A sequential constraint relaxation algorithm for rank-one constrained problems

Cao, Pan; Thompson, John; Poor, H. Vincent

doi:10.23919/eusipco.2017.8081370

Cited by 72 publications

(37 citation statements)

References 14 publications

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“…The details of the proposed sequential constaint relaxation algorithm is presented in Algorithm 2. For the convergence analysis of Algorithm 2, similar proof can be found in [34],…”

Section: Transmission and Reflection Beamforming Optimizationmentioning

confidence: 92%

Joint Design for Simultaneously Transmitting And Reflecting (STAR) RIS Assisted NOMA Systems

Zuo

Liu²,

Ding

et al. 2021

Preprint

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Different from traditional reflection-only reconfigurable intelligent surfaces (RISs), simultaneously transmitting and reflecting RISs (STAR-RISs) represent a novel technology, which extends the half-space coverage to full-space coverage by simultaneously transmitting and reflecting incident signals. STAR-RISs provide new degrees-of-freedom (DoF) for manipulating signal propagation. Motivated by the above, a novel STAR-RIS assisted non-orthogonal multiple access (NOMA) (STAR-RIS-NOMA) system is proposed in this paper. Our objective is to maximize the achievable sum rate by jointly optimizing the decoding order, power allocation coefficients, active beamforming, and transmission and reflection beamforming. However, the formulated problem is non-convex with intricately coupled variables. To tackle this challenge, a suboptimal two-layer iterative algorithm is proposed. Specifically, in the innerlayer iteration, for a given decoding order, the power allocation coefficients, active beamforming, transmission and reflection beamforming are optimized alternatingly. For the outer-layer iteration, the decoding order of NOMA users in each cluster is updated with the solutions obtained from the innerlayer iteration. Moreover, an efficient decoding order determination scheme is proposed based on the equivalent-combined channel gains. Simulation results are provided to demonstrate that the proposed STAR-RSI-NOMA system, aided by our proposed algorithm, outperforms conventional RIS-NOMA and RIS assisted orthogonal multiple access (RIS-OMA) systems.

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“…The details of the proposed sequential constaint relaxation algorithm is presented in Algorithm 2. For the convergence analysis of Algorithm 2, similar proof can be found in [34],…”

Section: Transmission and Reflection Beamforming Optimizationmentioning

confidence: 92%

Joint Design for Simultaneously Transmitting And Reflecting (STAR) RIS Assisted NOMA Systems

Zuo

Liu²,

Ding

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

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“…For dealing with the non-convex rank-one constraint, instead of dropping the rank-one constraint completely, we adopt the sequential rank-one constraint relaxation (SROCR) method to solve the problem OP7. The SROCR method [39,46] and penalty-based method [33] are based on the same theory. The penalty-based method in which the Taylor expansion is introduced to deal with the non-convex objective function, may generate suboptimal solution which is far away from the optimal solution.…”

Section: Passive Beamforming Optimizationmentioning

confidence: 99%

Intelligent Reflecting Surface Aided NOMA for Millimeter-Wave Massive MIMO With Lens Antenna Array

Liu

Cheng

et al. 2021

IEEE Trans. Veh. Technol.

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In this paper, we propose a downlink intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) for millimeter-wave (mmWave) massive MIMO with lens antenna array, i.e., IRS-aided mmWave beamspace NOMA, where the single-antenna users without direct-link but connected to the base station (BS) with the aid of the IRS are grouped as one NOMA group. Considering the power leakage problem in beamspace channel and the per-antenna power constraint, we propose two multi-beam selection strategies for the BS-IRS link under two channel models, i.e., 2-dimension (2D) channel model and 3-dimension (3D) channel model, respectively, where two corresponding RF chain configuration strategies are designed, respectively. Then, we formulate and solve the optimization problem for maximizing the weighted sum rate by jointly optimizing the active beamforming at the BS and the passive beamforming at the IRS, where we propose the alternating optimization (AO) method to solve the above joint optimization problem. Especially, different from the stochastic method, based on the beam-splitting technique, we propose the method to initialize the feasible solution for the proposed AO method, where the transmit power minimization problem is formulated and solved. Through simulations, the weighted sum rate performance of the proposed IRS-aided mmWave beamspace NOMA is verified.

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“…However, the solution deriving from Gaussian randomization may not satisfy all the constraints, which is not a feasible solution. Fortunately, invoked by [25], SROCR approach is suited for problems (20a)-(20j) to approximate a Rank-1 solution. First, constraint (20g) is replaced with the relaxed constraint which makes the largest eigenvalue to trace ratio of V j with the Initialization: set n � 0 and initialize feasible solutions (x 1 [0], x 3,k [0]) to problem (19).…”

Section: (18)mentioning

confidence: 99%

Enhanced Secure SWIPT in Heterogeneous Network via Intelligent Reflecting Surface

Yang

Huang

et al. 2021

Security and Communication Networks

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In this paper, secure transmission in a simultaneous wireless information and power transfer technology-enabled heterogeneous network with the aid of multiple IRSs is investigated. As a potential technology for 6G, intelligent reflecting surface (IRS) brings more spatial degrees of freedom to enhance physical layer security. Our goal is to maximize the secrecy rate by carefully designing the transmit beamforming vector, artificial noise vector, and reflecting coefficients under the constraint of quality-of-service. The formulated problem is hard to solve due to the nonconcave objective function as well as the coupling variables and unit-modulus constraints. Fortunately, by using alternating optimization, successive convex approximation, and sequential Rank-1 constraint relaxation approach, the original problem is transformed into convex form and a suboptimal solution is achieved. Numerical results show that the proposed scheme outperforms other existing benchmark schemes without IRS and can maintain promising security performance as the number of terminals increases with lower energy consumption.

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A sequential constraint relaxation algorithm for rank-one constrained problems

Cited by 72 publications

References 14 publications

Joint Design for Simultaneously Transmitting And Reflecting (STAR) RIS Assisted NOMA Systems

Joint Design for Simultaneously Transmitting And Reflecting (STAR) RIS Assisted NOMA Systems

Intelligent Reflecting Surface Aided NOMA for Millimeter-Wave Massive MIMO With Lens Antenna Array

Enhanced Secure SWIPT in Heterogeneous Network via Intelligent Reflecting Surface

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