As a vital technology of the mine Internet of Things (MIoT), mine goaf sensor networks (MGSNs) have strong self-organization and invulnerability, which has the potential to realize the safety monitoring of the goaf. However, the adverse characteristics of MGSNs need to be addressed, such as time-varying wireless channels, serious signal attenuation, vulnerable network nodes, and limited nonrechargeable battery power. This article proposes a virtual-range-forwarding-based opportunistic routing (VFBOR) method for MGSNs. First, according to the actual environment of the goaf, the novel, appropriate deployment of low-cost routing nodes is designed among sensors to construct hierarchical, invulnerable self-organized MGSNs. Moreover, following the principles of opportunistic routing theory, VFBOR synthetically evaluates the distance between nodes with regard to the residual energy to select the appropriate routing nodes. In addition, VFBOR adopts a recovery mechanism to avoid the void region problem during the data packet forwarding process of nodes and improve the network connectivity. Finally, a realistic implementation plan is proposed. The simulation results confirm that VFBOR significantly outperforms some existing routing protocols, in terms of energy saving, wireless communication connectivity, and network throughput.

Polar codes, as the coding scheme for the control channel in fifth-generation mobile communication technology (5G), have attracted widespread attention since their proposal. As a mainstream decoding algorithm for polar codes, the successive cancellation list (SCL) decoder usually improves the error correction performance by increasing the list size, but this method suffers from the problems of high decoding complexity. To address this problem, this paper proposes a layered-search bit-flipping (LS-SCLF) decoding algorithm based on SCL decoding. Firstly, a new flip-bit metric is proposed, which derives a formula to approximate the probability of an error occurring in an information bit. This formula introduces a perturbation parameter to improve the calculation accuracy. Secondly, a compromise scheme for determining the perturbation parameter is proposed. The scheme uses Monte Carlo simulation to determine an optimized parameter for the precise positioning of the first erroneous decoded bit under different decoding conditions. Finally, a layered search strategy is adopted to sequentially search the erroneous decoded bits from the low order to high order, which can correct up to multiple bits at the same time. Simulation results show that the proposed algorithm achieves improved error correction performance with a slight increase in decoding complexity compared to the generalized SCL-Flip (GSCLF) decoding algorithm. This algorithm also achieves a good balance between the error correction performance and decoding complexity.

In the context of the high-speed development of 5G communications, high-performance decoding schemes for polar codes are a hot spot in channel coding research. Shift pruning successive cancellation list (SP-SCL) decoding aims to recover the correct path by shift pruning in the extra SCL decoding. However, the current SP-SCL decoding is inflexible in determining the shift positions. In this paper, a flexible shift pruning SCL (FSP-SCL) decoding is proposed. Firstly, the reasons for movement and the eliminated states of the correct path are analyzed in detail using the path metric range $\left(PMR\right)$, and on this basis, the validity of the method adopted in this paper for determining the shift priority of the information bits is verified. Secondly, the FSP-SCL decoding proposes two methods for determining the shift positions. One is the log-likelihood ratio (LLR) threshold method, which compares the LLR values of the eliminated paths on the shift bit with the corresponding LLR threshold to determine the shift positions. The other is the path distance method. It combines the minimum distance between the eliminated paths and the received vector with the path metrics to determine the shift positions. Both methods are more flexible and practical, as they can calculate the corresponding shift positions online based on a specific shift bit, avoiding the high complexity caused by the simulation method. Finally, this paper designs various experimental schemes to verify the decoding performance of the FSP-SCL. The experimental results show that in terms of error-correction performance, the LLR threshold-based FSP-SCL (FSPL (LLR threshold)) decoding, the path distance-based FSP-SCL (FSPL (path distance)) decoding and the existing SP-SCL decoding are roughly equal overall. In terms of decoding complexity, FSPL (LLR threshold) decoding is slightly better than FSPL (path distance) decoding, and the decoding complexity of both is lower than that of SP-SCL decoding, with the difference being more pronounced in the medium to high SNR regions.

Compute-and-forward (CoF) is a novel physical layer network coding scheme that allows the receiver to efficiently exploit interference in wireless communication. The key idea of CoF is to implement integer combinations based on the codewords from multiple transmitters, rather than decoding individual source codewords. Although CoF is widely used in wireless relay networks, there are still some problems to be solved, such as rank failure, single antenna reception, shortest vector problem. In this paper, we propose two novel approaches for multi-source, multi-relay, and multi-antenna wireless relay networks, called parallel extended CoF (PECoF) and successive extended CoF (SECoF). Firstly, we propose the PECoF based on parallel computation. The PECoF overcomes the rank failure problem by optimizing and extending the original CoF. Secondly, we design the SECoF method based on the PECoF framework and combines the concepts of matrix projection and successive interference cancellation, which overcomes the PECoF rate tend to zero and improves the network performance. In addition, we deduce the corresponding concise formulas of PECoF and SECoF, respectively. Simulation results show that the SECoF and PECoF have strong robustness, the approaches outperform the state-of-the-art methods in terms of computation rate, rank failure probability, and outage probability.