Constant Envelope Precoding by Interference Exploitation in Phase Shift Keying-Modulated Multiuser Transmission

Amadori, Pierluigi Vito; Masouros, Christos

doi:10.1109/twc.2016.2626279

Cited by 92 publications

(75 citation statements)

References 39 publications

(77 reference statements)

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“…According to S-procedure, we need to guarantee the derivation in (27) hold as the premise for guaranteeing the first inequality in (24) always hold, which can be given as…”

Section: ) Problem Formulationmentioning

confidence: 99%

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Device-Centric Distributed Antenna Transmission: Secure Precoding and Antenna Selection With Interference Exploitation

Wei

Masouros

2020

IEEE Internet Things J.

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We address physical layer security in distributed antenna (DA) systems, where eavesdroppers (Eves) can intercept the information transmitted for the intended receiver (IR). To realize a user-centric, powerefficient and physical layer security-addressing system, we aim at minimizing total power consumption by jointly designing DA selection and secure precoding. Different from the conventional artificial noise (AN)-aided secure transmission, where AN is treated as an undesired element for the IR, we design AN such that it is constructive to the IR while keeping destructive to the Eves. Importantly, we investigate two practical scenarios, where the IR and Eves' channel state information (CSI) is imperfectly obtained or the Eves' CSI is completely unknown. To handle the CSI uncertainties, we solve the problems in probabilistic and deterministic robust optimization respectively, both satisfying the IR' signal-tointerference-and-ratio (SINR) requirement by use of constructive AN and addressing security against the Eves. Simulation results demonstrate our algorithms consume much less power compared to the centralized antenna (CA) systems with/without antenna selection, as well as the DA systems with conventional AN processing. Last but not least, by the proposed algorithms, the activation of DAs closely relates to users' locations and quality-of-service (QoS) requirements, featuring a user-centric and on-demand structure. 2 I. INTRODUCTION Wireless Communications for the future Internet of Things (IoT) and Industry 4.0 are required to provide power-efficient transmission together with high security level [1]. In the last decade, centralized multiple-input multiple-output (MIMO) has been considered as a potential technique due to its high throughput [2] and additional spatial diversity for enhancing physical layer security [3]. However, it requires extremely high power consumption caused by the fully activated antennas, and centralized MIMO often suffers from an equal level of path loss (PL) from the antenna array to one user caused by the co-located antenna (CA) deployment [4]. Besides, edge users in CA deployment may not be well served due to the severe propagation attenuation, otherwise significant transmission power is required for compensating the propagation loss. To create a user-centric and power efficient structure necessary for the IoT and Industry 4.0, distributed antenna (DA) systems have attracted much attention [5]. By geographically distributing the antennas and hence placing them closer to users, DA systems can reduce the PL impact and obtain blockage-free effect and also facilitate an on-demand network structure by activating those DAs contributing the most. The concepts of user-centric DA are particularly suited for communications in industrial environments, where antennas can be carefully planned and distributed in the ceilings of large factories to effectively extend network coverage without crucial increment of power consumption, and are therefore a key contender for industry IoT and Industry 4.0 ...

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“…According to S-procedure, we need to guarantee the derivation in (27) hold as the premise for guaranteeing the first inequality in (24) always hold, which can be given as…”

Section: ) Problem Formulationmentioning

confidence: 99%

“…By applying S-procedure, the derivation in (27) holds if and only if there exists λ such that the LMI constraint in (28) holds 1…”

Section: ) Problem Formulationmentioning

confidence: 99%

Device-Centric Distributed Antenna Transmission: Secure Precoding and Antenna Selection With Interference Exploitation

Wei

Masouros

2020

IEEE Internet Things J.

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“…In [3] and [4], a full study for the feasibility of CE precoding in single-user MISO channels was done and an optimal phase recovery algorithm for CE precoding was proposed in [4]. Subsequently, the concept of CE precoding was extended for multiuser MISO [5][6][7][8][9] and point-to-point MIMO [10]. In particular, the works [5,6] and [7] studied the multiuser interference (MUI) power minimization by CE precoding under frequency-flat channel and frequencyselective channel, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, the works [5,6] and [7] studied the multiuser interference (MUI) power minimization by CE precoding under frequency-flat channel and frequencyselective channel, respectively. In addition to MUI reduction, the concept of constructive interference using CE precoding is investigated in [8] for PSK modulations; cross-entropy and convex relaxation methods are proposed to handle the CE problem. The joint optimization of CE precoding and receive beamforming is considered for a single-user MIMO system in [10].…”

Section: Introductionmentioning

confidence: 99%

Minimum Symbol Error Rate-Based Constant Envelope Precoding for Multiuser Massive Miso Downlink

Shao

et al. 2018

2018 IEEE Statistical Signal Processing Workshop (SSP)

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This paper considers the problem of constant envelope (CE) precoder designs for multiuser massive MISO downlink channels. The use of CE signals allows one to employ low-cost radio frequency chains and thereby facilitates the implementation of massive MIMO. However, the subsequent CE precoder designs are usually challenging owing to the non-convex CE constraints. The existing CE precoder designs consider minimization of some measures on the distortion levels of the received symbols, and they usually aim at improving the symbol-error rate (SER) performances. In this paper we formulate a minimum SER-based design for CE precoding. The design formulation is non-convex and we propose two low-complexity first-order algorithms using gradient projection. Curiously, our simulation results show that the proposed designs can achieve bit-error rate performance close to that of zero-forcing beamforming without CE signaling restrictions.Index Termsmassive MIMO, constant envelope, symbol error rate, non-convex projected gradient

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“…Such notion is known as constructive interference or symbol-level precoding. Some recent works begin to exploit specific symbol constellations in one-bit and CE precoding [23][24][25]. A few most recent works take a more systematic approach by working on SEP directly [7,[26][27][28].…”

mentioning

confidence: 99%

A Framework for One-Bit and Constant-Envelope Precoding Over Multiuser Massive MISO Channels

Shao

et al. 2019

IEEE Trans. Signal Process.

102

113

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Consider the following problem: A multi-antenna base station (BS) sends multiple symbol streams to multiple single-antenna users via precoding. However, unlike conventional multiuser precoding, the transmitted signals are subjected to binary, unit-modulus, or even discrete unitmodulus constraints. Such constraints arise in the one-bit and constant-envelope (CE) massive MIMO scenarios, wherein high-resolution digital-to-analog converters (DACs) are replaced by one-bit DACs and phase shifters, respectively, for cutting down hardware cost and energy consumption. Multiuser precoding under one-bit and CE restrictions poses significant design difficulty. In this paper we establish a framework for designing multiuser precoding under the one-bit, continuous CE and discrete CE scenarios-all within one theme. We first formulate a precoding design that focuses on minimization of the symbol-error probabilities (SEPs), assuming quadrature amplitude modulation (QAM) symbol constellations. We then devise an algorithm for our SEP-based design. The algorithm combines i) a novel penalty method for handling binary, unit-modulus and discrete unit-modulus constraints; and ii) a first-order nonconvex optimization recipe custom-built for the design. Specifically, the latter is an inexact majorization-minimization method via accelerated projected gradient, which, as shown by simulations, runs very fast and can handle a large number of decision variables. Simulation results indicate that the proposed design offers significantly better bit-error rate performance than the existing designs.

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Constant Envelope Precoding by Interference Exploitation in Phase Shift Keying-Modulated Multiuser Transmission

Cited by 92 publications

References 39 publications

Device-Centric Distributed Antenna Transmission: Secure Precoding and Antenna Selection With Interference Exploitation

Device-Centric Distributed Antenna Transmission: Secure Precoding and Antenna Selection With Interference Exploitation

Minimum Symbol Error Rate-Based Constant Envelope Precoding for Multiuser Massive Miso Downlink

A Framework for One-Bit and Constant-Envelope Precoding Over Multiuser Massive MISO Channels

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