Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating devices for efficient utilization of available resources, improving data rates, reducing latency, and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.

A Survey of Device-to-Device Communications: Research Issues and Challenges

A survey on device-to-device (D2D) communication

A wide variety of works have been conducted in vehicle-to-everything (V2X) communications to enable a variety of applications for road safety, traffic efficiency and passenger infotainment. Although dedicated short-range communications (DSRC) based V2X is already in the deployment phase, cellular based V2X is gaining more interest in academia and industry most recently. This article surveys the existing work and challenges on LTE and 5G to support efficient V2X communications. First, we present the motivations for cellular based V2X communications. Second, we summarize the LTE V2X architecture and operating scenarios being considered. Third, we discuss the challenges in existing LTE for supporting V2X communications such as physical layer structure, synchronization, multimedia broadcast multicast services (MBMS), resource allocation, security and survey the recent solutions to these challenges. We further discuss the challenges and possible solutions for 5G based vehicular communications. Finally, we discuss the open research issues and possible research directions in cellular based vehicular communications.

Challenges and Solutions for Cellular Based V2X Communications

Wireless transceivers for mass-market applications must be cost effective. We may achieve this goal by deploying non-ideal low-cost radio frequency (RF) analog components. However, their imperfections may result in RF impairments, including phase noise (PN), carrier frequency offset (CFO), and in-phase (I) and quadrature-phase (Q) imbalance. These impairments introduce in-band and out-of-band interference terms and degrade the performance of wireless systems. In this survey, we present RF-impairment signal models and discuss their impacts. Moreover, we review RF-impairment estimation and compensation in single-carrier (SC) and multicarrier systems, especially orthogonal frequency division multiplexing (OFDM). Furthermore, we discuss the effects of the RF impairments in already-established wireless technologies, e.g., multiple-input multiple-output (MIMO), massive MIMO, full-duplex, and millimeter-wave communications and review existing estimation and compensation algorithms. Finally, future research directions investigate the RF impairments in emerging technologies, including cell-free massive MIMO communications, non-orthogonal multicarrier systems, non-orthogonal multiple access (NOMA), ambient backscatter communications, and intelligent reflecting surface (IRS)-assisted communications. Furthermore, we discuss artificial intelligence (AI) approaches for developing estimation and compensation algorithms for RF impairments.

/pdf/rf-impairments-in-wireless-transceivers-phase-noise-cfo-and-4c7v2xn92t.pdf

RF Impairments in Wireless Transceivers: Phase Noise, CFO, and IQ Imbalance – A Survey

Sensors and smartphones are used in industry and healthcare technology for data gathering. The sensed data can be acquired by devices and processed through multiple gateways to the Internet of things (IoT) enabled cloud framework. Device-to-device (D2D) communication paradigm is a central part of the third generation partnership project standards to facilitate peer-to-peer connectivity that will be an important part of IoT. There is no centralized control in D2D which strengthens the wireless networks more energy-efficient and spectrum. The D2D enhances the data transmission process with advance security schemes and also improves the quality of service. This paper surveyed recent works on D2D, which is mainly focused on resource allocation, power consumption, security, and also highlights the major challenges. The role of D2D communication systems in healthcare has been discussed here.

A Comprehensive Review on Device-to-Device Communication Paradigm: Trends, Challenges and Applications

In this paper, we study widely linear precoding techniques to mitigate in-phase/quadrature-phase (IQ) imbalance (IQI) in the downlink of large-scale multiple-input multiple-output (MIMO) systems. We adopt a real-valued signal model, which considers the IQI at the transmitter, and then develop widely linear zero-forcing (WL-ZF), widely linear matched filter, widely linear minimum mean-squared error, and widely linear block-diagonalization (WL-BD) type precoding algorithms for both single- and multiple-antenna users. We also present a performance analysis of WL-ZF and WL-BD. It is proved that without IQI, WL-ZF has exactly the same multiplexing gain and power offset as ZF, while when IQI exists, WL-ZF achieves the same multiplexing gain as ZF with ideal IQ branches, but with a minor power loss, which is related to the system scale and the IQ parameters. We also compare the performance of WL-BD with BD. The analysis shows that with ideal IQ branches, WL-BD has the same data rate as BD, while when IQI exists, WL-BD achieves the same multiplexing gain as BD without IQ imbalance. Numerical results verify the analysis and show that the proposed widely linear type precoding methods significantly outperform their conventional counterparts with IQI and approach those with ideal IQ branches.

Widely Linear Precoding for Large-Scale MIMO with IQI: Algorithms and Performance Analysis

In this letter, we propose pilot reuse among device-to-device (D2D) users (DUs) in a D2D underlay massive MIMO system to shorten pilot overhead. First, we derive a lower bound on the average signal-to-interference-plus-noise ratio of DUs. Then, a revised graph coloring-based pilot allocation (RGCPA) algorithm is proposed to mitigate the pilot contamination. Finally, a power control problem to minimize D2D links’ data transmit power is formulated and an iterative scheme is adopted to solve the problem. The simulation results show that pilot overhead can be shortened greatly by pilot reuse, and the effect of pilot contamination can be almost cancelled using the proposed RGCPA algorithm. In addition, the power control scheme converges rapidly.

Pilot Allocation and Power Control in D2D Underlay Massive MIMO Systems

To analyze the performance of orthogonal matching pursuit (OMP)-based compressed channel estimation (CCE) with deterministic pilot patterns, we propose a mathematical framework by defining four normalized mean square errors ( $\textrm {NMSE}_{\textrm s}$ ): the total NMSE ( $\textrm {NMSE}_{\textrm T}$ ), the NMSE on dominant channel components ( $\textrm {NMSE}_{\textrm D}$ ), the NMSE caused by “lost errors” ( $\textrm {NMSE}_{\textrm L}$ ), and the NMSE caused by “false alarms” ( $\textrm {NMSE}_{\textrm F}$ ). Then, we derive a formula with a closed form for evaluating the upper bound of $\textrm {NMSE}_{\textrm D}$ in the ideal case ( $\textrm {NMSE}_{\textrm {D,UB}}$ ). Using the proposed analytical framework, the main findings include: 1) the $\textrm {NMSE}_{\textrm {D,UB}}$ is determined by the following four parameters: the deterministic pilot pattern, the maximum Doppler shift, the number of dominant multipath components, and the SNR; 2) the $\textrm {NMSE}_{\textrm {D,UB}}$ can be viewed as an approximation of practical ${\textrm {NMSE}_{\textrm T}}$ in the case that the probability of the successes of OMP exceeds a certain threshold, in which both $\textrm {NMSE}_{\textrm L}$ and $\textrm {NMSE}_{\textrm F}$ are neglectable; and 3) using linear regression models, the practical bit-error-rate performance also can be predicted well based on the proposed $\textrm {NMSE}_{\textrm {D,UB}}$ . We believe that the proposed framework provides a useful tool for adaptively optimizing pilot parameters according to rapidly time-varying channel conditions when using OMP-based CCEs in mobile OFDM systems.

Performance Analysis of OMP-Based Channel Estimations in Mobile OFDM Systems

High peak-to-average power ratio (PAPR) is an inherit drawback of orthogonal frequency-division multiplexing (OFDM) systems, and it limits the use of OFDM technology. In all the PAPR reduction methods, digital clipping is probably the simplest one and it is very effective in the solution of the PAPR problem in OFDM systems. However, clipping introduces additional distortion, which degrades the performance of channel estimation and signal detection. In this paper, the performance of channel estimation using the simple least square (LS) method in OFDM systems with a clipping operation is analyzed, a decision-aided channel estimation method to mitigate the clipping distortion is developed, and the potential gain in channel estimation of the decision-aided method is derived theoretically. Simulation results show that, in clipped OFDM, the theoretical potential gain in channel estimation can be obtained by a few iterations of an iterative decision-aided channel estimation and signal detection process, and, simultaneously, the performance of signal detection is effectively improved

Iterative channel estimation and signal detection in clipped OFDM

In this paper we study widely-linear precoding techniques to mitigate in-phase/quadrature-phase (IQ) imbalance (IQI) in the downlink of large-scale multiple-input multiple-output (MIMO) systems. We adopt a real-valued signal model which takes into account the IQI at the transmitter and then develop widely-linear zero-forcing (WL-ZF), widely-linear matched filter (WL-MF), widely-linear minimum mean-squared error (WL-MMSE) and widely-linear block-diagonalization (WL-BD) type precoding algorithms for both {\color{red} single- and multiple-antenna users.} We also present a performance analysis of WL-ZF and WL-BD. It is proved that without IQI, WL-ZF has exactly the same multiplexing gain and power offset as ZF, while when IQI exists, WL-ZF achieves the same multiplexing gain as ZF with ideal IQ branches, but with a minor power loss which is related to the system scale and the IQ parameters. We also compare the performance of WL-BD with BD. The analysis shows that with ideal IQ branches, WL-BD has the same data rate as BD, while when IQI exists, WL-BD achieves the same multiplexing gain as BD without IQ imbalance. Numerical results verify the analysis and show that the proposed widely-linear type precoding methods significantly outperform their conventional counterparts with IQI and approach those with ideal IQ branches.

Bingyang Wu

Papers

Widely Linear Precoding for Large-Scale MIMO with IQI: Algorithms and Performance Analysis

Pilot Allocation and Power Control in D2D Underlay Massive MIMO Systems

Performance Analysis of OMP-Based Channel Estimations in Mobile OFDM Systems

Iterative channel estimation and signal detection in clipped OFDM

Widely-Linear Precoding for Large-Scale MIMO with IQI: Algorithms and Performance Analysis