Integrated sensing and communication (ISAC) technology enables simultaneous sensing and communication functions through shared hardware and resources tailored to specific applications. This technology reduces hardware costs and enhances system performance through synergistic interactions. While radio frequency-based ISAC (RF-ISAC) is well-studied, optical-based ISAC (O-ISAC) remains an emerging field. Compared with RF, light offers broader spectra, larger bandwidths, and flexible information transmission methods such as orbital angular momentum (OAM). Thus, O-ISAC research focuses on exploiting these unique optical advantages to significantly improve integrated system performance. This paper provides a comprehensive review of O-ISAC systems from three distinct perspectives: fundamental theory, system optimization design, and potential applications. By revisiting relevant optical theories and introducing novel insights, we propose a comprehensive theoretical framework grounded in light field theory to characterize and analyze the spatial distribution and propagation mechanisms of light. Leveraging this foundation, O-ISAC can be realized by coordinating multidimensional resources and harnessing light’s inherent structural properties. We then systematically examine critical performance metrics of integrated systems and propose an optimization framework that highlights essential technologies and corresponding evaluation criteria. Finally, the application of O-ISAC is illustrated with examples drawn from vehicular networks and hybrid optoelectronic base station architectures.

Intelligent Transport Systems (ITS) are crucial for safety, efficiency, and reduced congestion in transportation. They require efficient, secure, high-speed communication. Radio Frequency (RF) technologies like Fifth Generation (5G), Beyond 5G (B5G), and Sixth Generation (6G) are promising, but spectrum scarcity mandates coexistence with Optical Wireless Communication (OWC) networks, which offer high data rates and security, forming a strong foundation for hybrid RF/OWC applications in ITS. In this paper, we delve into the application of Machine Learning (ML) to enhance data communications within OWC systems in ITS. We commence by conducting an in-depth examination of the data communication prerequisites and the associated challenges within the ITS domain. Subsequently, we elucidate the compelling rationale behind the convergence of heterogeneous RF technologies with OWC for data communications in ITS scenarios. Our investigation then pivots towards elucidating the indispensable role played by ML in optimizing data communications via OWC within ITS. To provide a comprehensive perspective, we systematically evaluate and compare a spectrum of ML methodologies employed in OWC ITS data communications. As a culmination of our study, we proffer a set of valuable recommendations and illuminate promising avenues for future research endeavors that warrant further exploration within this critical intersection of ML, OWC, and ITS data communications.

Although Successive Interference Cancellation (SIC) decoding is widely adopted in Nonorthogonal Multiple Access (NOMA) schemes for the recovery of user data at acceptable complexity, the imperfect SIC would cause Error Propagation (EP), which can severely degrade system performance. In this work, we propose an SIC-free NOMA scheme in pulse modulation based Visible Light Communication (VLC) downlinks, including two types of users with different data rate requirements. Low bit-rate users adopt on-off keying, whereas high bit-rate ones use Multiple Pulse Position Modulation (MPPM). The soft decision decoding scheme is exploited by high bit-rate users to decode MPPM signals, which could fundamentally eliminate the detrimental effect of EP; the scheme is also easier and faster to execute compared with the conventional SIC decoding scheme. Expressions of the symbol error rate and achievable data rate for two types of users are derived. Results of the Monte Carlo simulation are provided to confirm the correctness of theoretical results.

Recently, the fifth-generation (5G) of wireless networks mainly focuses on the terrestrial applications. However, the well-developed emerging technologies in 5G are hardly applied to the maritime communications, resulting from the lack of communication infrastructure deployed on the vast ocean, as well as different characteristics of wireless propagation environment over the sea and maritime user distribution. To satisfy the expected plethora of broadband communications and multimedia applications on the ocean, a brand-new maritime information network with a comprehensive coverage capacity in terms of all-hour, all-weather, and all-sea-area has been expected as a revolutionary paradigm to extend the terrestrial capacity of enhanced broadband, massive access, ultra-reliable, and low-latency to the vast ocean. Further considering the limited available resource of maritime communication infrastructure, the convergence of broadband and broadcast/multicast can be regarded as a possible yet practical solution for realizing an efficient and flexible resource configuration with high quality of services. Moreover, according to such multi-functionality and all-coverage maritime information network, the monitoring and sensing of vast ocean area relying on massive Ocean of Things and advanced radar techniques can be also supported. Concerning these issues above, this study proposes a Software Defined Networking (SDN) based Maritime Giant Cellular Network (MagicNet) architecture for broadband and multimedia services. Based on this network, the convergence techniques of broadband and broadcast/multicast, and their supporting for maritime monitoring and marine sensing are also introduced and surveyed.

In fifth-generation wireless communication networks, Non-Orthogonal Multiple Access (NOMA) has attracted much attention in both academic and industrial fields because of its higher spectral efficiency in comparison with orthogonal multiple access. Recently, numerous uplink NOMA techniques have been proposed, some of which are based on Successive Interference Cancellation (SIC) and others on Joint Decoding (JD, or simultaneous decoding). In this study, we analyze the outage capacities of SIC and JD in the case of single-block transmission over a two-user Gaussian multiple-access channel with partial channel state information at transmitter from the perspective of information theory. Results of the analysis and numerals show that compared to SIC, JD can achieve a sum-rate gain of up to 10% or sum-power gain of 0.8 dB.

Traditional Amplitude Phase Shift Keying (APSK) consists of rings with points uniformly spaced. By giving up this uniform-spacing feature, we propose an APSK optimization method based on the uniform APSK with Gray labeling (Gray-APSK). The aim of the optimization is to maximize the Generalized Mutual Information (GMI) of Bit-Interleaved Coded Modulation (BICM) for the targeted code rate and channel. We show that our optimized non-uniform APSK could offer further performance gain compared with the conventional uniform Gray-APSK and considerably outperforms the traditional quadrature amplitude modulation at the targeted SNR and channel.