Broad Coverage Precoding Design for Massive MIMO With Manifold Optimization

Guo, Weiran; Lu, An-An; Meng, Xiangxu; Gao, Xiqi; Ma, Ni

doi:10.1109/tcomm.2018.2890263

Cited by 26 publications

(15 citation statements)

References 35 publications

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“…The obtained optimization problem is over the intersection of two manifolds. The problem ( 45 ) can also be used to design the broad coverage precoder for ULAs, which has been investigated in [ 17 ] with a different objective function based on manifold optimization. It has also been investigated in [ 13 ] with

being changed to the objective function for omnidirectional precoding.…”

Section: Broad Coverage Precoding Matrix Design For Upasmentioning

confidence: 99%

“…In practical systems, omnidirectional precoding might cause interference with other cells or sectors. To solve this problem, broad coverage precoding is proposed in [ 17 ]. It is designed for massive MIMO with ULAs based on manifold optimization under the per-antenna constant power and semi-unitary constraints.…”

Section: Introductionmentioning

confidence: 99%

“…It is designed for massive MIMO with ULAs based on manifold optimization under the per-antenna constant power and semi-unitary constraints. By considering the synchronization performance, the work in [ 17 ] is then extended to [ 18 , 19 ] for broad coverage precoder design for three-dimensional (3D) massive MIMO in terrestrial and satellite communication systems, respectively. However, as the size of antennas is still increasing, the complexity of the broad coverage precoder design for massive MIMO with a large number of antennas will be a problem.…”

Section: Introductionmentioning

confidence: 99%

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Broad Coverage Precoding for 3D Massive MIMO with Huge Uniform Planar Arrays

Chen

Gao

2021

Entropy

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In this paper, we propose a novel broad coverage precoder design for three-dimensional (3D) massive multi-input multi-output (MIMO) equipped with huge uniform planar arrays (UPAs). The desired two-dimensional (2D) angle power spectrum is assumed to be separable. We use the per-antenna constant power constraint and the semi-unitary constraint which are widely used in the literature. For normal broad coverage precoder design, the dimension of the optimization space is the product of the number of antennas at the base station (BS) and the number of transmit streams. With the proposed method, the design of the high-dimensional precoding matrices is reduced to that of a set of low-dimensional orthonormal vectors, and of a pair of low-dimensional vectors. The dimensions of the vectors in the set and the pair are the number of antennas per column and per row of the UPA, respectively. We then use optimization methods to generate the set of orthonormal vectors and the pair of vectors, respectively. Finally, simulation results show that the proposed broad coverage precoding matrices achieve nearly the same performance as the normal broad coverage precoder with much lower computational complexity.

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being changed to the objective function for omnidirectional precoding.…”

Section: Broad Coverage Precoding Matrix Design For Upasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Broad Coverage Precoding for 3D Massive MIMO with Huge Uniform Planar Arrays

Chen

Gao

2021

Entropy

Self Cite

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“…In this paper, it is assumed that the direct link between the AP and the user or eavesdropper is blocked by obstacles [43], [13]. In addition, we assume that the eavesdropper is active, thus the eavesdropper's channel is known at the AP [42].…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

Secure Wireless Transmission for Intelligent Reflecting Surface-Aided Millimeter-Wave Systems

Xiu

Zhang

2020

IEEE Access

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Due to the broadcast nature of millimeter wave (mmWave) communications, physical layer security has always been a fundamental but challenging concern. Fortunately, the recent advance of intelligent reflecting surface (IRS) introduces another dimension for mmWave secure communications by reconfiguring the transmission environments. In this paper, we investigate the physical layer security issue for IRS-aided mmWave communications. Specifically, two scenarios are considered, i.e., with and without the knowledge of the eavesdropper's channel. When the eavesdropper's channel is known, under the unit modulus constraints at the IRS and the transmit power constraint at the access point (AP), the secrecy rate is maximized by jointly designing the beamforming vector of the AP and the phase shifts of the IRS. We propose an alternating optimization algorithm for improving the secrecy rate to solve the non-convex optimization problem. In particular, the phase shift matrix of the IRS is firstly optimized based on the manifold optimization algorithm. Under the given phase shift matrix of the IRS, the original problem is transformed into a difference of convex (DC) programming problem. To solve this problem, we use the successive convex approximation (SCA)-based method to transform the original problem into a convex approximation problem, and the transmit beamforming vector is obtained by solving the convex approximation problem. In addition, when the eavesdropper's channel is unknown, under the transmit power constraint and the minimum user rate constraint, an artificial-noise (AN)-aided scheme is proposed to jam the eavesdropper by maximizing the AN power. Numerical results evaluate that the performance of our proposed schemes is better than that of the conventional scheme in terms of secrecy rate. Moreover, simulations also demonstrate that the secrecy behaviors of the IRS-aided mmWave communication system are superior to the mmWave communications without IRS.

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“…The IRS is configured to facilitate communica-tion between APs and users. In addition, the eavesdropper's channel is known at the AP, which is effective when the eavesdropper is active [28].…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

Wireless Secure Signal Transmission for Distributed Intelligent Surface-Aided Millimeter Wave Systems

Xiu

Zhang

2020

IEEE Access

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The optimization of the secrecy rate of the distributed intelligent reflecting surfaces (IRSs)assisted millimeter wave (mmWave) communication system is studied in this paper. In this system, the users are served by multiple IRSs, and by adjusting the switch state of each IRS and optimizing the phase shift of the IRS to maximize the secrecy rate of the system. The problem is described as a joint IRS control, transmit beamforming design problem. Our objective is to maximize the secrecy rate of the distributed IRSs-aided system under the transmit power constraint of the access point (AP). Since the problem is nonconvex, one alternating optimization algorithm is proposed for solving this problem. We use the successive convex approximation (SCA) algorithm to solve it, and the solution that is obtained by the SCA algorithm guarantees to converge to a stable point that satisfies the Karush-Kuhn-Tucker (KKT) conditions. Moreover, by using the dual method, we obtain the IRS switch. For the IRS phase shifts optimization problem, a lowcomplexity majorization-minimization (MM) algorithm is used to solve this problem. Numerical results show that the proposed scheme can achieve higher secrecy rate compared with the single IRS-aided scheme.

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Broad Coverage Precoding Design for Massive MIMO With Manifold Optimization

Cited by 26 publications

References 35 publications

Broad Coverage Precoding for 3D Massive MIMO with Huge Uniform Planar Arrays

Broad Coverage Precoding for 3D Massive MIMO with Huge Uniform Planar Arrays

Secure Wireless Transmission for Intelligent Reflecting Surface-Aided Millimeter-Wave Systems

Wireless Secure Signal Transmission for Distributed Intelligent Surface-Aided Millimeter Wave Systems

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