Device-to-Device mmWave Communication in the Presence of Interference and Hardware Distortion Noises

Tlebaldiyeva, Leila; Maham, Behrouz; Tsiftsis, Theodoros A.

doi:10.1109/lcomm.2019.2922905

Cited by 27 publications

(17 citation statements)

References 17 publications

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“…In [1], the authors investigated the effect of AHWD on the performance of a dual-hop relay with both amplify-and-forward and decodeand-forward protocols, and derived closed-form expressions for the outage probabilities, as well as an upper bound for the ergodic capacity. The outage probability for a device-todevice millimeter wave communication system with complex proper AHWD was derived in [2]. However, AHWD may be, in general, improper due to I/Q imbalance 1 [3]- [5], [43]- [47].…”

Section: A Related Workmentioning

confidence: 99%

Improper Gaussian Signaling for the $K$-User MIMO Interference Channels With Hardware Impairments

Soleymani

Santamarı́a

Schreier

2020

IEEE Trans. Veh. Technol.

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This paper investigates the performance of improper Gaussian signaling (IGS) for the K-user multiple-input, multiple-output (MIMO) interference channel (IC) with hardware impairments (HWI). HWI may arise due to imperfections in the devices like I/Q imbalance, phase noise, etc. With I/Q imbalance, the received signal is a widely linear transformation of the transmitted signal and noise. Thus, the effective noise at the receivers becomes improper, which means that its real and imaginary parts are correlated and/or have unequal powers. IGS can improve system performance with improper noise and/or improper interference. In this paper, we study the benefits of IGS for this scenario in terms of two performance metrics: achievable rate and energy efficiency (EE). We consider the rate region, the sum-rate, the EE region and the global EE optimization problems to fully evaluate the IGS performance. To solve these non-convex problems, we employ an optimization framework based on majorizationminimization algorithms, which allow us to obtain a stationary point of any optimization problem in which either the objective function and/or constraints are linear functions of rates. Our numerical results show that IGS can significantly improve the performance of the K-user MIMO IC with HWI and I/Q imbalance, where its benefits increase with the number of users, K, and the imbalance level, and decrease with the number of antennas.

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Section: A Related Workmentioning

confidence: 99%

Improper Gaussian Signaling for the $K$-User MIMO Interference Channels With Hardware Impairments

Soleymani

Santamarı́a

Schreier

2020

IEEE Trans. Veh. Technol.

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“…All the aforementioned studies considered perfect radio frequency (RF) elements at the transceivers. This assumption is not practical as in real-time communication all transceivers experience different types of hardware impairments (HIs) [45], e.g., in-phase/quadrature imbalance, amplifier nonlinearities, quantization error, phase noise, etc. Despite there are exist several algorithms to mitigate the effect of such HIs, some residual transceiver hardware impairments (RTHIs) caused by various kinds of noise and inaccurate calibration can not be eliminated [46].…”

Section: ) Residual Transceiver Hardware Impairmentsmentioning

confidence: 99%

“…is the aggregated distortion noise from transceiver; ϕ (•) = ϕ 2 t + ϕ 2 r represents the aggregate HI level from the transmitter and receiver. In practice, this level can be measured by the error vector magnitude (EVM) [45]; n (•) ∼ CN (0, σ 2 (•) ) is the additive white Gaussian noise (AWGN) term at each receive node; L P and x P are the transmit power and the message of P T , respectively.…”

Section: B Transmission Protocolmentioning

confidence: 99%

Hardware- and Interference-Limited Cognitive IoT Relaying NOMA Networks With Imperfect SIC Over Generalized Non-Homogeneous Fading Channels

et al. 2020

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Internet-of-Things (IoT) technology has received much attention due to its great potential to interconnect billions of devices in a broad range of applications. IoT networks can provide high-quality services for a large number of users and smart objects. On the other hand, massive connectivity in IoT networks brings problems associated with spectral congestion. This issue can be solved by applying cognitive radio (CR) and non-orthogonal multiple access (NOMA) techniques. In this respect, this paper studies the performance of cooperative CR-NOMA enabled IoT networks over a generalized α − µ fading channel model. Closed-form analytical expressions of the end-to-end outage probability (OP) for the secondary NOMA users are derived using the Meijer's G-function with a consideration of the impacts of the interference temperature constraint, primary interference, residual hardware impairments and imperfect successive interference cancellation. Moreover, to acquire some useful insights on the system performance, asymptotic closed-form OP expressions are provided. Additionally, the impact of α and µ fading parameters on the outage performance is examined and, as a result, it is concluded that the system performance sufficiently improves as α and/or µ increase. Furthermore, the outage performance of the proposed system model is shown to outperform that of an identical IoT network operating on orthogonal multiple access. Finally, the provided closed-form OP expressions are validated with Monte Carlo simulations. INDEX TERMS α − µ fading, cognitive radio (CR), cooperative communications, Internet-of-Things (IoT), non-homogeneous generalized fading, non-orthogonal multiple access (NOMA), outage probability (OP).

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“…The performance of various single antenna interferencelimited systems with imperfect devices has been studied in several works [3]- [5]. For example, the paper [3] derived the rate region of a 2-user SISO interference channel (IC) in the presence of additive asymmetric HWD.…”

Section: Introductionmentioning

confidence: 99%

“…The performance of dual-hop relaying with additive HWD is studied in [4]. In [5], the authors studied a device-to-device millimeter wave communication system with HWD under Nakagami-m fading channel and derived the outage probability of the system. HWD can be more harmful in multiple-antenna systems, and HWD-aware schemes are anticipated to play a key role in next generations of multiple-antenna systems [6]- [13], [15].…”

Section: Introductionmentioning

confidence: 99%

Rate Region of the K-user MIMO Interference Channel with Imperfect Transmitters

Soleymani

Santamarı́a

Maham

et al. 2021

2020 28th European Signal Processing Conference (EUSIPCO)

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This paper studies the rate region of a multipleinput, multiple-output (MIMO) system with imperfect transmitters when interference is treated as noise at the receiver side. We consider a K-user MIMO interference channel (IC) in which the transmitters suffer from an additive hardware distortion (HWD) modeled as spatially uncorrelated Gaussian noise with covariance matrix proportional to the transmit covariance matrix. We employ the difference of convex programming (DCP) technique to solve the rate-region optimization problem and obtain its stationary points. Our proposed HWD-aware algorithm outperforms the HWD-unaware design that disregards HWD. Our results show that the performance of the K-user MIMO IC is highly affected by HWD, especially in high signal-to-noise-ratio scenarios. Index Terms-Achievable rate region, additive hardware distortions, difference of convex programming, interference channel, MIMO systems.

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Device-to-Device mmWave Communication in the Presence of Interference and Hardware Distortion Noises

Cited by 27 publications

References 17 publications

Improper Gaussian Signaling for the $K$-User MIMO Interference Channels With Hardware Impairments

Improper Gaussian Signaling for the $K$-User MIMO Interference Channels With Hardware Impairments

Hardware- and Interference-Limited Cognitive IoT Relaying NOMA Networks With Imperfect SIC Over Generalized Non-Homogeneous Fading Channels

Rate Region of the K-user MIMO Interference Channel with Imperfect Transmitters

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