Learning Optimal Fronthauling and Decentralized Edge Computation in Fog Radio Access Networks

Fog radio access networks (F-RANs), which consist of a cloud and multiple edge nodes (ENs) connected via fronthaul links, have been regarded as promising network architectures. The F-RAN entails a joint optimization of cloud and edge computing as well as fronthaul interactions, which is challenging for traditional optimization techniques. This paper proposes a Cloud-Enabled Cooperation-Inspired Learning (CECIL) framework, a structural deep learning mechanism for handling a generic F-RAN optimization problem. The proposed solution mimics cloud-aided cooperative optimization policies by including centralized computing at the cloud, distributed decision at the ENs, and their uplink-downlink fronthaul interactions. A group of deep neural networks (DNNs) are employed for characterizing computations of the cloud and ENs. The forwardpass of the DNNs is carefully designed such that the impacts of the practical fronthaul links, such as channel noise and signling overheads, can be included in a training step. As a result, operations of the cloud and ENs can be jointly trained in an end-to-end manner, whereas their real-time inferences are carried out in a decentralized manner by means of the fronthaul coordination. To facilitate fronthaul cooperation among multiple ENs, the optimal fronthaul multiple access schemes are designed. Training algorithms robust to practical fronthaul impairments are also presented. Numerical results validate the effectiveness of the proposed approaches.Comment: to appear in IEEE Transactions on Wireless Communication

Modulation and Equalization Techniques for mmWave ARoF

Fifth generation (5G) is the emerging mobile communications platform that aims to meet the market requirements in terms of enhanced broadband connectivity based on harnessing small cell and mmWave technology. These two in synergy will provide high capacity gain not only through the hyperdense deployment of small cell but also through accessing large swathes of untapped spectrum at mmWave frequencies. The envisaged architecture entails an integrated optical wireless network architecture, where optical technology will complement radio in order to handle the new demands on capacity over the backhaul and fronthaul network, leading to the notion of analog radio over fiber (ARoF). The goal of this chapter is to provide novel approaches to optimize the performances of mmWave ARoF systems that includes developing enabling technology from a digital to signal processing (DSP) and device perspective

Digital signal processing waveform aggregation and its experimental demonstration for next generation mobile fronthaul

L'abstract è presente nell'allegato / the abstract is in the attachmen

Centralized and partial decentralized design for the Fog Radio Access Network

Fog Radio Access Network (F-RAN) has been shown to be a promising network architecture for the 5G network. With F-RAN, certain amount of signal processing functionalities are pushed from the Base Station (BS) on the network edge to the BaseBand Units (BBU) pool located remotely in the cloud. Hence, partially centralized network operation and management can be achieved, which can greatly improve the energy and spectral efficiency of the network, in order to meet the requirements of 5G. In this work, the optimal design for both uplink and downlink of F-RAN are intensively investigated

Total Cost of Ownership of Digital vs. Analog Radio-Over-Fiber Architectures for 5G Fronthauling

The article analyzes the total cost of ownership (TCO) of 5G fronthauling solutions based on analog and digital radio-over-fiber (RoF) architectures in cloud radio access networks (C-RANs). The capital and operational expenditures (CAPEX, OPEX) are assessed, for a 10-year period, considering three different RoF techniques: intermediate frequency analog RoF (IF-A-RoF), digital signal processing (DSP) assisted analog RoF (DSP-A-RoF), and digital RoF (D-RoF) based on the common public radio interface (CPRI) specifications. The greenfield deployment scenario under exam includes both fiber trenching (FT) and fiber leasing (FL) options. The TCO is assessed while varying (i) the number of aggregated subcarriers, (ii) the number of three-sector antennas located at the base station, and (iii) the mean fiber-hop length. The comparison highlights the significance that subcarrier aggregation has on the cost efficiency of the analog RoF solutions. In addition, the analysis details the contribution of each cost category to the overall CAPEX and OPEX values. The obtained results indicate that subcarrier aggregation via DSP results in high cost efficiency for a mobile fronthaul network, while a CPRI-based architecture together with FL brings the highest OPEX value

Total Cost of Ownership of Digital vs. Analog Radio-Over-Fiber Architectures for 5G Fronthauling

The article analyzes the total cost of ownership (TCO) of 5G fronthauling solutions based on analog and digital radio-over-fiber (RoF) architectures in cloud radio access networks (C-RANs). The capital and operational expenditures (CAPEX, OPEX) are assessed, for a 10-year period, considering three different RoF techniques: intermediate frequency analog RoF (IF-A-RoF), digital signal processing (DSP) assisted analog RoF (DSP-A-RoF), and digital RoF (D-RoF) based on the common public radio interface (CPRI) specifications. The greenfield deployment scenario under exam includes both fiber trenching (FT) and fiber leasing (FL) options. The TCO is assessed while varying (i) the number of aggregated subcarriers, (ii) the number of three-sector antennas located at the base station, and (iii) the mean fiber-hop length. The comparison highlights the significance that subcarrier aggregation has on the cost efficiency of the analog RoF solutions. In addition, the analysis details the contribution of each cost category to the overall CAPEX and OPEX values. The obtained results indicate that subcarrier aggregation via DSP results in high cost efficiency for a mobile fronthaul network, while a CPRI-based architecture together with FL brings the highest OPEX value

Experimental Demonstration of 100 Gbps/λ C-Band Direct-Detection Downstream PON Using Non-Linear and CD Compensation with 29 dB+ OPL over 0 Km-100 Km

Passive Optical Networks (PON), able to operate at 50 Gbps per wavelength (λ), are under development and standardization, based on intensity-modulation (IM) and direct-detection (DD) systems. The next step in PON evolution will be driven by 5G/6G fronthauling capacity demands, and will require the development of 100 Gbps/λ (and beyond) systems, which poses big challenges if maintaining the DD-format. In this contribution, we analyze a 100 Gbps/λ PON architecture able to preserve the IM-DD approach at the Optical Network Unit (ONU), placing the complexity at the Optical Line Terminal (OLT), thanks to Digital Signal Processing (DSP). We experimentally demonstrate a 100 Gbps/λ transmission using this architecture in the downstream (DS) direction. Chromatic dispersion digital pre-compensation (CD-DPC) in combination with an IQ Mach-Zehnder Modulator (IQ-MZM) is used at the transmitter (TX). Keeping the ONU DSP as simple as possible, as compared with current DSP proposals for 50 Gbps/λ PON, is another main goal of this work. Adaptive equalization (AEQ) is used to correct for linear impairments, in addition to digital non-linear correction (NLC) at the receiver (RX). We compare two NLC approaches: a full Volterra Non-Linear Equalizer (VNLE) and a simpler NLC technique based on a square-root like function (SQRT). Operation over standard single-mode fiber (SMF) in C-band, achieving reaches from 0 km to 100 km and Optical Path Loss (OPL) values higher than 29 dB, are shown. The analyzed proposal is directly applicable to Terabit-capable wavelength division multiplexing (WDM)-PON, and can be extended to very high-speed Time Division Multiplexing (TDM)-PON and TWDM-PON, with some modifications discussed here