In this paper, a differential scheme is proposed for reconfigurable intelligent surface (RIS) assisted spatial modulation, which is referred to as RIS-DSM, to eliminate the need for channel state information (CSI) at the receiver. The proposed scheme is an improvement over the current differential modulation scheme used in RIS-based systems, as it avoids the high-order matrix calculation and improves the spectral efficiency. A mathematical framework is developed to determine the theoretical average bit error probability (ABEP) of the system using RIS-DSM. The detection complexity of the proposed RIS-DSM scheme is extremely low through the simplification. Finally, simulations results demonstrate that the proposed RIS-DSM scheme can deliver satisfactory error performance even in low signal-to-noise ratio environments.

Reconfigurable intelligent surface (RIS) assisted dual-function radar communications (DFRC) system is a promising integrated sensing and communication (ISAC) technology for future 6G. In this paper, we propose a scheme of RIS-assisted DFRC system based on frequency shifted chirp spread spectrum index modulation (RDFI) for secure communications. The proposed RDFI achieves the sensing and transmission of target location information in its radar and communication modes, respectively. In both modes, the frequency-shifted chirp spread spectrum index modulation (FSCSS-IM) signal is used as the baseband signal for radar and communications, so that the signal sent by the radar also carries information. This scheme implements the RIS-assisted beamforming in the communication mode through the azimuth information of the target acquired in the radar mode, so that the signal received from the eavesdropper is distorted in amplitude and phase. In addition, this paper analyzes the radar measurement accuracy and communication security of the FSCSS-IM signal using ambiguity function and secrecy rate (SR) analysis, respectively. Simulation results show that RDFI achieves both excellent bit error rate (BER) performance and physical layer security of communications.

Orthogonal time frequency space (OTFS) technique, which modulates data symbols in the delay-Doppler (DD) domain, presents a potential solution for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing (UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model (HMM). The empirical state evolution (SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm, we derive the update criterion for the hyperparameters through the expectation-maximization (EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.

Modulation recognition becomes unreliable at low signal-to-noise ratio (SNR) over fading channel. A novel method is proposed to recognize the digital modulated signals with frequency and phase offsets over multi-path fading channels in this paper. This method can overcome the effects of phase offset, Gaussian noise and multi-path fading. To achieve this, firstly, the characteristic parameters search is constructed based on the cyclostationarity of received signals, to overcome the phase offset, Gaussian white noise, and influence caused by multi-path fading. Then, the carrier frequency of the received signal is estimated, and the maximum characteristic parameter is searched around the integer multiple carriers and their vicinities. Finally, the modulation types of the received signal with frequency and phase offsets are classified using decision thresholds. Simulation results demonstrate that the performance of the proposed method is better than the traditional methods when SNR is over 5dB, and that the proposed method is robust to frequency and phase offsets over multi-path channels.

In this paper, a powerful model-driven deep learning framework is exploited to overcome the challenge of multi-domain signal detection in space-domain index modulation (SDIM) based multiple input multiple output (MIMO) systems. Specifically, we use orthogonal approximate message passing (OAMP) technique to develop OAMPNet, which is a novel signal recovery mechanism in the field of compressed sensing that effectively uses the sparse property from the training SDIM samples. For OAMPNet, the prior probability of the transmit signal has a significant impact on the obtainable performance. For this reason, in our design, we first derive the prior probability of transmitting signals on each antenna for SDIM-MIMO systems, which is different from the conventional massive MIMO systems. Then, for massive MIMO scenarios, we propose two novel algorithms to avoid pre-storing all active antenna combinations, thus considerably improving the memory efficiency and reducing the related overhead. Our simulation results show that the proposed framework outperforms the conventional optimization-driven based detection algorithms and has strong robustness under different antenna scales.

Reconfigurable intelligent surface (RIS)-assisted symbiotic radio is a spectrum- and energy- efficient communication paradigm, in which an RIS performs passive beamforming to enhance active transmission, while using the electromagnetic waves from the active transmission for additional information transfer (i.e., passive transmission). In this paper, a hybrid RIS-based modulation, termed hybrid phase and code modulation (HPCM), is proposed to improve the reliability of RIS-assisted symbiotic radio. In RIS-HPCM, the RIS simultaneously performs direct sequence spread spectrum and passive beamforming on incident signals. Moreover, both the spreading code and phase offset are exploited to carry the RIS's own information. A low-complexity detector is designed, in which the receiver first detects the spreading codes and then demodulates the constellation symbols. We analyze the bit error rate (BER) performance of RIS-HPCM over Rician fading channels. BER upper bounds and approximate BER expressions are derived in closed-form for maximum-likelihood and low-complexity detectors, respectively. Simulation results in terms of BER verify the analysis and show the superiority of RIS-HPCM over the existing RIS-based modulation.

To provide reliability in distributed systems, combination property (CP) is desired, where $k$ original packets are encoded into $n \geq k$ packets and arbitrary $k$ are sufficient to reconstruct all the original packets. Shift-and-add (SA) encoding combined with zigzag decoding (ZD) obtains the CP-ZD, which is promising to reap low computational complexity in the encoding/decoding process of these systems. As densely coded modulation is difficult to achieve CP-ZD, research attentions are paid to sparse coded modulation. The drawback of existing sparse CP-ZD coded modulation lies in high overhead, especially in widely deployed setting $m<k$, where $m \triangleq n-k$. For this scenario, namely, $m<k$, a sparse reverse-order shift (Rev-Shift) CP-ZD coded modulation is designed. The proof that Rev-Shift possesses CP-ZD is provided. A lower bound for the overhead, as far as we know is the first for sparse CP-ZD coded modulation, is derived. The bound is found tight in certain scenarios, which shows the code optimality. Extensive numerical studies show that compared to existing sparse CP-ZD coded modulation, the overhead of Rev-Shift reduces significantly, and the derived lower bound is tight when $k$ or $m$ approaches 0.

This paper proposes a high-throughput short reference differential chaos shift keying cooperative communication system with the aid of code index modulation, referred to as CIM-SR-DCSK-CC system. In the proposed CIM-SR-DCSK-CC system, the source transmits information bits to both the relay and destination in the first time slot, while the relay not only forwards the source information bits but also sends new information bits to the destination in the second time slot. To be specific, the relay employs an $N$-order Walsh code to carry additional ${{\log }_{2}}N$ information bits, which are superimposed onto the SR-DCSK signal carrying the decoded source information bits. Subsequently, the superimposed signal carrying both the source and relay information bits is transmitted to the destination. Moreover, the theoretical bit error rate (BER) expressions of the proposed CIM-SR-DCSK-CC system are derived over additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. Compared with the conventional DCSK-CC system and SR-DCSK-CC system, the proposed CIM-SR-DCSK-CC system can significantly improve the throughput without deteriorating any BER performance. As a consequence, the proposed system is very promising for the applications of the 6G-enabled low-power and high-rate communication.