Channel Estimation and Low-complexity Beamforming Design for Passive Intelligent Surface Assisted MISO Wireless Energy Transfer

Mishra, Deepak; Johansson, Håkan

doi:10.1109/icassp.2019.8683663

Cited by 583 publications

(540 citation statements)

References 18 publications

Supporting

Mentioning

539

Contrasting

Unclassified

Order By: Relevance

“…, N − 1 (16) each of which depends on the phase-shift vector φ. We aim to optimize the IRS reflection φ for maximizing the average achievable rate in (5), which, however, is non-concave over φ and thus difficult to maximize optimally. Alternatively, we consider to maximize the rate upper bound of (5), which is given by (based on the Jensen's inequality)…”

Section: B Reflection Optimizationmentioning

confidence: 99%

Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization

Zheng¹,

Zhang²

2020

IEEE Wireless Commun. Lett.

851

628

View full text Add to dashboard Cite

In the intelligent reflecting surface (IRS)-enhanced wireless communication system, channel state information (CSI) is of paramount importance for achieving the passive beamforming gain of IRS, which, however, is a practically challenging task due to its massive number of passive elements without transmitting/receiving capabilities. In this letter, we propose a practical transmission protocol to execute channel estimation and reflection optimization successively for an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system. Under the unit-modulus constraint, a novel reflection pattern at the IRS is designed to aid the channel estimation at the access point (AP) based on the received pilot signals from the user, for which the channel estimation error is derived in closedform. With the estimated CSI, the reflection coefficients are then optimized by a low-complexity algorithm based on the resolved strongest signal path in the time domain. Simulation results corroborate the effectiveness of the proposed channel estimation and reflection optimization methods.

show abstract

Section: B Reflection Optimizationmentioning

confidence: 99%

Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization

Zheng¹,

Zhang²

2020

IEEE Wireless Commun. Lett.

851

628

View full text Add to dashboard Cite

show abstract

“…Afterwards, the user feeds back p to the BS andφ to the IRS controller, respectively. 2 It is worth pointing out that during the preparation of this work, we became aware of a related work [15] on the channel estimation for IRS-enhanced systems, which independently proposed a sequential channel estimation method under the frequencyflat channel that requires M + 1 pilot symbols in the training phase. This method can be considered as a special case of our proposed scheme without the grouping.…”

Section: B Processing and Feedbackmentioning

confidence: 99%

Intelligent Reflecting Surface Meets OFDM: Protocol Design and Rate Maximization

Yang

Zheng

Zhang

et al. 2020

IEEE Trans. Commun.

690

581

View full text Add to dashboard Cite

Intelligent reflecting surface (IRS) is a promising new technology for achieving both spectrum and energy efficient wireless communication systems in the future. However, existing works on IRS mainly consider frequency-flat channels and assume perfect knowledge of channel state information (CSI) at the transmitter. Motivated by this, in this paper we study an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system under frequency-selective channels and propose a practical transmission protocol with channel estimation. First, to reduce the overhead in channel training and estimation and to exploit the channel spatial correlation, we propose a novel IRS elements grouping method, where each group consists of a set of adjacent IRS elements that share a common reflection coefficient. Based on this grouping method, we propose a practical transmission protocol where only the combined channel of each group needs to be estimated, thus substantially reducing the training overhead. Next, with any given grouping and estimated CSI, we formulate the problem to maximize the achievable rate by jointly optimizing the transmit power allocation and the IRS passive array reflection coefficients. Although the formulated problem is non-convex and thus difficult to solve, we propose an efficient algorithm to obtain a high-quality suboptimal solution for it, by alternately optimizing the power allocation and the passive array coefficients in an iterative manner, along with a customized method for the initialization.Simulation results show that the proposed design significantly improves the OFDM link rate performance as compared to the case without using IRS. Moreover, it is shown that there exists an optimal size for IRS elements grouping which achieves the maximum achievable rate due to the trade-off between the training overhead and IRS passive beamforming flexibility. Part of this work has been submittedIntelligent reflecting surface (IRS), passive array optimization, power allocation, OFDM, channel estimation. I. INTRODUCTIONThe explosion of mobile data and the ever-increasing demand for higher data rates have continuously driven the advancement of wireless communication technologies in the past decade, such as polar code, massive multiple-input multiple-output (MIMO) and millimeter wave (mmWave) communications, among others. Moreover, a 1000-fold increment in network capacity with ubiquitous connectivity and low latency is envisioned for the forthcoming fifth-generation (5G) wireless network [2]. Meanwhile, the energy efficiency of future wireless networks is expected to be improved by several orders of magnitude so as to maintain the power consumption at increasingly higher data rates. Although massive MIMO and mmWave, seen as the key enablers for 5G, are expected to achieve dramatic spectral efficiency improvements, the deployment of large-scale antenna arrays usually results in high implementation cost and increased power consumption [3]. In addition, combining mmWave with massive MIMO for further performance impro...

show abstract

“…. , K [2]- [5], [7], [12]- [15], [22]. We are the first to analyze the OLP under an arbitrary spatial correlation matrix at the RIS.…”

Section: Ris Design For Full-rank Hmentioning

confidence: 99%

“…Among the very recent hardware technologies that promise significant reduction in the energy consumption of future wireless networks, while realizing unprecedented spectral efficiency gains belong the reconfigurable intelligent surfaces (RIS)s [2]- [15]. RIS is an array of nearly passive, low-cost, reflecting elements with reconfigurable parameters.…”

Section: Introductionmentioning

confidence: 99%

Asymptotic Max-Min SINR Analysis of Reconfigurable Intelligent Surface Assisted MISO Systems

Nadeem

Kammoun

Chaaban

et al. 2020

IEEE Trans. Wireless Commun.

466

426

View full text Add to dashboard Cite

This work focuses on the downlink of a single-cell multi-user system in which a base station (BS) equipped with M antennas communicates with K single-antenna users through a reconfigurable intelligent surface (RIS) installed in the line-of-sight (LoS) of the BS. RIS is envisioned to offer unprecedented spectral efficiency gains by utilizing N passive reflecting elements that induce phase shifts on the impinging electromagnetic waves to smartly reconfigure the signal propagation environment.We study the minimum signal-to-interference-plus-noise ratio (SINR) achieved by the optimal linear precoder (OLP), that maximizes the minimum SINR subject to a given power constraint for any given RIS phase matrix, for the cases where the LoS channel matrix between the BS and the RIS is of rank-one and of full-rank. In the former scenario, the minimum SINR achieved by the RIS-assisted link is bounded by a quantity that goes to zero with K. For the high-rank scenario, we develop accurate deterministic approximations for the parameters of the asymptotically OLP, which are then utilized to optimize the RIS phase matrix. Simulation results show that RISs can outperform half-duplex relays with a small number of passive reflecting elements while large RISs are needed to outperform full-duplex relays.

show abstract

Channel Estimation and Low-complexity Beamforming Design for Passive Intelligent Surface Assisted MISO Wireless Energy Transfer

Cited by 583 publications

References 18 publications

Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization

Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization

Intelligent Reflecting Surface Meets OFDM: Protocol Design and Rate Maximization

Asymptotic Max-Min SINR Analysis of Reconfigurable Intelligent Surface Assisted MISO Systems

Contact Info

Product

Resources

About