LT Codes with Double Encoding Matrix Reorder Physical Layer Secure Transmission

In traditional wireless sensor networks, information transmission usually uses data encryption methods to prevent information from being stolen illegally. However, once the encryption methods are leaked, eavesdropping nodes can easily obtain information. LT codes are rateless codes; if it is attacked by random channel noise, the decoding process will change and the decoding overhead will also randomly change. When it is used for physical layer communication of wireless sensor networks, it ensures that the destination node recovers all the information without adding the key, while the eavesdropping node can only obtain part of the information to achieve wireless information security transmission. To reduce the intercept efficiency of eavesdropping nodes, a physical layer security (PLS) method of LT codes with double encoding matrix reorder (DEMR-LT codes) is proposed. This method performs two consecutive LT code concatenated encoding on the source symbol, and part of the encoding matrix is reordered according to the degree value of each column from large to small, which reduces the probability of eavesdropping nodes recovering the source information. Experimental results show that compared with other LT code PLS schemes, DEMR-LT codes only increase the decoding overhead by a small amount. However, it can effectively reduce the intercept efficiency of eavesdropping nodes and improve information transmission security.

Memory-Based LT Codes for Efficient 5G Networks and Beyond

The next-generation networks (5G and beyond) require robust channel codes to support their high specifications, such as low latency, low complexity, significant coding gain, and flexibility. In this paper, we propose using a fountain code as a promising solution to 5G and 6G networks, and then we propose using a modified version of the fountain codes (Luby transform codes) over a network topology (Y-network) that is relevant in the context of the 5G networks. In such a network, the user can be connected to two different cells at the same time. In addition, the paper presents the necessary techniques for analyzing the system and shows that the proposed scheme enhances the system performance in terms of decoding success probability, error probability, and code rate (or overhead). Furthermore, the analyses in this paper allow us to quantify the trade-off between overhead, on the one hand, and the decoding success probability and error probability, on the other hand. Finally, based on the analytical approach and numerical results, our simulation results demonstrate that the proposed scheme achieves better performance than the regular LT codes and the other schemes in the literature.

Distributed Arithmetic Coding Over Binary Erasure Channel

In this paper, the Binary Erasure Channel (BEC) is researched by Distributed Arithmetic Coding (DAC) based on Slepian-Wolf coding framework. The source and side information are modelled as a virtual BEC. The DAC decoder uses maximum a posteriori (MAP) as the criterion to recover the source. A deep residual network is used to boost the DAC decoding process. The experimental results show that our algorithm nearly achieves the same performance with LT codes under different erasure probabilities.

Performance and Time Improvement of LT Codes-based Cloud Storage

Outsourcing data on the cloud storage services has already attracted great attention due to prospect of rapid data growth and storing efficiencies for customers. The coding-based cloud storage approach can offer more reliable and faster solution with less storage space in comparison with replication-based cloud storage. LT codes as a famous member of rateless codes family can improve performance of storage systems utilizing good degree distributions. Since degree distribution plays key role in LT codes performance, recently introduced Poisson Robust Soliton Distribution (PRSD) and Combined Poisson Robust Soliton Distribution (CPRSD) motivate us to investigate LT codes-based cloud storage system. So, we exploit LT codes with new degree distributions in order to provide lower average degree and higher decoding efficiency, specifically when receiving fewer encoding symbols, comparing with popular degree distribution, Robust Soliton Distribution (RSD). In this paper, we show that proposed cloud storage outperforms traditional ones in terms of storage space and robustness encountering unavailability of encoding symbols, due to compatible properties of PRSD and CPRSD with cloud storage essence. Furthermore, modified decoding process based on required encoding symbols behavior is presented to reduce data retrieval time. Numerical results confirm improvement of cloud storage performance.

A Novel LT Scheme without Feedback Messages for IoT of Smart City Scenarios

For IoTs of smart city scenarios always with the low cost, low power consumption, and high transmission delay properties, the traditional protocols based on feedback messages, e.g., the Automatic Repeat reQuest (ARQ) schemes, would dramatically affect the transmission efficiency. Therefore, the LT codes with only one feedback message in each entire coding process can be used to substitute the traditional protocols. As in many IoTs of smart city scenarios, the data must have both high transmission efficiency and timeliness requirements; thus, the negative effect of only the feedback message in each entire coding process cannot be neglected in such transmission environments. To enhance the transmission efficiency of such ensembles, a novel LT scheme without feedback messages is proposed in this paper. By presenting the definitions of optimal decoding overhead and recovery ratio per symbol, the optimal decoding overhead of LT codes can be found directly, then the encoding overhead of the encoder can be predesigned also. For this reason, the feedback messages in LT schemes can be removed. By using the proposed LT scheme, the transmission efficiency of IoT of smart city scenarios can be enhanced.