305 research outputs found
NOMA-Aided Joint Radar and Multicast-Unicast Communication Systems
No full textThe novel concept of non-orthogonal multiple access (NOMA) aided joint radar
and multicast-unicast communication (Rad-MU-Com) is investigated. Employing the
same spectrum resource, a multi-input-multi-output (MIMO) dual-functional
radar-communication (DFRC) base station detects the radar-centric users
(R-user), while transmitting mixed multicast-unicast messages both to the
R-user and to the communication-centric user (C-user). In particular, the
multicast information is intended for both the R- and C-users, whereas the
unicast information is only intended for the C-user. More explicitly, NOMA is
employed to facilitate this double spectrum sharing, where the multicast and
unicast signals are superimposed in the power domain and the superimposed
communication signals are also exploited as radar probing waveforms. First, a
beamformer-based NOMA-aided joint Rad-MU-Com framework is proposed for the
system having a single R-user and a single C-user. Based on this framework, the
unicast rate maximization problem is formulated by optimizing the beamformers
employed, while satisfying the rate requirement of multicast and the predefined
accuracy of the radar beam pattern. The resultant non-convex optimization
problem is solved by a penalty-based iterative algorithm to find a high-quality
near-optimal solution. Next, the system is extended to the scenario of multiple
pairs of R- and C-users, where a cluster-based NOMA-aided joint Rad-MU-Com
framework is proposed. A joint beamformer design and power allocation
optimization problem is formulated for the maximization of the sum of the
unicast rate at each C-user, subject to the constraints on both the minimum
multicast rate for each R&C pair and on accuracy of the radar beam pattern for
detecting multiple R-users. The resultant joint optimization problem is
efficiently solved by another penalty-based iterative algorithm developed.Comment: 14 pages, 12 figures, this work is accepeted for the publication in
IEEE Journal on Selected Areas in Communication
RIS-aided near-field communications for 6G: opportunities and challenges
No full textReconfigurable intelligent surface (RIS)-aided nearfield communications is investigated. First, the necessity of investigating RIS-aided near-field communications and the advantages brought about by the unique spherical-wave-based near-field propagation are discussed. Then, the family of patch-array-based RISs and metasurface-based RISs are introduced along with their respective near-field channel models. A pair of fundamental performance limits of RIS-aided near-field communications, namely their power scaling law and effective degrees-of-freedom, are analyzed for both patch-array-based and metasurface-based RISs, which reveals the potential performance gains that can be achieved. Furthermore, the associated near-field beam training and beamforming design issues are studied, where a twostage hierarchical beam training approach and a low-complexity element-wise beamforming design are proposed for RIS-aided near-field communications. Finally, a suite of open research problems is highlighted for motivating future research
Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted UAV communications
No full textA novel air-to-ground communication paradigm is conceived, where an unmanned aerial vehicle (UAV)-mounted base station (BS) equipped with multiple antennas sends information to multiple ground users (GUs) with the aid of a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). In contrast to the conventional RIS whose main function is to reflect incident signals, the STAR-RIS is capable of both transmitting and reflecting the impinging signals from either side of the surface, thereby leading to full-space 360 degree coverage. However, the transmissive and reflective capabilities of the STAR-RIS require more complex transmission/reflection coefficient design. Therefore, in this work, a sum-rate maximization problem is formulated for the joint optimization of the UAV’s trajectory, the active beamforming at the UAV, and the passive transmission/reflection beamforming at the STAR-RIS. This cutting-edge optimization problem is also subject to the UAV’s flight safety, to the maximum flight duration constraint, as well as to the GUs’ minimum data rate requirements. Given the unknown locations of obstacles prior to the UAV’s flight, we provide an online decision making framework employing reinforcement learning (RL) to simultaneously adjust both the UAV’s trajectory as well as the active and passive beamformer. To enhance the system’s robustness against the associated uncertainties caused by limited sampling of the environment, a novel “distributionally-robust” RL (DRRL) algorithm is proposed for offering an adequate worst-case performance guarantee. Our numerical results unveil that: 1) the STAR-RIS assisted UAV communications benefit from significant sum-rate gain over the conventional reflecting-only RIS; and 2) the proposed DRRL algorithm achieves both more stable and more robust performance than the state-of-the-art RL algorithms
Joint Location and Beamforming Design for STAR-RIS Assisted NOMA Systems
No full textSimultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) communication systems are investigated in its vicinity, where a STAR-RIS is deployed within a predefined region for establishing communication links for users. Both beamformer-based NOMA and cluster-based NOMA schemes are employed at the multi-antenna base station (BS). For each scheme, the STAR-RIS deployment location, the passive transmitting and reflecting beamforming (BF) of the STAR-RIS, and the active BF at the BS are jointly optimized for maximizing the weighted sum-rate (WSR) of users. To solve the resultant non-convex problems, an alternating optimization (AO) algorithm is proposed, where successive convex approximation (SCA) and semi-definite programming (SDP) methods are invoked for iteratively addressing the non-convexity of each sub-problem. Numerical results reveal that 1) the WSR performance canbe significantly enhanced by optimizing the specific deployment location of the STAR-RIS; 2) both beamformer-based and clusterbased NOMA prefer asymmetric STAR-RIS deployment
Hybrid reinforcement learning for STAR-RISs: a coupled phase-shift model based beamformer
No full textA simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted multi-user downlink multiple-input single-output (MISO) communication system is investigated. In contrast to the existing ideal STAR-RIS model assuming an independent transmission and reflection phase-shift control, a practical coupled phase-shift model is considered. Then, a joint active and passive beamforming optimization problem is formulated for minimizing the long-term transmission power consumption, subject to the coupled phase-shift constraint and the minimum data rate constraint. Despite the coupled nature of the phase-shift model, the formulated problem is solved by invoking a hybrid continuous and discrete phase-shift control policy. Inspired by this observation, a pair of hybrid reinforcement learning (RL) algorithms, namely the hybrid deep deterministic policy gradient (hybrid DDPG) algorithm and the joint DDPG & deep-Q network (DDPG-DQN) based algorithm are proposed. The hybrid DDPG algorithm controls the associated high-dimensional continuous and discrete actions by relying on the hybrid action mapping. By contrast, the joint DDPG-DQN algorithm constructs two Markov decision processes (MDPs) relying on an inner and an outer environment, thereby amalgamating the two agents to accomplish a joint hybrid control. Simulation results demonstrate that the STARRIShas superiority over other conventional RISs in terms of its energy consumption. Furthermore, both the proposed algorithms outperform the baseline DDPG algorithm, and the joint DDPGDQN algorithm achieves a superior performance, albeit at anincreased computational complexity
STAR: Simultaneous Transmission And Reflection for 360° Coverage by Intelligent Surfaces
No full textA novel simultaneously transmitting and reflecting (STAR) system design relying on reconfigurable intelligent surfaces (RISs) is conceived. First, an existing prototype is reviewed and the potential benefits of STAR-RISs are discussed. Then, the key differences between conventional reflecting-only RISs and STAR-RISs are identified from the perspectives of hardware design, physics principles, and communication system design. Furthermore, the basic signal model of STAR-RISs is introduced, and three practical protocols are proposed for their operation, namely energy splitting, mode switching, and time switching. Based on the proposed protocols, a range of promising application scenarios are put forward for integrating STAR-RISs into next-generation wireless networks. By considering the downlink of a typical RIS-aided multiple-input single-output (MISO) system, numerical case studies are provided for revealing the superiority of STAR-RISs over other baselines, when employing the proposed protocols. Finally, several open research problems are discussed
Simultaneously Transmitting and Reflecting Intelligent Omni-Surfaces: Modeling and Implementation
Full text linkGiven the rapid development of advanced electromagnetic (EM) manipulation technologies, researchers have turned their attention to the investigation of smart surfaces for enhancing radio coverage. Simultaneously transmitting and reflecting (STAR) intelligent omni-surfaces (IOSs) constitute one of the most promising categories. Although previous research contributions have demonstrated the benefits of simultaneously transmitting and reflecting intelligent omni-surfaces (STAR-IOSs) in terms of wireless communication performance gains, several important issues remain unresolved, including practical hardware implementations and accurate physical models. In this article, we address these by discussing four practical hardware implementations of STAR-IOSs as well as three hardware modeling techniques and five channel modeling methods. We thus clarify the taxonomy of smart surface technologies in support of further investigating the family of STAR-IOSs.</p
Genetic and Molecular Approaches for Breeding Improvement in Aquaculture
No full textAquaculture has become an increasingly vital sector for global food security, contributing significantly to the supply of high-quality, sustainable animal protein [...
Integrated Utilization of Sewage Sludge and Coal Gangue for Cement Clinker Products: Promoting Tricalcium Silicate Formation and Trace Elements Immobilization
No full textThe present study firstly proposed a method of integrated utilization of sewage sludge (SS) and coal gangue (CG), two waste products, for cement clinker products with the aim of heat recovery and environment protection. The results demonstrated that the incremental amounts of SS and CG addition was favorable for the formation of tricalcium silicate (C3S) during the calcinations, but excess amount of SS addition could cause the impediment effect on C3S formation. Furthermore, it was also observed that the C3S polymorphs showed the transition from rhombohedral to monoclinic structure as SS addition was increased to 15 wt %. During the calcinations, most of trace elements could be immobilized especially Zn and cannot be easily leached out. Given the encouraging results in the present study, the co-process of sewage sludge and coal gangue in the cement kiln can be expected with a higher quality of cement products and minimum pollution to the environment.National Natural Science Foundation of China [51522401, 51472007, 51272005]; Ministry of public welfare industry scientific research projects [201511062]SCI(E)[email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected]
Joint Radar and Multicast-Unicast Communication: A NOMA Aided Framework
No full textThe novel concept of non-orthogonal multiple access (NOMA) aided joint radar
and multicast-unicast communication (Rad-MU-Com) is investigated. Employing the
same spectrum resource, a multi-input-multi-output (MIMO) dual-functional
radar-communication (DFRC) base station detects the radar-centric user
(R-user), while transmitting mixed multicast-unicast messages both to the
R-user and to the communication-centric user (C-user). In particular, the
multicast information is intended for both the R- and C-users, whereas the
unicast information is only intended for the C-user. More explicitly, NOMA is
employed to facilitate this double spectrum sharing, where the multicast and
unicast signals are superimposed in the power domain and the superimposed
communication signals are also exploited as radar probing waveforms. A
beamformer-based NOMA-aided joint Rad-MU-Com framework is proposed for the
system having a single R-user and a single C-user. Based on this framework, the
unicast rate maximization problem is formulated by optimizing the beamformers
employed, while satisfying the rate requirement of multicast and the predefined
accuracy of the radar beam pattern. The resultant non-convex optimization
problem is solved by a penalty-based iterative algorithm to find a high-quality
near-optimal solution. Finally, our numerical results reveal that significant
performance gains can be achieved by the proposed scheme over the benchmark
schemes.Comment: This is the conference version of arXiv:2110.0237
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