Orthogonal time frequency space (OTFS) modulation is a two-dimensional (2-D) modulation technique that has the potential to overcome the challenges faced by orthogonal frequency division multiplexing (OFDM) in high Doppler environments. The performance of OTFS in a multi-user scenario with orthogonal multiple access (OMA) techniques has been impressive. Due to the requirement of massive connectivity in 5G and beyond, it is essential to devise and examine the OTFS system with the existing non-orthogonal multiple access (NOMA) techniques. This paper proposes a multi-user OTFS system based on a code-domain NOMA technique called sparse code multiple access (SCMA). This system is referred to as the OTFS-SCMA model. The framework for OTFS-SCMA is designed for both downlink and uplink. First, the sparse SCMA codewords are strategically placed on the delay-Doppler plane. The overall overloading factor of the OTFS-SCMA system is equal to that of the underlying basic SCMA system. The receiver in downlink performs the detection in two sequential phases: first, the conventional OTFS detection using the method of linear minimum mean square error (LMMSE) estimation, and then the SCMA detection. We propose a single-phase detector based on a message-passing algorithm (MPA) to detect multiple users’ symbols for the uplink. The expressions for the asymptotic diversity orders of the proposed OTFS-SCMA system are derived for downlink and uplink. OTFS-SCMA provides a significant diversity gain over other multiple access systems for OTFS. Based on the diversity analysis, an algorithm is proposed to devise an optimal codeword allocation scheme. The performance of the proposed OTFS-SCMA system is validated through extensive simulations both in downlink and uplink. We consider delay-Doppler planes of different parameters and various SCMA systems of overloading factor up to 200%. The performance of OTFS-SCMA is compared with those of the existing OTFS-OMA, OFDM-SCMA and OTFS-power-domain (PD)-NOMA techniques. The analysis of OTFS-SCMA with channel estimation is also presented along with the BER performance.

Intelligent reflecting surface (IRS) is a recent technology garnering lots of attention amongst the wireless communication research community due to its ability to improve the channel conditions extravagantly. The main feature of IRS technology is its capability to tune the phases of the reflecting elements to trigger a cohesive amalgamation of various multipath. IRS can easily co-exist with almost all technologies, thereby offering flexibility to the designers to come up with attractive systems. Further, orthogonal time frequency space (OTFS) is a recent 2D modulation technique that can mitigate the drawbacks of the traditional orthogonal frequency division multiplexing (OFDM) for fifth generation (5G) and beyond networks, especially in high Doppler wireless environments like vehicle-to-everything (V2X) and millimeter wave (mmWave) communications. This paper presents the system architecture of the IRS-assisted OTFS scheme in the delay-Doppler (DD) domain, including the modulation, demodulation, and detection methods. The selection of the reflection coefficients play the most vital role in the IRS-OTFS system, like any IRS system. IRS reflection optimization cannot perfectly line up all multipath with the same phase in the frequency-selective channels. We adopt an IRS phase optimization method where only the strongest delay-Doppler path is phase-aligned, while the paths with lesser strengths will be out of phase with the direct path. This reconfigurability of IRS elements enhances the OTFS modulation scheme, thereby significantly mitigating the multipath fading effects in high Doppler channels. Additionally, we propose a channel estimation for the IRS-OTFS system where both data and pilots are embedded in the same OTFS frame with minimal guard-band overhead. The paper presents extensive simulation results on the error-rate performance of the proposed system over Rayleigh and Rician fading channels. The effects of the number of IRS elements, the phase selections, and the channel estimation method on the system's performance are investigated. The comprehensive simulation study demonstrates that by exploiting the features of both OTFS and IRS, the proposed approach can provide impressive performance in high Doppler environments.

In this letter, we propose a joint power and codedomain non-orthogonal multiple access (NOMA) technique for the fifth generation (5G) wireless networks and beyond. We consider a downlink system, where the users experience diverse channel conditions. The transmitter involves sparse code multiple access (SCMA) encoder and allows diversity in power allocation to the users. The detection is based on combined message-passing and successive-interference-cancellation algorithms. Simulation results demonstrate that the proposed NOMA system achieves higher spectral efficiency than the conventional single power domain NOMA and SCMA-based systems.

Orthogonal time frequency space (OTFS) has emerged as the most sought-after modulation technique in a high mobility scenario. Sparse code multiple access (SCMA) is an attractive code-domain non-orthogonal multiple access (NOMA) technique. Recently a code-domain NOMA approach for OTFS, named OTFS-SCMA, is proposed. OTFS-SCMA is a promising framework that meets the demands of high mobility and massive connectivity. This paper presents a channel estimation technique based on the convolutional sparse coding (CSC) approach for OTFS-SCMA in the uplink. The channel estimation task is formulated as a CSC problem following a careful rearrangement of the OTFS input-output relation. We use an embedded pilot-aided sparse-pilot structure that enjoys the features of both OTFS and SCMA. The existing channel estimation techniques for OTFS in multi-user scenarios for uplink demand extremely high overhead for pilot and guard symbols, proportional to the number of users. The proposed method maintains a minimal overhead equivalent to a single user without compromising on the estimation error. The results show that the proposed channel estimation algorithm is very efficient in bit error rate (BER), normalized mean square error (NMSE), and spectral efficiency (SE).

The integration of multiple-input multiple-output (MIMO) technology with reconfigurable intelligent surfaces (RIS) in Terahertz (THz) communication systems has emerged as a promising approach to address the challenges and exploit the opportunities in next-generation wireless networks. This technical reviewprovides a systematic state-of-the-art research and developments toward MIMO-based RIS-supported THz communication, systems focus on the potential research opportunities, challenges, and emerging applications of this innovative technology. Further, this paper explores the combined benefits of integrating MIMO with RIS to improve link reliability, along with the associated system-level design challenges. Furthermore, we discuss various aspects of MIMO-based RIS-supported THz communication, such as channel modeling, channel estimation, beamforming techniques, beam split effect resource allocation strategies, and performance evaluation metrics. Moreover, the role of artificial intelligence and machine learning (AI/ML) in the design of RIS-empowered THz wireless communication systems is also discussed.

In a device-to-device communication scenario, the number of far users (FUs) is higher than the near users (NUs) in each cluster. In such a scenario, the paired NUs and FUs communicate through non-orthogonal multiple access (NOMA), and the remaining FUs communicate through orthogonal multiple accesses (OMA) schemes. This system is called as hybrid-NOMA (HNOMA). This paper proposes a reconfigurable intelligent surface (RIS)-assisted HNOMA system to enhance the energy and spectral efficiencies of the conventional HNOMA. In this proposed RIS-assisted HNOMA (PR-HNOMA) system, the NU is paired with multiple FUs with allocations of different bandwidths. The PR-HNOMA system’s sum rate is maximized by considering joint beamforming at BS and RIS via semidefinite relaxation (SDR) and alternatively optimization (AO) techniques. Further, the sum rate of the PR-HNOMA under imperfect successive interference cancellation (ISIC) is analyzed and compared with different NOMA and OMA schemes. Simulation results show that the PR-HNOMA achieves better sum-rate performance than the conventional RIS assisted HNOMA (R-HNOMA), and RIS assisted NOMA (R-CNOMA), and OMA (R-OMA).