Fronthaul evolution: From CPRI to Ethernet

It is proposed that using Ethernet in the fronthaul, between base station baseband unit (BBU) pools and remote radio heads (RRHs), can bring a number of advantages, from use of lower-cost equipment, shared use of infrastructure with fixed access networks, to obtaining statistical multiplexing and optimised performance through probe-based monitoring and software-defined networking. However, a number of challenges exist: ultra-high-bit-rate requirements from the transport of increased bandwidth radio streams for multiple antennas in future mobile networks, and low latency and jitter to meet delay requirements and the demands of joint processing. A new fronthaul functional division is proposed which can alleviate the most demanding bit-rate requirements by transport of baseband signals instead of sampled radio waveforms, and enable statistical multiplexing gains. Delay and synchronisation issues remain to be solved

6G Radio Testbeds: Requirements, Trends, and Approaches

The proof of the pudding is in the eating - that is why 6G testbeds are essential in the progress towards the next generation of wireless networks. Theoretical research towards 6G wireless networks is proposing advanced technologies to serve new applications and drastically improve the energy performance of the network. Testbeds are indispensable to validate these new technologies under more realistic conditions. This paper clarifies the requirements for 6G radio testbeds, reveals trends, and introduces approaches towards their development

Architectures and synchronization techniques for distributed satellite systems: a survey

Cohesive Distributed Satellite Systems (CDSSs) is a key enabling technology for the future of remote sensing and communication missions. However, they have to meet strict synchronization requirements before their use is generalized. When clock or local oscillator signals are generated locally at each of the distributed nodes, achieving exact synchronization in absolute phase, frequency, and time is a complex problem. In addition, satellite systems have significant resource constraints, especially for small satellites, which are envisioned to be part of the future CDSSs. Thus, the development of precise, robust, and resource-efficient synchronization techniques is essential for the advancement of future CDSSs. In this context, this survey aims to summarize and categorize the most relevant results on synchronization techniques for Distributed Satellite Systems (DSSs). First, some important architecture and system concepts are defined. Then, the synchronization methods reported in the literature are reviewed and categorized. This article also provides an extensive list of applications and examples of synchronization techniques for DSSs in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position. The survey also provides a discussion on emerging data-driven synchronization techniques based on Machine Learning (ML). Finally, a compilation of current research activities and potential research topics is proposed, identifying problems and open challenges that can be useful for researchers in the field.This work was supported by the Luxembourg National Research Fund (FNR), through the CORE Project COHEsive SATellite (COHESAT): Cognitive Cohesive Networks of Distributed Units for Active and Passive Space Applications, under Grant FNR11689919.Award-winningPostprint (published version

Design of a Drone-Flight-Enabled Wireless Isolation Chamber

The next wave of drone applications is moving from repeatable, single-drone activities such as evaluating propagation environments to team-based, multi-drone objectives such as drone-based emergency services. In parallel, testbeds have sought to evaluate emerging concepts such as highly-directional and distributed wireless communications. However, there is a lack of intersection between the two works to characterize the impact of the drone body, antenna placement, swarm topologies, and multi-dimensional connectivity needs that require in-flight experimentation with a surrounding testbed infrastructure. In this work, we design a drone-flight-enabled isolation chamber to capture complex spatial wireless channel relationships that drone links experience as applications scale from single-drone to swarm-level networks within a shared three-dimensional space. Driven by the challenges of outdoor experimentation, we identify the need for a highly-controlled indoor environment where external factors can be mitigated. To do so, we first build an open-source drone platform to provide programmable control with visibility into the internal flight control system and sensors enabling specialized coordination and accurate repeatable positioning within the isolated environment. We then design a wireless data acquisition system and integrate distributed software defined radios (SDRs) in order to inspect multi-dimensional wireless behavior from the surrounding area. Finally, we achieve and demonstrate the value of measurement perspectives from diverse altitudes and spatial locations with the same notion of time

Satellite-derived Time for Enhanced Telecom Networks Synchronization: the ROOT Project

Satellite-derived timing information plays a determinant role in the provisioning of an absolute time reference to telecommunications networks, as well as in a growing set of other critical infrastructures. In light of the stringent requirements in terms of time, frequency, and phase synchronization foreseen in upcoming access network architectures (i.e., 5G), Global Navigation Satellite System (GNSS) receivers are expected to ensure enhanced accuracy and reliability not only in positioning but also in timing. High-end GNSS timing receivers combined with terrestrial cesium clocks and specific transport protocols can indeed satisfy such synchronization requirements by granting sub-nanosecond accuracy. As a drawback, the network infrastructure can be exposed to accidental interferences and intentional cyber-attacks. Within this framework, the ROOT project investigates the effectiveness and robustness of innovative countermeasures to GNSS and cybersecurity threats within a reference network architecture

Nanosecond-Level Resilient GNSS-Based Time Synchronization in Telecommunication Networks Through WR-PTP HA

In recent years, the push for accurate and reliable time synchronization has gained momentum in critical infrastructures, especially in telecommunication networks, driven by the demands of 5G new radio and next-generation technologies that rely on submicrosecond timing accuracy for radio access network (RAN) nodes. Traditionally, atomic clocks paired with global navigation satellite systems (GNSS) timing receivers have served as grand master clocks, supported by dedicated network timing protocols. However, this approach struggles to scale with the increasing numbers of RAN intermediate nodes. To address scalability and high-accuracy synchronization, a more cost-effective and capillary solution is needed. Standalone GNSS timing receivers leverage ubiquitous satellite signals to offer stable timing signals but can expose networks to radio-frequency attacks due to the consequent proliferation of GNSS antennas. Our research introduces a solution by combining the white rabbit precise time protocol with a backup timing source logic acting in case of timing disruptive attacks against GNSS for resilient GNSS-based network synchronization. It has been rigorously tested against common jamming, meaconing, and spoofing attacks, consistently maintaining 2 ns relative synchronization accuracy between nodes, all without the need for an atomic clock

Systems with Massive Number of Antennas: Distributed Approaches

As 5G is entering maturity, the research interest has shifted towards 6G, and specially the new use cases that the future telecommunication infrastructure needs to support. These new use cases encompass much higher requirements, specifically: higher communication data-rates, larger number of users, higher accuracy in localization, possibility to wirelessly charge devices, among others.The radio access network (RAN) has already gone through an evolution on the path towards 5G. One of the main changes was a large increment of the number of antennas in the base-station. Some of them may even reach 100 elements, in what is commonly referred as Massive MIMO. New proposals for 6G RAN point in the direction of continuing this path of increasing the number of antennas, and locate them throughout a certain area of service. Different technologies have been proposed in this direction, such as: cell-free Massive MIMO, distributed MIMO, and large intelligent surface (LIS). In this thesis we focus on LIS, whose conducted theoretical studies promise the fulfillment of the aforementioned requirements.While the theoretical capabilities of LIS have been conveniently analyzed, little has been done in terms of implementing this type of systems. When the number of antennas grow to hundreds or thousands, there are numerous challenges that need to be solved for a successful implementation. The most critical challenges are the interconnection data-rate and the computational complexity.In the present thesis we introduce the implementation challenges, and show that centralized processing architectures are no longer adequate for this type of systems. We also present different distributed processing architectures and show the benefits of this type of schemes. This work aims at giving a system-design guideline that helps the system designer to make the right decisions when designing these type of systems. For that, we provide algorithms, performance analysis and comparisons, including first order evaluation of the interconnection data-rate, processing latency, memory and energy consumption. These numbers are based on models and available data in the literature. Exact values depend on the selected technology, and will be accurately determined after building and testing these type of systems.The thesis concentrates mostly on the topic of communication, with additional exploration of other areas, such as localization. In case of localization, we benefit from the high spatial resolution of a very-large array that provides very rich channel state information (CSI). A CSI-based fingerprinting via neural network technique is selected for this case with promising results. As the communication and localization services are based on the acquisition of CSI, we foresee a common system architecture capable of supporting both cases. Further work in this direction is recommended, with the possibility of including other applications such as sensing.The obtained results indicate that the implementation of these very-large array systems is feasible, but the challenges are numerous. The proposed solutions provide encouraging results that need to be verified with hardware implementations and real measurements

Architectures and Synchronization Techniques for Distributed Satellite Systems: A Survey

Cohesive Distributed Satellite Systems (CDSSs) is a key enabling technology for the future of remote sensing and communication missions. However, they have to meet strict synchronization requirements before their use is generalized. When clock or local oscillator signals are generated locally at each of the distributed nodes, achieving exact synchronization in absolute phase, frequency, and time is a complex problem. In addition, satellite systems have significant resource constraints, especially for small satellites, which are envisioned to be part of the future CDSSs. Thus, the development of precise, robust, and resource-efficient synchronization techniques is essential for the advancement of future CDSSs. In this context, this survey aims to summarize and categorize the most relevant results on synchronization techniques for Distributed Satellite Systems (DSSs). First, some important architecture and system concepts are defined. Then, the synchronization methods reported in the literature are reviewed and categorized. This article also provides an extensive list of applications and examples of synchronization techniques for DSSs in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position. The survey also provides a discussion on emerging data-driven synchronization techniques based on Machine Learning (ML). Finally, a compilation of current research activities and potential research topics is proposed, identifying problems and open challenges that can be useful for researchers in the field

Time and Frequency Transfer in a Coherent Multistatic Radar using a White Rabbit Network

Networks of coherent multistatic radars require accurate and stable time and frequency transfer (TFT) for range and Doppler estimation. TFT techniques based on global navigation satellite systems (GNSS), have been favoured for several reasons, such as enabling node mobility through wireless operation, geospatial referencing, and atomic clock level time and frequency stability. However, such systems are liable to GNSS-denial, where the GNSS carrier is temporarily or permanently removed. A denial-resilient system should consider alternative TFT techniques, such as the White Rabbit (WR) project. WR is an Ethernet based protocol, that is able to synchronise thousands of nodes on a fibre-optic based network with sub-nanosecond accuracy and picoseconds of jitter. This thesis evaluates WR as the TFT network for a coherent multistatic pulse-Doppler radar – NeXtRAD. To test the hypothesis that WR is suitable for TFT in a coherent multistatic radar, the time and frequency performance of a WR network was evaluated under laboratory conditions, comparing the results against a network of multi-channel GPS-disciplined oscillators (GPSDO). A WR-disciplined oscillator (WRDO) is introduced, which has the short-term stability of an ovenised crystal (OCXO), and long-term stability of the WR network. The radar references were measured using a dual mixer time difference technique (DMTD), which allows the phase to be measured with femtosecond level resolution. All references achieved the stringent time and frequency requirements for short-term coherent bistatic operation, however the GPSDOs and WRDOs had the best short-term frequency stability. The GPSDOs had the highest amount of long-term phase drift, with a peak-peak time error of 9.6 ns, whilst the WRDOs were typically stable to within 0.4 ns, but encountered transient phase excursions to 1.5 ns. The TFT networks were then used on the NeXtRAD radar, where a lighthouse, Roman Rock, was used as a static target to evaluate the time and frequency performance of the references on a real system. The results conform well to the laboratory measurements, and therefore, WR can be used for TFT in coherent radar

Online Expectation-Maximization Based Frequency and Phase Consensus in Distributed Phased Arrays

Distributed phased arrays are comprised of separate, smaller antenna systems that coordinate with each other to support coherent beamforming towards a destination. However, due to the frequency drift and phase jitter of the oscillators, as well as the frequency and phase estimation errors induced at the nodes, there exists decoherence that degrades the beamforming process. A decentralized frequency and phase consensus (DFPC) algorithm was proposed in prior work for undirected networks in which the nodes locally share their frequencies and phases with their neighbors to reach synchronization. Kalman filtering (KF) was also integrated with DFPC (KF-DFPC) to lower the total residual phase error upon convergence. Since these DFPC-based algorithms rely on the average consensus protocol, they do not converge for directed networks. In this paper, we propose a push-sum based frequency and phase consensus (PsFPC) algorithm for the directed networks. The residual phase error of PsFPC is theoretically derived as well. Kalman filtering is also integrated with PsFPC and the resulting KF-PsFPC algorithm shows a significant reduction in the residual phase error upon convergence. KF assumes that the model parameters, i.e., the measurement noise and innovation noise covariance matrices, are known. Since they may not be known in practice, we develop an online expectation maximization (EM) based algorithm that iteratively computes the maximum likelihood (ML) estimate of the unknown matrices in an online manner. EM is integrated with KF-PsFPC to propose the EM-KF-PsFPC algorithm. Simulation results are included where the performance of the PsFPC-based algorithms is analyzed for different distributed phased arrays and is compared to other algorithms