Radio Units Research Articles

Meta surface Assisted Open radio access networks

The paradigm of the open radio access networks (O-RAN) seeks to carry intelligence and openness (multi-vendors) to the conventional proprietary and closed radio access networks (RAN) schemes and deliver performance enhancement, cost-efficiency, and flexibility, in both the network's operation and deployment. On the other hand, Reconfigurable Intelligent Surfaces (RIS) are suggested for future networks due to their effectiveness in terms of cost and energy consumption. However, due to the fast time-varying feature of the dense wireless systems, it becomes difficult to allow optimal user association and beamforming in terms of signalling overheads and processing in RIS assisted RANs with the limited capacity of the fronthaul. Therefore, the objective of this study is to attain a trade-off between the costs (signalling overhead/complexity) and the throughput performance. In other words, the study sets the challenges of the RIS aided O-RAN technology regarding the joint selection of user’s equipment (UEs)/open radio unit (O-RU)-RIS pairs and the designing of beamforming at the O-RU/RIS and open distributed unit (O-DU). From this point, to addressing the designing challenges, this work suggests a simple and potential beamforming strategy in RIS aided O-RAN architecture taking into account the specification of the interfaces between different O-RAN units to split opportunities between the radio and distributing units. In specific, a channel-gain-based selection of UEs/O-RU-RIS pairs joint with duality theory (DT) and transform of quadratic function (TQF) algorithm (namely DT_TQF) is proposed. Firstly, the non-convex optimization problem is relaxed via duality and transform of quadratic functions, and then an iterative approach is carried out for the active and passive beamformers via a simple alternating optimization approach. This approach can achieve flexibility in the environment of a high-traffic transmission while lowering the interference between radio units and the signalling burden required for beamforming tasks. Numerical simulation results justify the effectiveness of the algorithm for different systems' parameter settings and validate the important of installing RIS. For example, for a certain environment, the performance gain is about 52.9 % in comparison to the classic null-steering/random phase shifter scheme.

Signalling overhead minimization aware handover execution using ensemble learning in next generation wireless networks

Upcoming smart intelligent heterogeneous wireless networks (HWNs) and their uses can greatly benefit from the merging of long-term evolution (LTE) sub-6 GHz along with millimeter wave (mmWave) frequencies by boosting the coverage, bandwidth, reliability, seamless connectivity, and high quality of service (QoS). Nevertheless, because of the inability of directed waves in terms of coverage, it is difficult to locate the appropriate mmWave remote radio units (RRUs). Therefore, it is crucial to lessen the burden of the handover signaling processes. In meeting research requirements this paper presents signaling overhead minimization aware handover execution (SOMAHE) model. The SOMAHE model first introduces a novel handover mechanism between LTE and mmWave is presented in this research, followed by a machine learning (ML)-based autonomous handover execution technique. To estimate the handover success rate, the model introduces a feature ensemble learning (FEL) model built using XGBoost (XGB) model that makes use of sampling windows channel data. To conclude, combining FEL into the SOMAHE model reduces signaling overhead while simultaneously increasing the handover success-rate. Experiment results with varying mobile terminals, demonstrate that the SOMAHE model significantly outperforms the existing standard deep q-networks (DQN)-based handover-execution method.

A Dynamic Load Modulation Power Amplifier with Ferroelectric-Based Tunable Matching Network.

Power amplifiers are crucial components that significantly influence the linearity and energy efficiency of next-generation communication system radio units. A key challenge in designing power amplifiers is managing high peak-to-average power ratio (PAPR) in order to achieve both high linearity and energy efficiency during back-off conditions. This paper presents simulation and measurement results for a dynamic load modulation power amplifier based on a ferroelectric tunable matching network to operate at 2.5 GHz. Experimental studies on a power amplifier with the tunable output matching network confirm its performance at 8 dB back-off while varying the control voltage applied to the ferroelectric element. Additionally, a bias modulator to adjust the transistor's load in relation to input power was designed. Measurement studies of the dynamic load modulation power amplifier have demonstrated an efficiency of at least 50% at 8 dB back-off and more than 60% at peak power at 2.5 GHz. Furthermore, it was found that the modulator output voltage adjustment function on input power of the bias modulator affects the linearity of the output power. Different bias responses were studied and, as a result, the optimal output voltage response was found. The proposed load modulation power amplifier is promising for operation with high PAPR digital signals.

Simultaneous radio/pump/power-over-multi-core fiber transmission for optically powered radio units eliminating electrical power amplifiers.

We demonstrate simultaneous radio-/pump-/power-over-fiber transmission using a single multi-core fiber for downlink radio-over-fiber transmission. This scheme not only introduces a remotely pumped optical amplifier to eliminate electrical power amplifiers (PAs) in radio units (RUs) but also drives a high-power photodiode, which is the main component of the RU by power-over-fiber. Using this scheme, we achieved a 20-dB improvement in the RF output signal power using a remotely pumped optical amplifier without electrical PAs in the optically powered RU.

An efficient algorithm for resource optimization in TWDM passive optical network using a C-RAN

The traditional base station in C-RAN is divided into three parts: a pool of centralized baseband units (BBUs), a fronthaul network that links the BBUs and remote radio units (RRUs), and RRUs. This paper proposes a novel cooperative algorithm for resource optimization in a time-wavelength division multiplexed (TWDM) passive optical network (PON) incorporating a cloud radio access network (C-RAN). First, a joint collaborative strategy is deployed to optimize cooperative caching and transmission in the wireless and optical domains. Then, the quality of experience (QoE) is improved by bandwidth configuration and caching. Simulation results show that the average throughput of the proposed QoE-aware video cooperative caching and transmission mechanism (QACCTM) algorithm is approximately 30% higher than that of other algorithms. Compared with the relative average residual clutter power (RARCP) and quality-aware wireless edge caching (QAWEC) algorithms, the proposed QACCTM algorithm reduces the access delay by approximately 27.1% and 15.9%, respectively.

Experimental results of multiplexing transmission of 256-QAM 5G NR signal with control signal by SCM over 20-km analog RoF link

Analog radio over fiber is attracting interest as a low-cost solution for high-frequency band distributed antenna systems (DAS). DAS demands the beamforming, TDD timing switching, and CLK synchronization of each distributed antenna section (or remote radio unit (RRU)), but as the number of optical carriers used for RRU control increases, the result is an undesirable increase in RRU complexity. In this paper, we propose and demonstrate a wireless system that can simultaneously transmit, via a single optical carrier, an analog main signal and a control signal (beamforming, TDD, and CLK signals) by subcarrier multiplexing (SCM). Simulations show that the signal quality degradation caused by nonlinearities in the optical modulator during SCM transmission can be avoided by properly designing the input power balance between the analog main signal and the control signal. We also conducted experiments on the downlink transmission of 256 QAM-modulated 5G NR signals by connecting a CS-RRU pair with a 20-km SMF. According to our OTA evaluation using a millimeter-wave band antenna, the EVM value was about 3.41%, which satisfies the 3GPP specification. In addition, control signals were found to be demodulated successfully.

Remote radio frequency unit selection of self-sustaining distributed base-station system based on downlink physical layer secure transmission

Remote radio frequency unit selection of self-sustaining distributed base-station system based on downlink physical layer secure transmission

Optical fiber fronthaul segment in open radio access 5G networks: enhanced performance utilizing AFBG

In open Radio access network (oRAN) 5G networks, a fronthaul segment between virtual Distribution unit (vDU) edge cloud and other external Remote radio units (RRUs) sites is very important to transmit high data rate to achieve 5G requirements. Performance parameters such as Quality factor (Q-factor) and Bit error rate (BER) of an optical fiber fronthaul segment are the main important parameters to enhance latency and bit rate. An Apodized fiber bragg grating (AFBG) is utilized with different apodization profiles to optimize linewidth of an optical signal leading to enhance performance. The designed AFBG is used with a data rate of 25 Gb/s optical Ethernet module at the vDU edge cloud to optimize the linewidth of the optical signal between the vDU and the RRU in the fronthaul optical fiber segment. The AFBG is investigated at different connections pre, post, and symmetrical connections, where different apodization functions are used in the AFBG design. It is found that the best results for the maximum Q-factor and minimum BER are 9.2 and 2.72e− 21, respectively, obtained from uniform function in the symmetrical connection. Finally, the proposed model linewidth is 0.408 nm, which is better than 1.56 nm that is evaluated by related work.

Sub-6 GHz beamforming with low-cost software-defined radio: Design, testing, and performance evaluation

The rapid evolution of mobile communication systems has led to the introduction of novel technologies and techniques that address existing challenges, such as interference caused by multiple users and transmission through the millimetre-wave band. In this paper, we present a novel approach that utilises a low-cost software defined radio (SDR) unit to enable transmitting and receiving beamforming in the sub-6 GHz band. We provide a detailed account of the underlying concepts and background of beamforming and SDR, outline the design of multiple components, and report on the comprehensive testing and verification of a real-life prototype using over-the-air (OTA) methods. Our results demonstrate that the proposed approach achieves outstanding performance, with measurements of bit error rate (BER) that outperform existing solutions. In summary, this work contributes to the ongoing efforts to enhance mobile communication systems by providing an innovative, high-performance solution that is cost-effective and reliable using SDR technology in the sub-6 GHz band.

Millimeter-wave over fiber integrated sensing and communication system using self-coherent OFDM

Orthogonal frequency-division multiplexing (OFDM) waveform is highly preferred as a dual-function candidate for integrated sensing and communication (ISAC) systems. However, the sensitivity to both carrier frequency offset (CFO) and phase noise greatly impedes its applications in millimeter-wave ISAC systems. Here, we propose and experimentally demonstrate a photonic millimeter-wave ISAC system employing the virtual-carrier-aided self-coherent OFDM technique, wherein a digitally-generated local oscillator is transmitted along with the OFDM signal. Then, a compact CFO-immune and phase noise-immune envelope detection method is implemented for down-converting millimeter-wave communication and radar echo signals. In experiments, a V-band ISAC system is successfully implemented with a simplified remote radio unit, using the remote photonic millimeter-wave heterodyning up-conversion for downlink and the envelope detection-assisted down-conversion for uplink (or radar echoes). In the converged transmission link with a 5-km fiber link and 2-m space link, the Kramers–Kronig (KK) receiver supports a communication data rate up to 16-Gbit/s by mitigating signal-signal beat interference (SSBI). More significantly, the SSBI leads to negligible effects on the sensing performance when classic matched filtering is adopted for target identification. Consequently, a 4.8-cm range resolution and a 4-mm range accuracy are obtained for the radar sensing function.

A machine learning approach for package size estimation using UHF RFID interrogation signature

This paper introduces a new approach for performing package classification and sizing using Radio-Frequency Identification (RFID) systems. This technique is applicable when packages are labeled with or contain multiple RFID-tagged items. During the interrogation of the tags, received signal strength (RSS) statistics and other information, such as the frame count or the reading time, are collected by the reader and used to predict the package type from a set of candidate classes using an Artificial Neural Network (ANN). The primary challenge lies in acquiring sufficient training data for a target scenario to ensure reliable predictions. To address this, a two-phase training process based on transfer learning is adopted. Initially, a base model is developed using synthetic data generated from a detailed RFID simulator, designed to suit diverse scenarios, establish detailed link budgets, and comprehensively simulate the communication protocols. This model is then refined using a small dataset collected experimentally in the actual scenario. This method was validated in a real testbed with four different package types. The base model was trained using 1000 synthetic samples per package type (4000 in total), whereas the refined model was trained with a dataset consisting of only 25 real interrogation traces (samples) per package type (100 in total). The experimental samples were obtained using a software-defined radio unit, the Ettus B210 Universal Software Radio Peripheral (USRP) platform. This experiment achieved an accuracy of over 92%. In summary, this approach introduces a new feature to existing RFID setups, demonstrating potential for advanced package handling and cost optimization in the logistics sector.

Hybrid cell handover strategy for O-RAN-based campus networks

In recent years, the concept of Open Radio Access Network (O-RAN) has become a prominent and ongoing research area in mobile communications, as mobile operators strive to enhance the intelligence, efficiency, and vendor independence of their RAN (Radio Access Network) architectures and components. O-RAN aims to virtualize and improve RAN functions in software and therefore it supports virtualized RANs where disaggregated network components of multiple vendors are connected via open interfaces. O-RAN is a concept based on interoperability and standardization of RAN elements including a unified interconnection standard for white-box hardware and open-source software elements from different vendors. Architecture integrates a modular base station software stack on off-the-shelf hardware which allows baseband and radio unit components from different suppliers to operate seamlessly together. Analyzing and examining the O-RAN architecture in terms of various network scenarios and different network policies is crucial for next-generation networks. This study begins by discussing the O-RAN architecture and its advantages in detail. Subsequently, a campus network has been proposed for the analysis and simulation of the O-RAN architecture, and performance analyses have been performed within the scope of different scenarios and network policies. As a result of these analysis, a new hybrid algorithm for cell handovers in the O-RAN architecture has been developed and compared with traditional cell handover methods based on Reference Signal Received Power (RSRP) and Quality of Service (QoS). The results indicate that the proposed hybrid handover algorithm for O-RAN architecture yields better outcomes.

Data-driven decision-making framework for optical fronthaul slice resizing in 6G networks

The third-generation partnership introduced three main types of slices: enhanced mobile broadband, massive machine-type communication, and ultrareliable low-latency communication. To accommodate these services, the next generation of mobile networks will require architecture with distinct requirements and network slices. To implement these services on an optical fronthaul, the slices will be hosted using lightpaths. Such lightpaths will have to accommodate latency and bandwidth constraints to keep radio units (RUs) and baseband units (BBUs) synchronized. However, the traffic in a slice may vary, and the resources allocated to a long-established lightpath could be out of date, leading to waste or lack of resources. For example, a lack of bandwidth can cause desynchronization between BBUs and RUs. Therefore, the slice must be resized regularly to meet the variable demands. This work proposes a data-driven decision-making (DDDM) framework to resize the fronthaul slices while mitigating the consequences of a lack of bandwidth. The framework uses long short-term memory to implement its analytical stage and integer linear programming (ILP) to reconfigure the entire network when it is required. The results show that the DDDM-based framework outperforms the state-of-the-art ILP-based heuristic by up to 15% in terms of radio blocking mitigation.

Evaluation of User-Centric Cell-Free Massive Multiple-Input Multiple-Output Networks Considering Realistic Channels and Frontend Nonlinear Distortion

Future 6G networks are expected to utilize Massive Multiple-Input Multiple-Output (M-MIMO) and follow a user-centric cell-free (UCCF) architecture. In a UCCF M-MIMO network, the user can be potentially served by multiple surrounding Radio Units (RUs) and Distributed Units (DUs) controlled and coordinated by a single virtualized Centralized Unit (CU). Moreover, in an M-MIMO network, each transmit frontend is equipped with a Power Amplifier (PA), typically with nonlinear characteristics, that can have a significant impact on the throughput achieved by network users. This work evaluates a UCCF M-MIMO network within an advanced system-level simulator considering multicarrier transmission, using Orthogonal Frequency-Division Multiplexing (OFDM), realistic signal-processing steps, e.g., per resource block scheduling, and a nonlinear radio frontend. Moreover, both idealistic independent and identically distributed (i.i.d.) Rayleigh and 3D ray-tracing-based radio channels are evaluated. The results show that under the realistic radio channel, the novel user-centric network architecture can lead to an almost uniform distribution of user throughput and improve the rate of the users characterized by the worst radio conditions by over 3 times in comparison to a classical, network-centric design. At the same time, the nonlinear characteristics of the PA can cause significant degradation of the UCCF M-MIMO network’s performance when operating close to its saturation power.

An analysis of the driving forces behind the Yangtze River Delta (YRD) region's high-quality growth in the digital creative industries.

The digital creative sector has grown enormously on a global scale as a result of the digital age's fast progress. The development and transformation of the regional financial system in China is largely due to the efforts of the digital innovation industry. Hence, a comprehensive examination of the catalysts at the back of its premium boom is fundamental. The Yangtze River Delta (Abbreviation YRD) area is a powerful group of Chinese cities, well-known for its economic impact, the basis of its urbanization, and its total potential. It also offers some advantages related to the digital creative sector. The YRD area's digital creative industries are growing, and this research looks at what's behind that development. Through the compilation and analysis of surface-level data, the research focused on identifying the key drivers influencing the industry's high-quality advancement. This is achieved by assessing the digital creative industries of the YRD and determining the elements that facilitate their continued growth and superior development using ArcMap10.8 and the entropy-weight-TOPSIS approach. This approach supports the assessment and ranking of the variables impacting the expansion of the digital creative industries in the YRD region. The findings demonstrate that: 1) The YRD region's performance in developing a high-quality digital creative industry is improving between 2017 and 2022; 2) According to an assessment of growth in this sector, Jiangsu and Zhejiang provinces have excelled, while Shanghai and Anhui provinces have lagged in developing digital creative industries over the past six years; 3) Anhui and Zhejiang provinces had the greatest outcomes, according to an annual study of the YRD digital creative industries conducted between 2017 and 2022. The digital creative sector in Zhejiang Province has performed well, showing a consistent growing trend; in contrast, Shanghai City's industry has seen a decrease; while Anhui and Jiangsu Provinces have shown generally stable, slightly increasing tendencies; 4) In the weighting analysis of the indicators, the number of strategic emerging industry project transactions (C10), the total income of radio and television business units (C13), the number of ordinary undergraduate and specialist graduates of ordinary schools (C18), the area of land for public facilities (C24), and the regional gross domestic product (C12) are five indicators of significant impact on the development of the degree of influence.

Efficient Video QoE Prediction in Intelligent O-RAN

Open Radio Access Network (O-RAN) is a platform developed by a collaboration between wireless operators, infrastructure vendors, and service providers for deploying mobile fronthaul and midhaul networks, built entirely on cloud-native principles. The vision of O-RAN lies in the virtualization of traditional wireless infrastructure components, like Central Units (CU), Radio Units (RU), and Distributed Units (DU). O-RAN decouples the above-mentioned wireless infrastructure components into open-source elements, operating consistently with other elements of different vendors in the network. Quality of Experience (QoE) deals with a user's subjective measure of satisfaction. RAN Intelligent Controller (RIC) in O-RAN provides flexibility to intelligently program and control RAN functions using AI/ML-based models. We argue that various QoE parameters can be measured and operated by the RIC in O-RAN. We propose to improve the efficiency of O-RAN's radio resources by creating a RIC xApp that estimates the QoE measured using Video Mean Opinion of Score (MOS), and accurately optimizes the usage of radio resources across multiple network slices. We use predictive AI/ML-based models to accurately predict the QoE parameters in the network after which we can optimize the usage of network compo-nents leading to an enhanced user experience. Simulation results on 3 simulated data sets show that our proposed approach can achieve up to 95% QoE prediction accuracy.

IMPLEMENTATION OF FUNCTIONAL BLOCK RADIO UNIT BASED ON SYSTEM-ON-CHIP

This article discusses the implementation of the Radio Unit functional block based on the System-on-Chip. The primary focus was on integrating Radio Unit blocks such as modulation and Fast Fourier Transform on Field-Programmable Gate Array. Technical aspects of design, module testing, and Radio Unit block performance optimization are thoroughly examined. The results demonstrate that when separating the functionality of the 7.3 technology Fifth Generation (5G) radio block, the modulation module uses the minimum Field-Programmable Gate Array resources compared to other blocks. The Fast Fourier Transform block can meet delay requirements at the maximum Field-Programmable Gate Array size and clock frequency of 250 MHz. This article serves as a resource for engineers and researchers interested in optimizing the development and integration process of high-performance functional blocks in modern radio systems.

Optimized Precoding for MU-MIMO With Fronthaul Quantization

One of the first widespread uses of multi-user multiple-input multiple-output (MU-MIMO) is in 5G networks, where each base station has an advanced antenna system (AAS) that is connected to the baseband unit (BBU) with a capacity-constrained fronthaul. In the AAS configuration, multiple passive antenna elements and radio units are integrated into a single box. This paper considers precoded downlink transmission over a single-cell MU-MIMO system. We study optimized linear precoding for AAS with a limited-capacity fronthaul, which requires the precoding matrix to be quantized. We propose a new precoding design that is aware of the fronthaul quantization and minimizes the mean-squared error at the receiver side. We compute the precoding matrix using a sphere decoding (SD) approach. We also propose a heuristic low-complexity approach to quantized precoding. This heuristic is computationally efficient enough for massive MIMO systems. The numerical results show that our proposed precoding significantly outperforms quantization-unaware precoding and other previous approaches in terms of the sum rate. The performance loss for our heuristic method compared to quantization-aware precoding is insignificant considering the complexity reduction, which makes the heuristic method feasible for real-time applications. We consider both perfect and imperfect channel state information (CSI).

Joint Resource Allocation in TWDM-PON-Enabled Cell-Free mMIMO System

Cell-free massive multiple input multiple outputs (CF-mMIMO) is considered a promising technology for sixth-generation (6G) telecommunication systems. In the CF-mMIMO system, an extensive array of distributed small base stations (BSs) is deployed across the network, which enables us to facilitate seamless collaboration among BSs. To achieve this goal, the baseband signal from these BSs needs to be transmitted to a central server via fronthaul networks. Due to the large number of BSs, the data that needs to be transmitted is usually huge, which brings severe requirements on fronthaul networks. Time and wavelength division multiplexed passive optical networks (TWDM-PON) can be a potential solution for CF-mMIMO fronthaul due to their large capacity and high flexibility. However, how to efficiently allocate both optical and wireless resources in a TWDM-PON-enabled CF-mMIMO system is still a problem to be addressed. This paper proposes a joint scheduling method of wavelength, antenna, radio unit (RU), and radio resource block (RB) resources in the TWDM-PON-enabled CF-mMIMO system. Furthermore, an integer linear programming (ILP) model for joint resource allocation is proposed to minimize the fronthaul resource occupancy, thereby increasing network scalability. Considering the complexity of the ILP model, two heuristic algorithms are also presented to solve this model. We compare the ILP with heuristic algorithms under different scenarios. Simulation results show that the proposed algorithm can reduce the fronthaul resource occupancy to improve the network scalability of the CF-mMIMO system.

Oceania’s 5G Multi-Tier Fixed Wireless Access Link’s Long-Term Resilience and Feasibility Analysis

Information and communications technologies play a vital role in achieving the Sustainable Development Goals (SDGs) and bridging the gap between developed and developing countries. However, various socioeconomic factors adversely impact the deployment of digital infrastructure, such as 5G networks, in the countries of Oceania. The high-speed broadband fifth-generation cellular network (5G) will improve the quality of service for growing mobile users and the massive Internet of Things (IoT). It will also provide ultra-low-latency services required by smart city applications. This study investigates the planning process for a 5G radio access network incorporating sub-6 GHz macro-remote radio units (MRRUs) and mmWave micro-remote radio units (mRRUs). We carefully define an optimization problem for 5G network planning, considering the characteristics of urban macro-cells (UMa) and urban micro-cells (UMi) with appropriate channel models and link budgets. We determine the minimum number of MRRUs and mRRUs that can be installed in each area while meeting coverage and user traffic requirements. This will ensure adequate broadband low-latency network coverage with micro-cells instead of macro-cells. This study evaluates the technical feasibility analysis of combining terrestrial and airborne networks to provide 5G coverage in Oceania, with a special emphasis on Fiji.