on max-sum (MS) algorithm for massive multiple-input multiple-output (MIMO) systems is therefore proposed to reduce computational complexity of general belief propagation. Owing to employing the approximation strategy, complexity reduction of MS is at the expense of detection performance loss. Based on MS algorithm, two effective approaches are...
In this paper, an improved and low-complexity signal detection approach for large-scale multiple-input multiple-output (MIMO) systems has been proposed. This approach utilizes the preconditioning technique to accelerate the conventional detection algorithm based on Gauss-Seidel (GS) iterative method, and achieves a detection performance close to the minimum mean square error (MMSE) detection algorithm...
Nowadays, molecular computing and artificial intelligence have drawn intensive attentions from both academia and industry. Therefore, people begin to seek possible combination of these two promising areas. In this paper, with the aid of chemical reaction networks (CRNs), a design methodology of realizing the key block of fast convolution unit (FCU) in convolutional neural networks (CNNs) is proposed...
It is prevalently known that Markov chains have been successfully applied to many fields such as digital communications, queuing theory, and finance. However, when the system becomes massive and complex, the computational load will become too heavy to be handled by conventional approaches. To address this issue, molecular computation, which is inherently parallel, has been considered in this paper...
By adopting multiple-input multiple-output (MIMO) technique, the spectral efficiency and data rate of wireless communication systems can be highly improved. To fully take the advantages of MIMO, belief prorogation (BP) detection methods are considered as a way in balancing the hardware complexity and error performance. Also with BP methods, polar code, which has been adopted by 3GPP eMBB control channel,...
Low-density parity-check (LDPC) coded massive multiple-input and multiple-output (MIMO) scheme is getting increasingly popular and sophisticated in today's wireless communication systems, since it can highly improve the spectral efficiency, data rates, and error performance. In this paper, a novel iterative detection and decoding (IDD) method for LDPC-coded massive MIMO systems is proposed. Based...
In massive multiple-input multiple-output (MIMO) mobile system, the computational complexity of signal detection increases exponentially along with the growing number of antennas. For example, the sub-optimal linear detection schemes, such as zero forcing (ZF) detector and minimum mean square error (MMSE) detector, always have to balance the performance and complexity resulted from the large-scale...
In nowadays wireless communication systems, massive multiple-input multiple-output (MIMO) technique brings better energy efficiency and coverage but higher computational complexity than small-scale MIMO. For linear detection such as minimum mean square error (MMSE), prohibitive complexity lies in solving large-scale linear equations. For a better tradeoff between BER performance and computational...
Massive Multiple-Input Multiple-Output (MIMO) is one of the key technologies in the fifth generation (5G) wireless communication for much higher throughput. However, current detection algorithms for massive MIMO suffer from large computational complexity. The Neumann series based approximated matrix inverse is a good tradeoff between detection performance and computational complexity. In this paper,...
In this paper, a novel, low-complexity, and hardware efficient signal detection algorithm and its corresponding VLSI architecture are proposed for massive multiple-input multiple-output (MIMO) systems. This method is based on the parallel Gauss-Seidel (PGS) iterative method, and achieves comparable detection performance as the linear minimum mean-square error (MMSE) detection. It successfully avoids...
Recently, both polar codes and low-density parity-check (LDPC) codes have been adopted by 3GPP eMBB scenario. Since both codes exist in one system, it is natural to consider the concatenation scheme of them. In this paper, a merged belief propagation (BP) decoding algorithm for the concatenated codes of polar and LDPC codes is proposed. By jointing factor graphs, this merged algorithm is designed...
At present, China is the largest carbon emission country in the world. To adapt to the green new normal, solving the economic and environmental problem become a task of top priority. The paper calculates the carbon emission of China's iron and steel industry over the time period 1992–2012 by the IPCC empirical approach. We found that the carbon emissions increased rapidly during this time period,...
The natural language semantic corpus construction is the key step to implement information exchange in the intelligent cloud-computing environment. This paper makes a detailed analysis of semantic corpus construction technologies, and proposes a new webpage de-duplication algorithm based on TF-IDF and word vector distance. Experimental results show accuracy and efficiency of the proposed method. Our...
Path metric sorting unit of successive cancellation list (SCL) decoders for polar codes is the main concern in this paper. After reviewing existing sorting units in SCL decoders, we propose 2 new sorting schemes namely quick select (QS) based selection algorithm and simplified bitonic sorter (SBT), which exploit the special data dependency of path metrics in log-likelihood ratio based SCL decoding...
With better spectral efficiency, multiple-input and multiple-output (MIMO) systems have drawn increasing attentions. Due to its near-optimal performance, K-best algorithm has been widely adopted for MIMO detection. To the best knowledge of the authors, this paper first proposes a joint detection and decoding (JDD) method for MIMO with low-density parity-check (LDPC) codes. By pruning the searching...
To address the inherent limits of silicon-based technologies, the research on synthesizing various logic functions with chemical reaction networks (CRNs) has emerged in large numbers. However, in order to properly synthesize a given sequential logic, the difficulties lie in constructing a clock signal with an arbitrary duty cycle of M/N. Therefore, this paper is dedicated to putting forward a CRN-based...
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