In secret key generation of physical layer security technology, it is challenging to achieve high key capacity and low secret key inconsistency rate. This paper investigates intelligent reflecting surface (IRS) assisted secret key generation, which aims to maximize the secret key capacity by adjusting the placement of the IRS units. Specifically, we first analyze and deduce the key capacity expression of the IRS-assisted system from the perspective of information theory. Then we investigate how to use the channel state information (CSI) to place the IRS units effectively so as to maximize the secret key capacity. Simulation results show that our scheme could improve the quality of secret key generation significantly.

Integrating sparse code multiple access (SCMA) and mobile edge computing (MEC) into the Internet of Things (IoT) networks can enable efficient connectivity and timely computation for resource-limited IoT users. This paper studies the computation rate maximization problem under task deadline constraints in dynamic SCMA-MEC networks. Specifically, we propose a predictive deep Q-network for SCMA resource allocation and computation offloading (PQ-RACO) algorithm for single-cell scenarios, where IoT devices use long short-term memory (LSTM) networks to predict the states and actions of other agents. However, the PQ-RACO algorithm is not scalable for increasing numbers of IoT devices. To address this issue, an improved multi-agent deep Q-network for SCMA resource allocation and computation offloading algorithm (MQ-RACO) is proposed for multi-cell scenarios. The algorithm is a centralized training and decentralized execution (CTDE) multi-agent reinforcement learning (MARL) algorithm with explicit rewards, which is tailored to the special structure of joint rewards. Simulation results demonstrate that the proposed algorithm outperforms several state-of-the-art MARL algorithms and other benchmark schemes in terms of convergence speed and computation rate.

Multiple-input multiple-output (MIMO) and sparse code multiple access (SCMA) are two effective techniques supporting high spectral efficiency and massive connectivity, respectively. Although the combination of these two techniques, namely MIMO-SCMA, can further improve the spectral efficiency, it deteriorates the error performance and greatly increases the computational costs. In this letter, in order to enhance the error performance and reduce the receiver complexity of the uplink MIMO-SCMA system, we propose a new scheme named spatial modulation sparse code multiple access (SM-SCMA). At the receiver, a low complexity joint message passing algorithm based on the principle of the maximum a posterior probability and the simplified factor graph is proposed. Simulation results show that the SM-SCMA can achieve a better bit-error-rate performance while significantly reducing the receiver complexity compared with the conventional MIMO-SCMA.

SCMA and polar coding are possible candidates for 5G systems. In this paper, we firstly propose the joint iterative detection and decoding (JIDD) receiver for the uplink polar coded sparse code multiple access (PC-SCMA) system. Then, the EXIT chart is used to investigate the performance of the JIDD receiver. Additionally, we optimize the system design and polar code construction based on the EXIT chart analysis. The proposed receiver integrates the factor graph of SCMA detector and polar soft-output decoder into a joint factor graph, which enables the exchange of messages between SCMA detector and polar decoder iteratively. Simulation results demonstrate that the JIDD receiver has better BER performance and lower complexity than the separate scheme. Specifically, when polar code length $N=256$ and code rate $R = 1/2$ , JIDD outperforms the separate scheme 4.8 and 6 dB over AWGN channel and Rayleigh fading channel, respectively. It also shows that, under 150% system loading, the JIDD receiver only has 0.3 dB performance loss compared to the single user uplink PC-SCMA over AWGN channel and 0.6 dB performance loss over Rayleigh fading channel.

Researches on 5th generation mobile communication networks (5G) are emerging to meet the demands of rapidly developing communications applications. The reliability and security of data have become key factors of its development, and thus 5G has put forward higher requirements for new coding and encryption technologies. In this paper, a physical layer encryption algorithm based on polarization codes and chaotic sequences is proposed to improve the reliability and confidentiality of transmission. In our scheme, chaotic sequences are allocated in the frozen bits of polar codes. Therefore, error correction and encryption can be performed simultaneously. Since the frozen bits are unknown to the eavesdroppers, it is difficult for them to decode the transmitted bits without the knowledge of the chaotic sequences. To further improve the security, we propose to generate the chaotic sequences by using the channel state information. Besides, the chain effects of delayed feedback are applied to increase the decrypted complexity of the eavesdroppers in this paper. Theoretic analysis and simulation results both show that the proposed algorithms can achieve high security without any error rate performance loss.

To defend against eavesdropping and spoofing attacks, the physical layer authentication (PLA) techniques utilize the unique attributes of channel or device for identifying attackers. Among these techniques, the PLA schemes based on channel phase responses use the secret key driven channel phase to authenticate the legitimate user, which have a better performance than the channel amplitude based schemes. However, the prior phase-based schemes only consider the perfect channel correlation coefficient between the two successive timeslots, which differs from the real scenarios. Meanwhile, the closed-form expressions of the theoretical analysis results are not comprehensive in the prior schemes, which are also not tight especially at low signal-to-noise ratio (SNR) regions. In this paper, we propose a PLA scheme based on the channel phase response, aiming to offset the performance loss introduced by the channel correlation coefficient. Moreover, we derive the closed-form expressions of the theoretical analysis results, such as the mean value, the variance and the probability density functions (PDFs), which can be utilized to provide the closed-form threshold for making decision instead of a great ideal of testing. Then, the security analysis is provided to verify the resistance of the proposed scheme under the attacks. Simulation results show that the proposed scheme outperforms the benchmarks and the proposed theoretical results match well with the simulated results even under low SNR regions.