Combining semi-grant-free (SGF) transmission with non-orthogonal multiple access transmission (NOMA) allows grant-free (GF) UEs to access the network through resource blocks that are solely allocated to grant-based (GB) UEs. A channel gain constraint for GF UEs is introduced to reduce the interference impact to GB UE, which causes an access fairness problems for GF UEs. Moreover, the power collision (PC) interference significantly degrades the interference cancellation performance. To address these issues, this paper proposes a layer SGF-NOMA random access (RA) procedure and a joint power back-off (PB) scheme. In the proposed RA procedure, GF UEs can freely share the GB UE’s resource blocks without channel gain constraints. To suppress the PC interference, the proposed PB scheme optimizes the power distribution in the NOMA group according to the variable interference experienced by the NOMA UEs. To maintain the signal-to-interference balance, more power is transferred to the UEs that suffer more interference. The closed-form expressions of the outage probability, successful access probability and sum data rate are derived via order statistic theory. Both the analytical and simulation results demonstrate that the layer SGF-NOMA procedure and joint PB scheme achieves significant performance gains over traditional schemes.

With the capability to configure wireless propagation environment, reconfigurable intelligent surface (RIS) has attracted wide attention from both academia and industry, in which measurement campaign of RIS in commercial networks is of great importance for performance evaluation. However, existing RIS configuration schemes in practical environments are generally angle-based which require accurate angle information and mainly consider single incident beam, or statistical methods with high sampling overhead. In this paper, we propose a phase shift design scheme for RIS referred to as multiple incident beam superposition (MIBS) scheme, which can be applied in scenarios with incident signals on the RIS from multiple directions. Instead of utilizing random sampling, the proposed scheme firstly employs an incident beam scanning process to extract the incident beam information by pre-calculated codebook to reduce sampling cost, and requires no complex channel estimation or prior channel information. Then the proposed scheme concentrates the incident beams toward the desired reflection direction through a phase shift superposition algorithm. Numerical simulations verify the excellent performance and a 90% sample reduction of the proposed scheme compared with existing methods under the condition of 1-bit RIS hardware for practical applications. Furthermore, a measurement campaign in 5G commercial networks is conducted to validate the advantages of the proposed MIBS scheme in optimizing crucial signal metrics, yielding a 6.76 dB RSRP gain, a 4.9 dB SINR gain and a 37% throughput improvement, showing great potential of RIS for coverage enhancement.

The multi-base-station cooperative (MBC) ISAC mechanism is promising to satisfy the higher-quality sensing requirements of accuracy and coverage in 6G. STAR-RIS can help ISAC BSs provide cooperative sensing and communication (S&C) across full-space radio signal coverage. Short-packet transmission (SPT) is expected to be performed by ISAC BSs in 6G vertical applications to provide enhanced ultra-reliable low-latency S&C services. This paper proposes a STAR-RIS-assisted heterogeneous (SRH) MBC ISAC mechanism within the finite blocklength (FBL) regime. Multiple ISAC BSs and a communication-only (Comm-only) BS collaborate to provide S&C services to users and the target using STAR-RISs and cooperative detection results. A composite SPT (C-SPT) time frame structure is proposed by dynamically designing the S&C block lengths from the perspectives of the sub-frame and the entire transmission block. The systemic sum achievable capacity (SAC) over the entire transmission block is maximized by jointly optimizing the pilot and data block lengths and powers, as well as the active and passive beamforming of ISAC BSs and STAR-RISs under constraints of temporal, spatial, and power resources. The non-convex optimization problem is solved by combining the methods of alternating optimization (AO), quadratic transform (QT), sequential rotation (SR), and particle swarm optimization (PSO). Simulation results demonstrate the superiority of the proposed SRH-MBC ISAC mechanism with the C-SPT frame structure in achieving higher systemic communication performance with the assistance of STAR-RIS.

Reconfigurable intelligent surface (RIS) is a promising technology for 6G wireless communication. To learn from former successful deployed technique, a mature and widely deployed solution in 5G networks, the repeater, is a subject worth comparing. This paper presents a comparative study of RIS and commercial repeater through field trials in a typical indoor parking lot scenario. By providing empirical insights rather than algorithmic contributions, the study focuses on assessing their performance in terms of coverage, signal quality, and deployment characteristics. Field trials were conducted to measure key metrics such as reference signal received power (RSRP) and signal-to-interference-plus-noise ratio (SINR) under both point and area coverage scenarios. The results reveal that RIS achieves localized coverage improvements with enhanced signal reflection, whereas repeater excels in wide-area coverage through cascaded digital remote units (DRUs). The findings highlight the distinct advantages and limitations of each technology, providing practical insights for their deployment in indoor environments.

Unsourced multiple access (UMA) is a promising technology for the sixth generation (6G) mobile networks to fulfil the requirements of massive random access or massive small data transmission. However, the performance evaluation of UMA for non-orthogonal data transmission with real user active detection and real channel estimation is not thoroughly considered for fading channels. In this paper realistic user active detection and realistic channel estimation is carried out for unsourced sparse multiple access (USMA) scheme where sparse interleaver division multiple access is employed. The estimated channels of active users from preamble part are applied for multi-user signal detection for data transmission part. It is found that the multi-user detection performance loss of USMA compared to the ideal channel estimation is marginal in both additive white Gaussian noise (AWGN) channel and flat fading channel under the reasonable system parameter setting.

Integrated sensing and communication (ISAC) has been identified as a potential key 6G technology that empowers cellular systems with wireless sensing capabilities. It is challenging for an individual ISAC node to meet the increased sensing demands of 6G Internet of Everything (IoE) applications, such as larger coverage and higher accuracy. To address this issue, multinode cooperative ISAC (MNC-ISAC) schemes have recently been explored to improve sensing performances for 6G IoE applications. This article innovatively proposes a distributed MNC-ISAC (DMNC-ISAC) scheme, which differs from the conventional centralized MNC-ISAC (CMNC-ISAC) scheme where all cooperative ISAC nodes form a single sensing coalition. In the proposed DMNC-ISAC scheme, multiple ISAC nodes form a satisfied number of cooperative groups by coordinating their sensing abilities and resources in a distributed way. The interactions between multiple ISAC nodes, characterized by collaboration in sensing and competition for resources, are modeled as a local cooperation-based game. Then, to maximize the overall sensing and communication (S&C) performance of the proposed DMNC-ISAC scheme, the cooperation grouping and transmission beamforming of multiple ISAC nodes are jointly optimized. The stochastic learning automata (SLA) and particle swarm optimization algorithms are utilized to obtain the equilibrium grouping results and design the beamforming of multiple ISAC nodes. Finally, simulation results show that the distributed cooperative ISAC scheme enhances sensing performance by at least 5%, leading to improved systemic performance in most ISAC scenarios. This improvement is particularly notable in challenging sensing environments and when the possible status of the target is ambiguous.

The forthcoming sixth-generation (6G) wireless system brings forth the need to meet increasingly stringent performance criteria, necessitating refinement and advanced design of channel coding and modulation techniques. Within this context, polar codes stand out as a competitive candidate due to their favorable attributes. This study delves into probabilistically-shaped polar-coded modulation (PS-PCM) for its potential to enhance spectral efficiency and error-correction performance, offering a pragmatic design geared toward standardization. Specifically, we present a coding chain for PS-PCM that ensures backward compatibility with legacy 5G polar codes. We also propose, for the first time, a channel-independent method for constructing PS-PCM that eliminates the need for on-the-fly computations, which is an imperative attribute for practical system implementation. The core of this code construction method is the utilization of a surrogate channel to allocate rates to each component code while considering the varying probability distributions and protection levels of label bits. The assigned component code rates can be seamlessly integrated into the modulation and coding scheme (MCS) table to facilitate rapid construction for both base stations and user equipment. Furthermore, we devise flexible rate matching methods to allow fine granularity adjustment of rates and blocklengths for PS-PCM. Simulation results validate the efficacy of our proposed approaches, which also provide insights and benchmarks for the capability of PS-PCM to meet requirements for enhanced spectral efficiency, higher reliability, and more flexibility.

For fifth-generation wireless networks to transition to sixth-generation wireless networks, the integration of coordinated multipoint (CoMP) and non-orthogonal multiple access (NOMA) techniques is expected to overcome new challenges and enhance performance compared to the CoMP or NOMA scheme. The joint-transmission CoMP (JT-CoMP) technique is a typical technical implementation of the CoMP scheme. In this study, we investigate a downlink network with a joint JT-CoMP-NOMA scheme. Based on the generalized Stienen model from stochastic geometry, we divide far and near NOMA user equipment (UE) and develop a theoretical framework to analyze the system performance. Expressions for the coverage probabilities and average achievable rates of two types of UEs (named CoMP and non-CoMP UEs) are derived. By comparing analytical results with Monte Carlo simulations, we show that the approximations in the analytical derivations are tight. The impact of certain network parameters, such as the power allocation coefficient, on the system performance is also studied. Notably, the developed transmission scheme is shown to outperform the NOMA-only and the JT-CoMP-only schemes.

Integrated sensing and communication (ISAC) has the potential to facilitate coordination gains from mutual assistance between sensing and communication (S&C), especially sensing-aided communication enhancement (SACE). Reconfigurable intelligent surface (RIS) is another potential technique for achieving resource-efficient communication enhancement. Therefore, this paper proposes an innovative RIS-assisted SACE (R-SACE) mechanism with the goal of improving the systemic communication performance of the ISAC system in practical scenarios where the channel status information (CSI) is imperfectly known. In the proposed R-SACE mechanism, a dual-functional base station (BS) provides downlink communication services to both the communication user and the dynamically changing target that is detected using the communication signals. RIS assists in both sensing and communications of the BS. A typical scenario is investigated in which either or both the direct and RIS-assisted reflected communication links are available depending on sensing results. The average systemic throughput (AST) over the entire timeline of the R-SACE mechanism is maximized by jointly optimizing both temporal and spatial resources under the probabilistic constraint and the sensing performance, transmission power, and communication interference constraints. The non-convex probabilistic mixed optimization problem is transformed and then solved by the proposed fixed-point iterative (FPI) algorithm. Simulation results demonstrate that the proposed FPI algorithm and R-SACE mechanism outperform the baseline algorithms and communication enhancement mechanisms in achieving higher systemic communication performance.

The 6th generation mobile communication system (6G) will provide everything as a service (XaaS), where X includes communication, sensing, computing, artificial intelligence (AI), big data and security and more. Novel features such as sensing as a Service (SaaS) will contribute to further realising Internet of Everything (IoE). Integrated Sensing and Communication (ISAC) is identified as one of the six usage scenarios for 6G by the International Telecommunication Union Radiocommunication Sector (ITU-R), and the corresponding studies on the detailed technical performance requirements and evaluation methodologies have begun in 2024. Although ISAC has become a popular topic, there are no systematic performance requirements metrics and corresponding evaluation methodologies defined for SaaS in a mobile communication system, while conventional key performance indicators (KPI) for radar systems have been borrowed currently. Therefore, to fill this gap, this paper proposes SensCAP, a systematic CAPability performance metric composed of Sensing Capacity, Accuracy and Probability. The sensing capacity reflects the comprehensive sensing performance, which can be expressed as the number of targets that can be detected per unit area within unit time, given Sensing Quality of Service (QoS) requirements consisting of sensing accuracy and probability. Furthermore, the performance evaluation of the SensCAP is conducted through system simulation using proposed evaluation methodologies, and the KPI values are suggested as the guidelines for further study in ITU-R.

In this paper we propose a novel non-orthogonal multiple access (NOMA) scheme via non-binary factor graphs by introducing operations over Galois field GF(q). By utilizing sparse GF(q) spreading, the proposed scheme benefits from an improved diversity of the superimposed symbols and accordingly a lower probability of constellation overlapping. Meanwhile, the coordination with high-order modulation helps to reduce the interference at the receiver, and therefore a better error performance can be expected. Iterative belief-propagation (BP) detection based on log-domain probabilities is derived for the GF(q) NOMA. The upper bounds of maximum likelihood (ML) detection and simulation results in terms of symbol error rate are provided, which demonstrate the superiority of the proposed scheme to its binary counterparts.

As a candidate technique to achieve sixth-generation wireless communication (6G), reconfigurable intelligent surface (RIS) has become popular in both academia and industry. For better exploration of the advantages of RIS, we compare the performances of RIS and network-controlled repeater (NCR) in 3GPP release-18. We first theoretically analyze the received signal power and signal-to-noise ratio performances for both RIS and NCR. Then, we simulate the reference signal received power and signal-to-interference-and-noise ratio performances at the system level for both RIS and NCR in the frequency range 1 and frequency range 2 bands. Finally, several insights on engineering applications are given based on the comparison between RIS and NCR.

Reconfigurable intelligent surface (RIS) is an emerging technique employing metasurface to reflect the signal from the source node to the destination node. By smartly reconfiguring the electromagnetic (EM) properties of the metasurface and adjusting the EM parameters of the reflected radio waves, RIS can turn the uncontrollable propagation environment into an artificially reconfigurable space, and thus, can significantly increase the communications capacity and improve the coverage of the system. In this paper, we investigate the far field channel in which the line-of-sight (LOS) propagation is dominant. We propose an antenna model that can characterize the radiation patterns of realistic RIS elements, and consider the signal power received from the two-hop path through RIS. System-level simulations of network performance under various scenarios and parameter configurations are performed, which show significant gain of RIS.

Multi-user multiple-input multiple-output (MU-MIMO) is one of the key techniques to meet high spectral efficiency requirements for the fifth generation (5G) and beyond 5G wireless network. To achieve the high capacity of uplink MU-MIMO, a generalized polar precoding scheme based on rotation and permutation (GP-RP) is proposed in this paper, which can enhance the reliability distinctions between users’ channels. Via the three-stage channel transformation, the binary polar coding, signal modulation and the original multi-user channel are successively partitioned into multiple bit polarized channels. To further amplify the polarization effect, an unitary precoding scheme is proposed for the uplink MU-MIMO system without changing the communication capacity. The simulation results show that the proposed precoding scheme can further improve the polarization between the synthesized user channels and achieve lower block error ratio (BLER).

As a visible light communications (VLC) modulation method, the layered asymmetrically clipped optical orthogonal frequency division multiplexing (LACO-OFDM) is promising. The layers in LACO-OFDM provide a high flexibility for power allocation and modulation selection. In this paper, we analyze the impacts of LACO-OFDM layer selection, layer power allocation and modulation selection. Firstly, we compare the BER performance of different power allocation methods and investigate the impact of layers on BER and optical power. On this basis, we propose a joint layer selection and power allocation algorithm. Simulation results show that the proposed power allocation scheme has a better bit error ratio (BER) performance than the common schemes. Finally, we verify the layer modulation selection and propose a search method with low time complexity.

As the transmitter in visible light communications (VLC) system, when the electrical current signal exceeds the input range of light emitting diode (LED), it will cause a nonlinear distortion. Since the electrical current is proportional to the optical power, the nonlinear distortion of electrical current signal is equivalent to the nonlinear distortion of optical power signal. This paper studies the impacts of optical power signal nonlinear distortion on signal distribution and capacity. Firstly, we derive the maximum entropy distribution of the optical power signal and obtain the corresponding capacity lower bound using the entropy power inequality (EPI). Then the nonlinear distortion is modelled as the signal clipping noise, and we analyze the impacts of upper-clipping and lower-clipping on system performance. Numerical results show that a certain degree of signal clipping is acceptable at low optical signal-to-noise ratio (OSNR). However, the clipping should be minimum at high OSNR.

In visible light communications, adding direct current (DC) bias is the most common solution to the bipolar problem of signal, so that the precoding and optical orthogonal frequency division multiplexing (O-OFDM) can be performed. Moreover, it will be easier to achieve dimming control. In this paper, we analyze the impact of DC bias on optical power signal in the view of distribution, capacity and nonlinear distortion. Firstly, we classify the impacts of DC bias into two types depends on the total power, and derive their maximum entropy distributions. Then we investigate the capacity of two different channels with DC bias. Finally, we study the nonlinear distortion of power signal. Derivation and simulation results show that the capacity would decrease as the DC bias increases in most cases. The conclusions will help the consideration of DC bias in future system design.

As one of the potential candidate technologies for sixth generation (6G), visible light communication (VLC) can provide indoor communication services with high data rate when combined with multiple-input multiple-output (MIMO). In this paper, we first study the impact of precoding on zonotopes model of channel and then derive the capacity of VLC-MIMO with precoding when the number of transmitters is greater than receivers. Based on the zonotopes graph, two design principles for VLC-MIMO optimal precoding are obtained. Simulation results show that the commonly used radio frequency (RF)-MIMO precodings can hardly catch the capacity lower bound. The optimal precoding in RF may not be optimal in VLC.

Visible light communication (VLC), as an auxiliary method of radio-frequency (RF) communication, can solve the problem of spectrum shortage in 6G. Due to the channel correlation caused by the layout of light-emitting diodes (LEDs) and photo detectors (PDs) in indoor scenario, the performance of VLC MIMO systems may get a significant degradation. This paper proposes a lamp selection scheme to select the optimal lamp subset to maximize the energy efficiency (EE) while meeting the illumination requirement. Simulation results verify that the performance of the proposed lamp selection scheme is close to that of the optimal scheme while reducing the complexity significantly.

Visible light communication (VLC) multiple-input multiple-output (MIMO) technology is a promising technology in 6G. However, the existing capacity formulae for radio frequency (RF) cannot be directly used for VLC due to the constraints of transmitted signals and unique channel characteristics. In this paper, we make a comparison of different signal distribution. Firstly, we analyze the relationship between transmitted and received signals based on zonotopes model. Then the capacity gap between the truncated Gaussian distribution and uniform distribution is analyzed. Simulations show that the uniform distribution has a better performance than truncated Gaussian, which may promote new signal design for VLC.

To adapt to the complicated interference and the high dynamics of wireless circumstances, deep reinforcement learning (DRL) has been considered as a potential solution for beam management in the massive multiple-input and multiple-output (MIMO) systems. However, due to the extremely high dimensions of both action and state spaces, the existing DRL-based schemes are with high computation costs, and the practical performance is still unknown. To provide some insights, DRL-based beam management in the massive MIMO systems is studied in this paper. First, a DRL-based beam management scheme has been designed for beyond the fifth generation and the sixth generation (B5G/6G) systems, which can support the collaborative beam selections of multiple panels with low complexity and fast convergence. Second, a system-level simulation platform is developed to evaluate the performance of our proposed scheme in B5G/6G systems. Finally, the system-level simulation results are provided, which show that our proposed scheme can achieve much higher spectrum efficiency than the referred evaluation results given by international telecommunication union (ITU).

Reconfigurable intelligent surface (RIS) is an emerging technique employing metasurface to reflect the signal from the source node to the destination node. Essentially, RIS can be considered as a passive relay between the source and destination node. By contrast, relay node in a traditional network has to be active, consuming energy when it is relaying the signal or information. It is worth investigating the differences between RIS and relay. In this paper, we compare the performances between RIS and active relay for a general multiple-input multiple-output (MIMO) system. To make the comparison fair and comprehensive, both the performances of RIS and active relay are optimized with best-effort, by formulating a non-convex optimization problem respectively. In case of RIS, transmit beamforming and reflecting coefficients are jointly optimized. In case of active relay including half-duplex relay and full-duplex relay, transmit beamforming for both source and relay are optimized. The original nonconvex optimization problems are transformed into to a weighted mean-square error (MSE) minimization problem and solved by the proposed alternating optimization algorithm, respectively. Numerical results are presented to demonstrate the validity of the proposed algorithm.

With the development of mobile Internet and the Internet of Everything (IoE) for beyond the fifth generation (BSG)/sixth generation (6G) mobile network, the short-packet communication have attracted much attention. In order to improve the utilization of sporadic spectrum and to reduce the peak-to-average power ratio (PAPR) and out-of-band emission (OOBE), a filtering and windowing based orthogonal frequency division multiplexing (FW-OFDM) waveform is proposed in this paper. An optimization problem is formulated to minimize the power spectral density (PSD) in the stopband, and subject to the constraints of the PAPR of the FW-OFDM signal. Meanwhile, both windowing and filtering operation will not cause energy degradation of the transmitted signal. The suboptimal coefficient vectors of windowing and filtering are obtained by the genetic algorithm (GA). Simulation results show that FW-OFDM and cyclic prefix-orthogonal frequency division multiplexing (CP-OFDM) perform better than filter bank multi-carrier (FBMC) in terms of time efficiency. Besides, because of better OOBE and PAPR performance, the proposed FW-OFDM waveform is more suitable for the IoE scenario.

Non-orthogonal multiple access (NOMA) has become one of the promising key technologies for future 5G wireless communications to improve spectral efficiency and support massive connectivity. However, in the uplink grant-free NOMA system, the current near-optimal multi-user detection (MUD) based on message passing algorithm (MPA) assumes that the user activity information is exactly known at the receiver, which is impractical yet challenging due to anyone of massive users can randomly enter or leave the system. In this paper, inspired by the observation of user sparsity, we jointly use compressive sensing (CS) and MPA to propose a CS-MPA detector to realize both user activity and data detection for uplink grant-free NOMA. Specifically, the MUD problem is firstly formulated under CS framework by exploiting user sparsity, and then user activity can be detected by sparse signal recovery algorithms in CS. Then, MPA can be performed to reliably detect active users' data. It is shown that the proposed CS-MPA detector with affordable complexity not only outperforms the conventional MPA detector without user activity information, but also achieves very close performance to the genie- knowledge MPA detector with exact knowledge of user activity, especially when the signal-to-noise ratio (SNR) is high.