With the rapid development of low-altitude economy, the low-altitude intelligent network (LAIN) serves as a critical infrastructure for supporting diversified aerial activities. However, current LAIN lacks a physical-network synchronization mechanism and fails to handle heterogeneity at the architecture level, which leads to difficulties in real-time adaptive adjustments and efficient unified coordination. To address these issues, this paper proposes the networked embodied intelligence (NEI) paradigm, with a network-level sensing-decision-action-feedback (SDAF) closed-loop mechanism to synchronize physical and network states. Building on this paradigm, we functionally reconfigure LAIN into four collaborative subnetworks: sensing, computing, communication and navigation. As a further step, we propose the NEI-LAIN architecture, where these subnetworks collaborate via the SDAF loop to achieve global collaboration and continuous evolution. Simulation results demonstrate that the proposed NEI-LAIN can significantly enhance the performance of communication robustness, resource utilization and task responsiveness in highly dynamic scenarios. Finally, we discuss its implementation challenges and future research directions.

The safe and high-efficiency operation of low-altitude vehicles (LAVs) is the key to supporting the rapid development of the low-altitude economy. However, the conventional space-air-ground integrated network (C-SAGIN) mainly focuses on ground users, which is difficult to provide high-quality services for LAVs. In this article, we first propose a novel architecture of low-altitude centric space-air-ground integrated network (LAC-SAGIN), where low-altitude airspace and LAVs become the communication centers. A detailed comparison is further illustrated between these two architectures in terms of their composition and performance metrics. Although LAC-SAGIN can effectively support the low-latency and continuous communication of LAVs, it still faces several key implementation challenges including insufficient low-altitude infrastructures, high mobility of LAVs and its diversified task requirements, and low transmission efficiency and energy efficiency in airspace communication. To address these challenges, the corresponding three countermeasures are proposed, which reveal the future research direction of LAC-SAGIN.

Owing to the ability of reconfiguring wireless channels, intelligent reflecting surface (IRS) can help non-orthogonal multiple access (NOMA) to release its tremendous potential. However, the inter-user interference becomes the bottleneck of IRS-NOMA networks. To tackle this challenge, we propose two constructive interference precoding (CIP) based countermeasures in this paper for interference exploitation in IRS-NOMA networks. Specifically, the first scheme makes the residual interference from higher-order users (HUs) be constructive to lower-order users (LUs), so that the interference-free decoding can be achieved. While the second scheme directly utilizes the interference from LUs for the signal reception of HUs to avoid successive interference cancellation (SIC). The transmit power is minimized by jointly optimizing the BS active beamforming and the IRS passive beamforming for the two schemes, subject to the signal-to-interference-plus-noise ratio (SINR) requirement of each user, SIC decoding constraints, constructive condition and IRS unit-modulus constraint. Due to the coupled variables and non-convex constraints, we first decompose each problem into two subproblems, and then apply successive convex approximation (SCA) to convert them into convex ones. Finally, an alternating optimization (AO) based algorithm is proposed to solve the two convex subproblems for each scheme iteratively. Simulation results are presented to show the superiority and applicability of the proposed schemes compared to benchmarks.

Non-orthogonal multiple access (NOMA) can help integrated sensing and communication (ISAC) to accommodate more users and well manage interference. In this paper, we first propose a NOMA-ISAC scheme, in which a multiantenna base station (BS) transmits ISAC signal to detect a radar user (RU), and provide wireless service to the RU and the communication user (CU) simultaneously. The inter-user interference can be mitigated by the successive interference cancellation (SIC). We further investigate the trade-off between minimizing the beampattern matching error and maximizing the CU’s achievable signal-to-noise ratio (SNR), and propose a penalty-based semi-definite relaxation (SDR) method to solve this non-convex problem. Then, to mitigate the instantaneous NOMA-ISAC beampattern shaking and enhance its stability, we utilize constructive interference precoding (CIP) to assist the NOMA-ISAC beampattern design. Introducing CIP can convert the interference from RU into the beneficial signal to CU and the complex SIC can be avoided. Then, the corresponding trade-off can be transformed into a convex problem by the Taylor-series approximation, and an iterative algorithm is proposed to solve it. Moreover, the Manopt toolbox assisted initialization is utilized to accelerate its convergence speed. Simulation results verify that the proposed CIP-NOMA-ISAC scheme can effectively enhance the stability of instantaneous NOMA-ISAC beampattern over limited time slots, and provide higher SNR for CU.

Reconfigurable intelligent surface (RIS) has been widely deployed to assist the covert transmission thanks to its ability of channel reconfiguration. Compared with the conventional RIS, simultaneous transmitting and reflecting RIS (STAR-RIS) can transmit and reflect the incident signal simultaneously. This paper investigates the STAR-RIS assisted covert multicasting with the hardware impairment. Specifically, Alice covertly transmits the common information to two users assisted by one STAR-RIS against two wardens. The covert rate is maximized via jointly optimizing the transmit beamforming, and the reflection and transmission phase shifts, satisfying the transmit power constraint, the covertness constraint and the protocol of STAR-RIS. Owing to the non-convexity, we propose an iterative algorithm based on the alternating optimization, successive convex approximation and penalty-based semi-definite relaxation to obtain a sub-optimal solution. Simulation results verify the effectiveness of STAR-RIS.

Although intelligent reflecting surface (IRS) can reconfigure the propagation environment to enhance the performance of both non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT), the security remains a key challenge. We design a secure beamforming scheme for IRS-assisted NOMA SWIPT networks in this paper, where the artificial jamming is inserted into NOMA signals by the base station to ensure the network security with the aid of IRS. Specifically, we jointly optimize the transmit beamforming and jamming vectors, the IRS reflecting matrix and the power splitting ratio to maximize the sum rate, satisfying the rate requirement and energy harvesting threshold for each user. The optimization problem is difficult to be solved directly due to its non-convexity with coupled variables. Thus, we first apply auxiliary variables to reformulate it into a more tractable form, and then decompose it into three subproblems that can be converted into convex ones via successive convex approximation. Finally, we solve them iteratively using an alternating optimization algorithm. Simulation results validate that the proposed scheme can yield significant improvement in both secrecy performance and energy harvesting efficiency in comparison with benchmarks.

As a symbol-level precoding scheme, constructive interference precoding (CIP) has been demonstrated its superiority in multi-antenna orthogonal multiple access (OMA). By utilizing both the channel state information (CSI) and data symbols, harmful multi-user interference can be converted into useful reception power via the well-designed CIP. When CIP meets non-orthogonal multiple access (NOMA) whose bottle-neck is usually at the weaker user, this paper is the first to propose CIP to enhance the downlink MISO-NOMA networks, by making the desired signal of the stronger user in a typical NOMA pair constructive to the weaker user. In our CIP-NOMA scheme, we properly design the CIP precoder for transmit power minimization at the base station (BS), subject to signal-to-interference-plus-noise ratio (SINR) requirements of NOMA users. We further derive its closed-form solutions with Karush-Kuhn-Tucker (KKT) conditions, and optimally obtain the desired CIP precoders. Moreover, as compared to conventional NOMA schemes, we theoretically prove that once two NOMA users possess distinct channel gains, our optimized CIP-NOMA scheme always uses lower transmit power to reach the SINR thresholds. To be robust against the channel estimation errors, we extend our CIP-NOMA scheme to the scenario of imperfect CSI, by further addressing the hidden CSI errors. Specifically, we first introduce some auxiliary variables to separate the coupled vectors, and then use S-Procedure and semi-definite relaxation (SDR) to further transform them into convex ones. Extensive simulations verify that our CIP-NOMA scheme greatly outperforms the benchmarks with both perfect and imperfect CSI.

Reconfigurable intelligent surface (RIS) has been widely deployed to assist the covert transmission thanks to its ability of channel reconfiguration. Compared with the conventional RIS, simultaneous transmitting and reflecting RIS (STAR-RIS) can transmit and reflect the incident signal simultaneously, which provides an opportunity for the full-space covert transmission. This paper investigates the robust covert multicasting aided by the STAR-RIS with the hardware impairment. Specifically, Alice covertly transmits the common information to two single-antenna users assisted by the STAR-RIS against two non-colluding multi-antenna wardens. Furthermore, both energy splitting (ES) and mode switching (MS) protocols of the STAR-RIS are considered. With perfect wiretap channel state information (CSI), the covert rate is maximized via jointly optimizing the transmit beamforming, the reflection and transmission coefficient matrices, satisfying the transmit power constraint, the covertness constraint and the protocol of the STAR-RIS. Moreover, we also investigate the covert rate maximization problem under the case of imperfect wiretap CSI. Due to the non-convexity of the problem, we propose iterative algorithms based on the alternating optimization, successive convex approximation and penalty-based semi-definite relaxation to obtain a near-optimal solution to each problem. Simulation results verify the effectiveness of the STAR-RIS, and show that the ES is superior to the MS.

Due to its capability of channel reconfiguration and enhancement, intelligent reflecting surface (IRS) can be introduced to improve the secrecy rate of non-orthogonal multiple access (NOMA) networks. However, the cost and hardware complexity of full-digital beamforming in existing related studies are high, especially for the systems with massive antennas. This paper studies the robust secure transmission for IRS-aided NOMA networks with cost-effective hybrid beamforming. Specifically, we deploy an IRS to assist the secure transmission from a base station with cost-effective hybrid beamforming to a cell-center user (U1) and a cell-edge user (U2), with the existence of a potential eavesdropper. Two schemes are proposed for guaranteeing the secure transmission of U1 with the perfect and imperfect channel state information (CSI), respectively. With the perfect CSI, the secrecy rate of U1 is maximized subject to the constant modulus constraint and the quality of service (QoS) constraint of U2 via optimizing the hybrid beamforming and phase shifts of IRS. With the imperfect CSI, the achievable rate at U1 is maximized, satisfying its worst-case eavesdropping rate constraint, the constant modulus constraint and the QoS constraint of U2. Because of the non-convexity, we first decompose each problem into two subproblems, respectively. Then, the subproblems are solved via the penalty-based algorithm and the successive convex approximation. Simulation results verify that the two proposed schemes have higher energy efficiency and can boost the security of IRS-aided NOMA networks with perfect and imperfect CSI, respectively.

As a symbol-level precoding scheme, constructive interference precoding (CIP) has been demonstrated its superiority in multi-antenna orthogonal multiple access (OMA) systems. By utilizing both the channel state information (CSI) and data symbols, harmful multi-user interference can convert to useful reception power via the well-designed CIP precoder. When CIP meets non-orthogonal multiple access (NOMA) whose bottleneck is usually at the weaker user side, this paper is the first to propose CIP to enhance the downlink MISO-NOMA networks, by making the desired signal of the stronger user in a typical NOMA pair constructive to the weaker user. In our CIP-NOMA scheme, we properly design the CIP precoder for transmit power minimization at the base station (BS), subject to signal-to-interference-plus-noise ratio (SINR) requirements of NOMA users. By replacing the non-convex constraints with convex linear matrix inequalities, we optimally obtain the precoding solutions for our CIP-NOMA scheme by semi-definite relaxation (SDR) method. Moreover, as compared to conventional NOMA schemes, we theoretically prove that once two NOMA users possess distinct channel gains, our optimized CIP-NOMA scheme always uses smaller transmit power to reach the target SINR thresholds. We further extend our CIP-NOMA scheme to the scenario of imperfect CSI, by further addressing the hidden CSI errors. Finally, we run extensive simulations to verify that our proposed CIP-NOMA scheme greatly outperforms zero-forcing (ZF), conventional NOMA and conventional CIP schemes.

Due to the ability of channel reconfiguration, intelligent reflecting surface (IRS) can be used to boost the secrecy rate of cognitive non-orthogonal multiple access (NOMA) systems. However, the cost and hardware complexity of full-digital beamforming in existing related studies is high, especially for the systems with massive antennas. In this paper, we investigate the secure transmission for IRS-aided cognitive NOMA systems with cost-effective analog beamforming. The secrecy rate of primary user is maximized subject to the quality of service constraint of secondary user via joint analog and passive beamforming optimization. Owing to the non-convexity, we first transform the problem into two subproblems. Then, each subproblem is tackled via the penalty-based algorithm and the successive convex approximation. Simulation results demonstrate that the proposed transmission scheme has higher energy efficiency and can boost the security of IRS-aided cognitive NOMA systems.

Combining non-orthogonal multiple access (NO-MA) and unmanned aerial vehicles (UAVs) can achieve better performance for wireless networks. In this paper, we propose an effective scheme for NOMA-UAV network with multiple clusters. Due to the limited resource, the user clustering and optimal routing are first developed by the K-means algorithm and genetic algorithm, respectively. Then, the sum throughput is maximized by jointly optimizing the transmission power, hovering locations and transmission duration of UAV. To solve this non-convex problem with coupled variables, we decompose it into three subproblems. Among them, the non-convex sub-problems can be transformed into convex ones by successive convex approximation. Then, we propose an iterative algorithm to solve these three subproblems alternately. Finally, simulation results are presented to show the effectiveness of the proposed scheme.

Combining non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAVs) could achieve better performance for wireless networks. However, effective resource allocation for quality of service (QoS) provision among all users still remains as a great challenge for multi-cluster NOMA-UAV networks. In this paper, we propose a NOMA-UAV scheme, where a UAV is deployed as the mobile base station to serve ground users. To meet the QoS requirements of all users with limited resource, the user clustering and optimal routing are first developed by the K-means algorithm and genetic algorithm, respectively. Then, the sum throughput is maximized by jointly optimizing the transmission power, hovering locations and transmission duration of UAV. To solve this non-convex problem with coupled variables, we decompose it into three subproblems. Among them, the power and location optimizations are also non-convex, which can be transformed into convex ones by successive convex approximation. The duration optimization is a linear programming which can be solved directly. Then, we propose an iterative algorithm to solve these three subproblems alternately. Finally, simulation results are presented to show the effectiveness of the proposed scheme.

The integration of intelligent reflecting surface (IRS) and multiple access provides a promising solution to improved coverage and massive connections at low cost. However, securing IRS-aided networks remains a challenge since the potential eavesdropper also has access to an additional IRS reflection link, especially when the eavesdropping channel state information is unknown. In this paper, we propose an IRS-assisted non-orthogonal multiple access (NOMA) scheme to achieve secure communication via artificial jamming, where the multi-antenna base station sends the NOMA and jamming signals together to the legitimate users with the assistance of IRS, in the presence of a passive eavesdropper. The sum rate of legitimate users is maximized by optimizing the transmit beamforming, the jamming vector and the IRS reflecting vector, satisfying the quality of service requirement, the IRS reflecting constraint and the successive interference cancellation (SIC) decoding condition. In addition, the received jamming power is adapted at the highest level at all legitimate users for successful cancellation via SIC. To tackle this non-convex optimization problem, we first decompose it into two subproblems, and then each subproblem is converted into a convex one using successive convex approximation. An alternate optimization algorithm is proposed to solve them iteratively. Numerical results show that the secure transmission in the proposed IRS-NOMA scheme can be effectively guaranteed with the assistance of artificial jamming.

In this paper, we propose a time-efficient data collection scheme, in which multiple ground devices upload their data to the unmanned aerial vehicle (UAV) via uplink nonorthogonal multiple access (NOMA). The total flight time of the UAV is equally divided into N time slots. The duration of each time slot is minimized by jointly optimizing the straight-line trajectory, device scheduling, and transmit power. To solve this mixed integer non-convex optimization problem, we decompose it into two steps. In the first step, we study the device scheduling strategy based on the UAV trajectory and the channel gains between the UAV and ground devices, through which the original problem can be greatly simplified. In the second step, the duration of each time slot is minimized by optimizing the transmit power and the UAV trajectory. An iterative algorithm based on alternating optimization is proposed, where each subproblem can be alternatively solved by applying successive convex approximation with the device scheduling updated at the end of each iteration. Numerical results are presented to evaluate the effectiveness of the proposed scheme.

Due to the mobility and line-of-sight conditions, unmanned aerial vehicle (UAV) is deemed as a promising solution to sensor data collection. On the other hand, it is vital to guarantee the timeliness of information for UAV-assisted data collection. In this paper, we propose a time-efficient data collection scheme, in which multiple ground devices upload their data to the UAV via uplink non-orthogonal multiple access (NOMA). The total flight time of the UAV is equally divided into$N$time slots. The duration of each time slot is minimized by jointly optimizing the straight-line trajectory, device scheduling, and transmit power. To solve this mixed integer non-convex optimization problem, we decompose it into two steps. In the first step, we study the device scheduling strategy based on the UAV trajectory and the channel gains between the UAV and ground devices, through which the original problem can be greatly simplified. In the second step, the duration of each time slot is minimized by optimizing the transmit power and the UAV trajectory. An iterative algorithm based on alternating optimization is proposed, where each subproblem can be alternatively solved by applying successive convex approximation with the device scheduling updated at the end of each iteration. Numerical results are presented to evaluate the effectiveness of the proposed scheme.

Combination of unmanned aerial vehicle (UAV) and non-orthogonal multiple access (NOMA) is deemed as an promising solution to achieving massive connectivity in future wireless networks. In this paper, a UAV-aided NOMA scheme is proposed to achieve simultaneous wireless information and power transfer (SWIPT) and guarantee the secure transmission for ground passive receivers (PRs), in which the nonlinear energy harvesting model is applied. Each time frame is divided into two phases. In the first phase, the received power at each PR is maximized to achieve rapid charging. In the second phase, SWIPT is performed via NOMA with the remaining energy at each PR, and artificial jamming is generated at UAV together with the NOMA information to guarantee the security. The throughput of PRs is maximized, with the highest received jamming power cancelled at each PR via successive interference cancellation (SIC). This disrupts the eavesdropping effectively by jamming without affecting the legitimate transmission. Due to the non-convexity of these two optimization problems, we first convert them to convex ones and then propose iterative algorithms to solve them. Simulation results are presented to show the effectiveness of the proposed scheme.

Non-orthogonal multiple access (NOMA) has been developed as a key multi-access technique for 5G. However, secure transmission remains a challenge in NOMA. Especially, the user with weakest channel is most threatened by eavesdropping, due to its highest transmit power. In this paper, we propose a novel scheme to generate artificial jamming at the NOMA base station (BS), aiming at disrupting the potential eavesdropping without affecting the legitimate transmission. In the scheme, the transmit power of artificial jamming is maximized, with its received power at each receiver higher than that of other users. Thus, the jamming signal can be eliminated via successive interference cancellation before others, and the eavesdropping can be disrupted effectively. Due to the non-convexity of the optimization problems, we first convert it to a convex one and then provide an iterative algorithm to solve it. Simulation results are presented to show the effectiveness of the proposed scheme in guaranteeing the security of NOMA networks.

Non-orthogonal multiple access (NOMA) has been developed as a key multi-access technique for 5G. However, secure transmission remains a challenge in NOMA. Especially, the user with weakest channel is most threatened by eavesdropping, due to its highest transmit power. Two schemes are proposed to generate artificial jamming at the NOMA base station (BS), aiming at disrupting the potential eavesdropping without affecting the legitimate transmission. In the first scheme, the transmit power of artificial jamming is maximized, with its received power at each receiver higher than that of other users. Thus, the jamming signal can be eliminated via successive interference cancellation before others. When the transmit power of the BS is inadequate, the transmit jamming power is maximized with the jamming signal zero-forced at each receiver. Thus, the legitimate transmission is not affected by the jamming, and the eavesdropping can be disrupted effectively. Due to the non-convexity of these two optimization problems, we first convert them to convex ones and, then, provide an iterative algorithm to solve them. Simulation results are presented to show the effectiveness of the proposed schemes in guaranteeing the security of NOMA networks.