Down-Conversion Gilbert Cell Mixer Design for 5G Wireless Communications Systems

With the improvement of mobile communication technologies and their broad applications, mobile communication will have more impact on our life. Such systems will support a variety of personal communication services with high-data rate and very low latency applications. To achieve such demands, many proposals associated with the development of 5G identify a set of requirements for which different technological directions are independently emerging. One direction is utilizing the millimeter-wave (mm-Wave) frequency bands where more spectrums are available. Millimeter-wave frequencies offer the advantage of physically smaller components that results in cost-effective RF transceivers and feasible large-scale integrated phased arrays. The smart RF transceivers of 5G along with the potential high-frequency innovative designs must satisfy the growing consumer and technology requirements. This implies utilizing the state-of-the-art guiding structures, especially printed ridge gap waveguide (PRGW), that have low loss and minimal dispersion compared with traditional PCB-based structures. The present chapter focuses on the necessary components for a beamforming antenna system which is implemented using PRGW technology. Millimeter wave antennas with different polarizations have been addressed. Power combining and dividing components have been also developed. These components have been used for integration in a complete beamforming antenna system working at an mm-Wave frequency band.

This letter presents a low-noise and high-gain CMOS mixer that uses a simple dynamic current-bleeding (DCB) technique. The conventional static current-bleeding (SCB) technique has high conversion gain and low noise figure at a high intermediate frequency (IF) but also has moderately high direct-mechanism flicker noise. Meanwhile, the conventional DCB technique possesses completely opposite characteristics. The proposed DCB technique obtains not only low direct flicker noise and low noise figure at high IF, but also has high conversion gain by combining only the advantageous features of both conventional techniques. Measurement results show a conversion gain of 21.2 dB and a noise figure of 16.3 dB at 10 kHz and 5.6 dB at 10 MHz, while the mixer consumes 4.2 mW at a 1.2 V supply voltage. It was implemented in a 0.11-μm CMOS process with a chip area of 0.8 × 0.8 mm2. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1267–1271, 2017

The millimeter-wave (mm-wave) frequency band has emerged as a means to overcome current radio frequency spectral limitations and represents an interesting solution to fulfill the bandwidth and networking requirements of fifth generation (5G) mobile communications and beyond. Photonic generation of these frequencies holds advantages over electronic methods in terms of cost and effective network distribution. Due to their coherent nature, optical frequency combs (OFC) are a promising solution for the efficient generation of mm-wave frequencies. The work outlined examines the use of OFCs in a mm-wave radio-over-fiber (RoF) heterodyne system with regard to the specific requirements of a 5G candidate waveform, universally filtered orthogonal frequency division multiplexing. Through experimentation and simulation, the key limitations of linewidth, effective path length difference, and relative intensity noise (RIN) are explored. Results are presented, in terms of error vector magnitude (EVM), for a wide range of system parameters highlighting important considerations to be taken in designing future mm-wave RoF systems employing OFCs. Performance of $\sim$ 5% EVM using single sideband modulation is achieved for optimized system conditions and an RIN level of $-$ 132 dB/Hz.

Unlimited access to information and data sharing wherever and at any time for anyone and anything is a fundamental component of fifth-generation (5G) wireless communication and beyond. Therefore, it has become inevitable to exploit the super-high frequency (SHF) and millimeter-wave (mmWave) frequency bands for future wireless networks due to their attractive ability to provide extremely high data rates because of the availability of vast amounts of bandwidth. However, due to the characteristics and sensitivity of wireless signals to the propagation effects in these frequency bands, more accurate path loss prediction models are vital for the planning, evaluating, and optimizing future wireless communication networks. This paper presents and evaluates the performance of several well-known machine learning methods, including multiple linear regression (MLR), polynomial regression (PR), support vector regression (SVR), as well as the methods using decision trees (DT), random forests (RF), K-nearest neighbors (KNN), artificial neural networks (ANN), and artificial recurrent neural networks (RNN). RNNs are mainly based on long short-term memory (LSTM). The models are compared based on measurement data to provide the best fitting machine-learning-based path loss prediction models. The main results obtained from this study show that the best root-mean-square error (RMSE) performance is given by the ANN and RNN-LSTM methods, while the worst is for the MLR method. All the RMSE values for the given learning techniques are in the range of to dB. Furthermore, this work shows that the models (except for the MLR model) perform excellently in fitting actual measurement data for wireless communications in enclosed indoor environments since they provide R-squared and correlation values higher than and , respectively. The paper shows that these learning methods could be used as accurate and stable models for predicting path loss in the mmWave frequency regime.

The millimeter-wave (mm-Wave) frequency band ~30-300 GHz has received significant attention lately as a prospective band for 5G systems. Millimeter-wave frequencies have traditionally been used for backhaul, satellite and other fixed services. While these bands offer substantial amount of bandwidth and opportunity for spatial multiplexing, the propagation characteristics for terrestrial mobile usage need to be fully understood prior to system design. Towards this end, this paper presents preliminary indoor measurement results obtained using a channel sounder equipped with omni- and directional antennas at 2.9 GHz and 29 GHz as a comparative study of the two bands. The measurements are made within a Qualcomm building in Bridgewater, NJ, USA, for two separate floors, each representing a different yet representative type of office plan. We present measurements and estimated parameters for path loss, excess delay, RMS delay and analyze the power profile of received paths. In addition, we present several spherical scans of particular links to illustrate the 3-D angular spread of the received paths. This work represents initial results of an ongoing effort for comprehensive indoor and outdoor channel measurements. The measurements presented here, along with cited references, offer interesting insights into propagation conditions (e.g. loss, delay/angular spread etc.), coverage and robustness for mobile use of millimeter-wave bands. We believe additional extensive measurement campaigns in diverse settings by academia and industry would help facilitate the generation of usable channel models.

The fifth generation of wireless communications (5G) promises massive increases in traffic volume and data rates, as well as improved reliability in voice calls. Jointly optimizing beamforming, power control, and interference coordination in a 5G wireless network to enhance the communication performance to end users poses a significant challenge. In this paper, we formulate the joint design of beamforming, power control, and interference coordination as a non-convex optimization problem to maximize the signal to interference plus noise ratio (SINR) and solve this problem using deep reinforcement learning. By using the greedy nature of deep Q-learning to estimate future rewards of actions and using the reported coordinates of the users served by the network, we propose an algorithm for voice bearers and data bearers in sub-6 GHz and millimeter wave (mmWave) frequency bands, respectively. The algorithm improves the performance measured by SINR and sum-rate capacity. In realistic cellular environments, the simulation results show that our algorithm outperforms the link adaptation industry standards for sub-6 GHz voice bearers. For data bearers in the mmWave frequency band, our algorithm approaches the maximum sum-rate capacity, but with less than 4% of the required run time.

The fifth-generation (5G), now being developed for use in the millimeter-wave (mm-wave) frequency bands, would enhance the Quality of Service (QoS) for the Mobile User (MU) in the near future. Despite the advantages of using mm-wave communications that are attained through the large bandwidth available in this band, it suffers from high penetration loss and low diffraction, which causes very high attenuation of the signal in free space. The attenuation of the signal can also be due to the blockages, such as buildings, human presence, vehicles, etc. As a result, the signal propagation path could be interrupted by those blockages causing significant fluctuation in the handover (HO) rate. Thus, the foreseen mm-wave communication gains are achieved at the expense of varying HO rates. Therefore, the impact of blockages on the HO rate for user mobility is a crucial performance factor that needs to be analyzed and addressed in mm-wave cellular communication systems. This paper analyses the impact of static blockage on the HO rate for a MU in the 5G mm-wave cellular network. We began by obtaining the impact of blockage with a fixed location in the 2-D plane on the HO rate for a MU moving radially away from the mm-wave base station (BS) at a certain speed. Afterward, we considered the MU moving in a uniform angle with a certain speed in the mm-wave cellular network. The mm-wave BSs, in this study, have been assumed to be distributed according to a homogeneous Poisson Point Process (PPP). The results show that the blockage has a remarkable impact on the HO rate, depending significantly on its location, and MU's direction and speed.

Multiple-input multiple-output (MIMO) is considered as the key technology for 5G wireless communications networks. In the millimeter-wave (mmWave) frequency bands, directional beamforming is essential to the establishment of an efficient radio link for signal transmission. However, in wireless mobile environments, the effective beam direction is generally unavailable in the initial access phase. Hence, beam alignment (BA) is crucial for link establishment in initial access. In this work, we propose an efficient BA technique, referred to as the multi-modal pattern BA scheme, to improve the performance and efficiency of initial access in massive MIMO systems. Unlike the conventional sequential search scheme using single-modal patterns, the transmission of synchronization signals in the proposed scheme is based on the use of multi-modal patterns, each of which specifies multiple main lobes with distinguishable directions. Incomparison with the conventional scheme, our scheme can greatly enhance the achieved angular resolution after BA under the use of a fixed number of synchronization signals. As a result, the signal-to-noise ratio (SNR) of the established link is significantly improved. By contrast, if the same angular resolution is desired, the proposed scheme can greatly reduce the number of required synchronization signals to conserve the radio resources, including transmission power and bandwidth, and to decrease the searching delay in the BA procedure. In addition, considering multi-modal pattern construction for the transmission using a single radio-frequency (RF) chain, we propose an effective approach to generate the desired beamforming vectors fulfilling the essential constant amplitude constraint.

The forthcoming fifth generation (5G) systems with high beamforming gain antenna units, millimeter-wave (mmWave) frequency bands together with massive Multiple Input Multiple Output (MIMO) techniques are key components for accurate positioning methods. In this paper, we propose the positioning technique that is relying on the sparsity in the MIMO-OFDM channel in time and spatial domains, together with effective beamforming methods. We will study the proposed solution in a multi-connectivity context, which has been considered so far for the purpose of improving the user equipment (UE) communication data rate. We utilize the multi-connectivity for positioning, in order to improve robustness to measurement errors and increase positioning service continuity. In particular, we show that when a UE that has connectivity to more base stations, the total power and delay needed for positioning can be reduced.

The increasing demand for ultra-high data rates and low-latency communication in next-generation wireless networks has led to the exploration of millimeter-wave (mmWave) frequency bands. These frequency bands offer significant bandwidth but are challenged by severe path loss, high susceptibility to blockage, and complex channel conditions. To address these challenges, a joint system modeling framework that integrates multicarrier time-division multiple access (MC-TDMA) with beamforming techniques is introduced. This study presents an analytical model that combines MC-TDMA’s flexible time-slot allocation with the high directionality and interference mitigation capabilities of beamforming, tailored to the unique characteristics of mmWave channels. Two optimization algorithms are proposed based on dynamic resource allocations for time slot allocations and hybrid beamforming respectively. Simulations experiments are performed under realistic propagation conditions, considering number of base station antennas, radio frequency (RF) chains, number of users and channel paths. Results demonstrate superior performance over existing schemes. The proposed schemes are verified to have smaller spectral efficiency gaps when compared to the fully-digital beamforming method. The findings offer a practical solution for high-capacity, low-latency communication in dense and dynamic mmWave environments, paving the way for more efficient next-generation networks design.

A deep reinforcement learning (DRL) approach is proposed for simultaneously maximizing distinct user coverage and data throughput in the presence of Sybil attacks. Adversaries are assumed to be capable of PHY layer spoofing and their own reinforcement learning (RL) to cause disruption to the drone network. The distribution of users is modelled as a Gaussian Mixture Model (GMM) with a fixed mean to model a stationary user population and a time varying mean to model movement of users. The drone communication is assumed to be over the millimeter-Wave (mmWave) frequency band and the presence of users are determined based on the beacon signals transmitted by them. Adversaries are assumed to attack the drone network by transmitting spoofed beacon signals. The simulation results indicate that DRL based approaches for UAV path planning is able to cover a significant number of users after a few training epochs. They also indicate that the presence of spoofed transmissions by the adversaries results in 10 to 22 percent reduction in the amount of data handled and the number of distinct users covered.

With the development of wireless communication, higher requirements arise for train-ground wireless communications in high-speed railway (HSR) scenarios. The millimeter-wave (mm-wave) frequency band with rich spectrum resources can provide users in HSR scenarios with high performance broadband multimedia services, while the full-duplex (FD) technology has become mature. In this paper,we study train-ground communication system performance in HSR scenarios with mobile relays (MRs) mounted on rooftop of train and operating in the FD mode. We formulate a nonlinear programming problem to maximize network capacity by allocation of spectrum resources. Then, we develop a sequential quadratic programming (SQP) algorithm based on the Lagrange function to solve the bandwidth allocation optimization problem fortrack-side base station (BS) and MRs in this mm-wave train-ground communication system. Extensive simulation results demonstrate that the proposed SQP algorithm can effectively achieve high network capacity for train-ground communication in HSR scenarios while being robust to the residual self-interference (SI).

The emerging 5G New Radio (NR) cellular systems that may operate in millimeter-wave (mmWave) frequency bands are expected to offer larger bandwidths. They are to be deployed in densely crowded environments, where the traffic load has a high degree of variability, which may introduce capacity bottlenecks. One of the options to alleviate the latter is to concurrently utilize the radio resources available in unlicensed mmWave bands, e.g., at 60 GHz. In this work, we address the coexistence of mmWave-based NR Unlicensed (NR-U) and WiGig technologies and account for the mmWave-specific directionality, propagation, and blockage effects. By further incorporating the features of duty cycling and random access operation, we construct a mathematical framework, which is capable of characterizing the achievable data rates of the NR-U users that operate over both licensed and unlicensed mmWave spectrum simultaneously. Our numerical results demonstrate that the rate attained by such devices is primarily regulated by the initial contention window size that, in its turn, heavily depends on the system and environmental parameters. We report the optimal contention window values for a wide range of blocker and user densities as well as antenna array configurations.

This letter presents a foldable vertically stacked Yagi–Uda antenna at millimeter-wave (mmWave) frequency band. The proposed antenna is built on a FR4 substrate. The antenna consists of a balun, feed dipole element, stacked folded dipole, and inside lamina emergent torsional (LET) joint array. The LET joint array is introduced to reduce and distribute the mechanical stress generated in folding the rigid FR4 substrate. In the planar mode, the antenna results in a measured gain value of 4.9 dBi at the design frequency 24 GHz with a cross-polarization suppression level of less than 12 dB. In the folded mode, the antenna has a measured gain value of 3.9 dB at the target frequency 24 GHz with a cross-polarization suppression level of less than 10 dB. Both operation modes of the proposed antenna cover the broad bandwidth from 23 to 28 GHz (about 20 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> ).

The low power wide area networks (LPWANs) are recently emerging to provide coverage for low- power devices distributed over very large areas. In order to further prolong the battery life of LPWAN devices, in this paper we propose to power LPWAN devices with radio frequency (RF) energy provided by 1) small-cell networks over millimeter-wave (mmWave) frequency bands, and 2) a macrocell base station (MBS) equipped with massive antennas over sub-6 GHz bands. By modeling the mmWave small-cell base stations (SBSs) as a homogeneous Poisson point process and applying stochastic geometry, the energy coverage for each LPWAN device is analyzed. Moreover, the ultra- dense mmWave SBSs case is further discussed by applying a simplified pathloss model. Our results show that ultra-dense mmWave SBSs are capable of powering a large number of LPWAN devices.