Ever since the deployment of the first-generation of mobile telecommunications, wireless communication technology has evolved at a dramatically fast pace over the past four decades. The upcoming fifth-generation (5G) holds a great promise in providing an ultra-fast data rate, a very low latency, and a significantly improved spectral efficiency by exploiting the millimeter-wave spectrum for the first time in mobile communication infrastructures. In the years beyond 2030, newly emerged data-hungry applications and the greatly expanded wireless network will call for the sixth-generation (6G) communication that represents a significant upgrade from the 5G network – covering almost the entire surface of the earth and the near outer space. In both the 5G and future 6G networks, millimeter-wave technologies will play an important role in accomplishing the envisioned network performance and communication tasks. In this paper, the relevant millimeter-wave enabling technologies are reviewed: they include the recent developments on the system architectures of active beamforming arrays, beamforming integrated circuits, antennas for base stations and user terminals, system measurement and calibration, and channel characterization. The requirements of each part for future 6G communications are also briefly discussed.

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The Role of Millimeter-Wave Technologies in 5G/6G Wireless Communications

Heat removal capabilities and radiation performances of several sparse antenna array topologies are studied for cooling enhancement in 5G millimeter-wave base station antennas. Both electromagnetic (EM) and thermal aspects are jointly considered for the first time in array layout optimization, and a novel connection between layout sparsity and thermal management is presented. Two types of active electronically scanned arrays (AESAs), based on the traditional and planar approaches, are examined. Thermal management in AESAs is discussed, with a focus on cooling challenges at millimeter waves. Being relatively low cost and low profile while supporting flexible beamforming, passively cooled planar AESAs with fanless CPU coolers are proposed, for the first time, to be used in 5G base stations. Additional cooling for such arrays is achieved by increasing the inter-element distances in the layout. Linear irregular arrays, spiral arrays, thinned arrays, circular ring arrays, and heat sink antenna arrays are revisited with a critical discussion on their EM and thermal performance. The results are compared with regular and square layouts that are used as benchmarks throughout this paper.

Thermal-Aware Synthesis of 5G Base Station Antenna Arrays: An Overview and a Sparsity-Based Approach

Flexible electromagnetic interference (EMI) shielding textiles with wide-operating-range Joule heating performances are urgently indispensable in the application of artificial intelligence, communi...

Multifunctional Electromagnetic Interference Shielding Ternary Alloy (Ni-W-P) Decorated Fabric with Wide-Operating-Range Joule Heating Performances.

In practical engineering, the layout optimization technique driven by the thermal performance is faced with a severe computational burden when directly integrating the numerical analysis tool of temperature simulation into the optimization loop. To alleviate this difficulty, this paper presents a novel deep learning surrogate-assisted heat source layout optimization method. First, two sampling strategies, namely the random sampling strategy and the evolving sampling strategy, are proposed to produce diversified training data. Then, regarding mapping between the layout and the corresponding temperature field as an image-to-image regression task, the feature pyramid network (FPN), a kind of deep neural network, is trained to learn the inherent laws, which plays as a surrogate model to evaluate the thermal performance of the domain with respect to different input layouts accurately and efficiently. Finally, the neighborhood search-based layout optimization (NSLO) algorithm is proposed and combined with the FPN surrogate to solve discrete heat source layout optimization problems. A typical two-dimensional heat conduction optimization problem is investigated to demonstrate the feasibility and effectiveness of the proposed deep learning surrogate-assisted layout optimization framework.

The heat source layout optimization using deep learning surrogate modeling

The next-generation 5G and beyond-5G wireless systems have stimulated a substantial growth in research, development, and deployment of mm-Wave electronic systems and antenna arrays at various scales. It is also envisioned that large dynamic range modulation signals with high spectral efficiency will be ubiquitously employed in future communication and sensing systems. As the interface between the antennas and transceiver electronics, power amplifiers (PAs) typically govern the output power, energy efficiency, and reliability of the entire wireless systems. However, the wide use of high dynamic range signals at mm-Wave carrier frequencies substantially complicates the design of PAs and demands an ultimate balance of energy efficiency and linearity as well as other PA performances. In this review paper, we will first introduce the system-level requirements and design challenges on mm-Waves PAs due to high dynamic range signals. We will review advanced active load modulation architectures for mm-Wave PAs and power devices. We will then introduce recent advances in mm-Wave PA technologies and innovations with several design examples. Special design considerations on mm-Wave PAs for phased array MIMOs and high mm-Wave frequencies will be outlined. We will also share our vision on future technology trends and innovation opportunities.

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Millimeter-Wave Power Amplifier Integrated Circuits for High Dynamic Range Signals

An extended-feature, system-driven convex algorithm for the synthesis of uniform-amplitude, irregular planar phased arrays with simultaneous multi-beam optimization for mm-wave 5G base station applications in multi-user scenarios is presented. The inter-user interferences are suppressed by minimizing the maximum sidelobe level (SLL) for a beam scanned freely inside a given sector. The aperture size is restricted to the size of the heatsink baseplate dimensions. A minimum guaranteed inter-element spacing in the final layout is pre-defined, which prevents element overlapping, eases the thermal problem and helps reduce the effects of high mutual coupling (MC). The algorithm performance is tested via the synthesis of a 64-element integrated array with at least half a wavelength inter-element spacing. The optimized array results show that, compared to their regular counterparts, significant reduction in the SLLs is achieved for a beam scanned inside the defined sector, while keeping the maximum temperature of the array at a reliable level. The effect of MC on the results is also investigated via full-wave simulations and it is explained how embedded element patterns can potentially be included in the optimization. Superior capabilities of the proposed method are illustrated by comparing the algorithm output to those reported in the state-of-the-art literature.

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Multiple Beam Synthesis of Passively Cooled 5G Planar Arrays Using Convex Optimization

Heat source layout optimization for two-dimensional heat conduction using iterative reweighted L1-norm convex minimization

Minimization of the maximum sidelobe level for a given array geometry, amplitude distribution, and nulling sectors by phase-only adjustment of the element coefficients is studied. Nonlinear optimization problem for phase distribution is solved using a novel iterative convex optimization algorithm, which includes mutual coupling effects and exploits small phase perturbations at each step. Superiority of the algorithm in terms of the peak sidelobe level and nulling depth achieved over several optimization methods reported in the most relevant literature is demonstrated in several case studies. Finally, a case study is performed to demonstrate added value of the algorithm for millimeter-wave fifth generation application with phase-only radiation pattern forming.

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Phase-Only Control of Peak Sidelobe Level and Pattern Nulls Using Iterative Phase Perturbations

The encouraging potential of employing large-scale aperiodic base station arrays in addressing the radiation pattern and thermal requirements of the next generation communication systems is demonstrated. Sample 256-element layout-optimized multibeam arrays are presented as a futuristic view. The system benefits (in terms of the statistical quality-of-service, energy efficiency, thermal management, and processing burden) of the proposed arrays, as well as their performance versus design complexity tradeoffs, are explained through interdisciplinary simulations. The key advantage of the proposed antennas over the currently proposed 64-element periodic arrays is identified as the increased gain with much lower side lobes, which yields much less power and less heat per element with more surface for cooling, and allows robust/computationally efficient precoding.

Yanki Aslan

Papers

Thermal-Aware Synthesis of 5G Base Station Antenna Arrays: An Overview and a Sparsity-Based Approach

Multiple Beam Synthesis of Passively Cooled 5G Planar Arrays Using Convex Optimization

Heat source layout optimization for two-dimensional heat conduction using iterative reweighted L1-norm convex minimization

Phase-Only Control of Peak Sidelobe Level and Pattern Nulls Using Iterative Phase Perturbations

System Advantages of Using Large-Scale Aperiodic Array Topologies in Future mm-Wave 5G/6G Base Stations: An Interdisciplinary Look