Nokia (Germany)

We argue for network slicing as an efficient solution that addresses the diverse requirements of 5G mobile networks, thus providing the necessary flexibility and scalability associated with future network implementations. We elaborate on the challenges that emerge when designing 5G networks based on network slicing. We focus on the architectural aspects associated with the coexistence of dedicated as well as shared slices in the network. In particular, we analyze the realization options of a flexible radio access network with focus on network slicing and their impact on the design of 5G mobile networks. In addition to the technical study, this article provides an investigation of the revenue potential of network slicing, where the applications that originate from this concept and the profit capabilities from the network operator's perspective are put forward.

The 6G vision of creating authentic digital twin representations of the physical world calls for new sensing solutions to compose multi-layered maps of our environments. Radio sensing using the mobile communication network as a sensor has the potential to become an essential component of the solution. With the evolution of cellular systems to mmWave bands in 5G and potentially sub-THz bands in 6G, small cell deployments will begin to dominate. Large bandwidth systems deployed in small cell configurations provide an unprecedented opportunity to employ the mobile network for sensing. In this paper, we focus on the major design aspects of such a cellular joint communication and sensing (JCAS) system. We present an analysis of the choice of the waveform that points towards choosing the one that is best suited for communication also for radar sensing. We discuss several techniques for efficiently integrating the sensing capability into the JCAS system, some of which are applicable with NR air-interface for evolved 5G systems. Specifically, methods for reducing sensing overhead by appropriate sensing signal design or by configuring separate numerologies for communications and sensing are presented. Sophisticated use of the sensing signals is shown to reduce the signaling overhead by a factor of 2.67 for an exemplary road traffic monitoring use case. We then present a vision for future advanced JCAS systems building upon distributed massive MIMO and discuss various other research challenges for JCAS that need to be addressed in order to pave the way towards natively integrated JCAS in 6G.

Routing services on the web and on hand-held devices have become ubiquitous in the past couple of years. Websites like Bing or Google Maps allow users to find routes between arbitrary locations comfortably in no time. Likewise onboard navigation units belong to the off-the-shelf equipment of virtually any new car.

In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. This approach enables the optimization of the transceiver in a single end-to-end process. We illustrate the benefits of this method by applying it to intensity modulation/direct detection (IM/DD) systems and show that we can achieve bit error rates below the 6.7% hard-decision forward error correction (HD-FEC) threshold. We model all componentry of the transmitter and receiver, as well as the fiber channel, and apply deep learning to find transmitter and receiver configurations minimizing the symbol error rate. We propose and verify in simulations a training method that yields robust and flexible transceivers that allow-without reconfiguration-reliable transmission over a large range of link dispersions. The results from end-to-end deep learning are successfully verified for the first time in an experiment. In particular, we achieve information rates of 42 Gb/s below the HD-FEC threshold at distances beyond 40 km. We find that our results outperform conventional IM/DD solutions based on two- and four-level pulse amplitude modulation with feedforward equalization at the receiver. Our study is the first step toward end-to-end deep learning based optimization of optical fiber communication systems.

We discuss the use of a coherent digital receiver for the compensation of linear transmission impairments and polarization demultiplexing in a transmission system compatible with a future 100-Gb/s Ethernet standard. We present experimental results on the transmission performance of 111 Gbit/s POLMUX-RZ-DQPSK. For a dense WDM setup with channels carrying 111 Gbit/s with a 50 GHz channel spacing (2.0 bits/s/Hz), we show the feasibility of 2375 km transmission. This is enabled through coherent detection which results in excellent noise performance, and subsequent electronic equalization which provides the high tolerance to polarization mode dispersion and chromatic dispersion (CD). Furthermore, we discuss the impact of sampling and digital signal processing with either 1 or 2 samples/bit. We show that when combined with low-pass electrical filtering, 1 sample/bit signal processing is sufficient to obtain a large tolerance towards CD. The proposed modulation and detection techniques enable 111 Gbit/s transmission that is directly compatible with the existing 10 Gbit/s infrastructure.

Fiber-optic communication systems are nowadays facing serious challenges due to fast growing demand on capacity from various new applications and services.It is now well recognised that nonlinear effects limit the spectral efficiency and transmission reach of modern fiber-optic communications.Nonlinearity compensation is therefore widely believed to be of paramount importance for increasing the capacity of future optical networks.Recently, there has been a steadily growing interest in the application of a powerful mathematical tool -the nonlinear Fourier transform (NFT) -in the development of fundamentally novel nonlinearity mitigation tools for fiber-optic channels.It has been recognized that, within this paradigm, the nonlinear crosstalk due to the Kerr effect is effectively absent, and fiber nonlinearity due to Kerr effect can enter as a constructive element rather than a degrading factor.The novelty and the mathematical complexity of the NFT, the versatility of the proposed system designs, and the lack of a unified vision of an optimal NFT-type communication system however constitute significant difficulties for communication researchers.In this paper, we therefore survey the existing approaches in a common framework and review the progress in this area with a focus on practical implementation aspects.First, an overview of existing key algorithms for the efficacious computation of the direct and inverse NFT is given, and the issues of accuracy and numerical complexity are elucidated.We then describe different approaches for the utilization of the NFT in practical transmission schemes.After that we discuss the differences, advantages and challenges of various recently emerged system designs employing the NFT, and the efficiency estimation available up-to-date.With many practical implementation aspects still being open, our minireview is aimed at helping researchers to assess the perspectives, understand the bottle-necks, and envision the development paths in the upcoming of NFT-based transmission technologies.

Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).

This article studies the processing principles, implementation challenges, and performance of orthogonal frequency-division multiplexing (OFDM)-based radars, with particular focus on the fourth-generation Long-Term Evolution (LTE) and fifth-generation (5G) New Radio (NR) mobile networks' base stations and their utilization for radar/sensing purposes. First, we address the problem stemming from the unused subcarriers within the LTE and NR transmit signal passbands and their impact on frequency-domain radar processing. In particular, we formulate and adopt a computationally efficient interpolation approach to mitigate the effects of such empty subcarriers in the radar processing. We evaluate the target detection and the corresponding range and velocity estimation performance through computer simulations and show that high-quality target detection as well as high-precision range and velocity estimation can be achieved. In particular, 5G NR waveforms, through their impressive channel bandwidths and configurable subcarrier spacing, are shown to provide very good radar/sensing performance. Then, a fundamental implementation challenge of transmitter-receiver (TX-RX) isolation in OFDM radars is addressed, with specific emphasis on shared-antenna cases, where the TX-RX isolation challenges are the largest. It is confirmed that from the OFDM radar processing perspective, limited TX-RX isolation is primarily a concern in the detection of static targets, while moving targets are inherently more robust to transmitter self-interference (SI). Properly tailored analog/RF and digital SI cancellation solutions for OFDM radars are also described and implemented and shown through RF measurements to be key technical ingredients for practical deployments, particularly from static and slowly moving targets' point of view.

In this paper, we outline the design of signal processing (DSP) algorithms with blind estimation for 100-G coherent optical polarization-diversity receivers in single-carrier systems. As main degrading optical propagation effects, we considered chromatic dispersion (CD), polarization-mode dispersion (PMD), polarization-dependent loss (PDL), and cross-phase modulation (XPM). In the context of this work, we developed algorithms to increase the robustness of the single DSP receiver modules against the aforesaid propagation effects. In particular, we first present a new and fast algorithm to perform blind adaptive CD compensation through frequency-domain equalization. This low complexity equalizer component inherits a highly precise estimation of residual dispersion independent from previous or subsequent blocks. Next, we introduce an original dispersion-tolerant timing recovery and illustrate the derivation of blind polarization demultiplexing, capable to operate also in condition of high PDL. At last, we propose an XPM-mitigating carrier phase recovery as an extension of the standard Viterbi-Viterbi algorithm.

While 5G is being deployed and the economy and society begin to reap the associated benefits, the research and development community starts to focus on the next, 6th Generation (6G) of wireless communications. Although there are papers available in the literature on visions, requirements and technical enablers for 6G from various academic perspectives, there is a lack of joint industry and academic work towards 6G. In this paper a consolidated view on vision, values, use cases and key enabling technologies from leading industry stakeholders and academia is presented. The authors represent the mobile communications ecosystem with competences spanning hardware, link layer and networking aspects, as well as standardization and regulation. The second contribution of the paper is revisiting and analyzing the key concurrent initiatives on 6G. A third contribution of the paper is the identification and justification of six key 6G research challenges: (i) “connecting”, in the sense of empowering, exploiting and governing, intelligence; (ii) realizing a network of networks, i.e., leveraging on existing networks and investments, while reinventing roles and protocols where needed; (iii) delivering extreme experiences, when/where needed; (iv) (environmental, economic, social) sustainability to address the major challenges of current societies; (v) trustworthiness as an ingrained fundamental design principle; (vi) supporting cost-effective global service coverage. A fourth contribution is a comprehensive specification of a concrete first-set of industry and academia jointly defined use cases for 6G, e.g., massive twinning, cooperative robots, immersive telepresence, and others. Finally, the anticipated evolutions in the radio, network and management/orchestration domains are discussed.

UTRAN long term evolution is currently being standardized in 3GPP with the aim of more than twice the capacity over high-speed packet access. The chosen multiple access for uplink is single carrier FDMA, which avoids the intra-cell interference typical of CDMA systems, but it is still sensitive to inter-cell interference. As a result, the role of the power control becomes decisive to provide the required SINR, while controlling at the same time the interference caused to neighboring cells. This is the target of the fractional power control (FPC) algorithm lately approved in 3GPP. This paper evaluates in detail the impact of a FPC scheme on the SINR and interference distributions in order to provide a sub-optimal configuration tuned for both interference- and noise-limited scenarios.

A few years ago it was recognized that the vision of a truly low-cost, low-power radio-based cable replacement was feasible. Such a ubiquitous link would provide the basis for portable devices to communicate together in an ad hoc fashion by creating personal area networks which have similar advantages to their office environment counterpart - the local area network (LAN). Bluetooth is an effort by a consortium of companies to design a royalty free technology specification enabling this vision. This article describes the vision and goals of the Bluetooth program and introduces the radio-based technology.

In this paper we present system level simulation results of a self-optimizing load balancing algorithm in a long-term-evolution (LTE) mobile communication system. Based on previous work, we evaluate the network performance of this algorithm that requires the load of a cell as input and controls the handover parameters. We compare the results for different simulation setups: for a basic, regular network setup, a non-regular grid with different cell sizes and also for a realistic scenario based on measurements and realistic traffic setup.

Cloud radio access network (C-RAN) refers to the visualization of base station functionalities by means of cloud computing. This results in a novel cellular architecture in which low-cost wireless access points, known as radio units or remote radio heads, are centrally managed by a reconfigurable centralized "cloud", or central, unit. C-RAN allows operators to reduce the capital and operating expenses needed to deploy and maintain dense heterogeneous networks. This critical advantage, along with spectral efficiency, statistical multiplexing and load balancing gains, make C-RAN well positioned to be one of the key technologies in the development of 5G systems. In this paper, a succinct overview is presented regarding the state of the art on the research on C-RAN with emphasis on fronthaul compression, baseband processing, medium access control, resource allocation, system-level considerations and standardization efforts.

The post-pandemic future will offer tremendous opportunity and challenge from transformation of the human experience linking physical, digital and biological worlds: 6G should be based on a new architecture to fully realize the vision to connect the worlds. We explore several novel architecture concepts for the 6G era driven by a decomposition of the architecture into platform, functions, orchestration and specialization aspects. With 6G, we associate an open, scalable, elastic, and platform agnostic het-cloud, with converged applications and services decomposed into micro-services and serverless functions, specialized architecture for extreme attributes, as well as open service orchestration architecture. Key attributes and characteristics of the associated architectural scenarios are described. At the air-interface level, 6G is expected to encompass use of sub-Terahertz spectrum and new spectrum sharing technologies, air-interface design optimized by AI/ML techniques, integration of radio sensing with communication, and meeting extreme requirements on latency, reliability and synchronization. Fully realizing the benefits of these advances in radio technology will also call for innovations in 6G network architecture as described.

Transmission of a 73.7 Tb/s (96 x 3 x 256-Gb/s) DP-16QAM mode-division-multiplexed signal over 119 km of few-mode fiber transmission line incorporating an inline multi mode EDFA and a phase plate based mode (de-)multiplexer is demonstrated. Data-aided 6 x 6 MIMO digital signal processing was used to demodulate the signal. The total demonstrated net capacity, taking into account 20% of FEC-overhead and 7.5% additional overhead (Ethernet and training sequences), is 57.6 Tb/s, corresponding to a spectral efficiency of 12 bits/s/Hz.

Energy efficient communication devices are essential to minimize the operational cost of future networks and to reduce the negative effects of global warming. In this paper we propose a novel energy reduction approach on network level that takes load-dependent energy consumption information of communication equipment into account. Case study calculation results show that energy savings of more than 35% and with it operational cost can be saved by applying energy profile aware routing.

We investigate the risk of overestimating the performance gain when applying neural network-based receivers in systems with pseudorandom bit sequences or with limited memory depths, resulting in repeated short patterns. We show that with such sequences, a large artificial gain can be obtained, which comes from pattern prediction rather than predicting or compensating the studied channel/phenomena.

Systems modulating, transporting, and detecting lightwaves have evolved tremendously in the past four decades. The first systems, which were relying on intensity modulation with direct detection have little in common with those manufactured today. Not only have optical fibers and electro-optic components drastically improved, systems now employ digital signal processing for its agility and versatility, initially deployed for long-reach communication systems but slowly making its way into systems covering shorter distances. Due to several network transforming reasons, we are now observing needs for massive deployment of fiber-optic transceivers covering distances of only 10 to 100 km but delivering much faster throughputs than those offered by legacy systems targeting these distances while maintaining low cost and power consumption, small foot print and very-low latency. In this paper, we review the evolution of fiber-optic communication systems, from intensity modulation with direct detection to coherent transceivers and digital signal processing-assisted direct detection. We address the main impairments preventing large bitrate-reach products for systems relying on intensity modulation with direct detection. We present a few reasons leading to the recent surge of the short-reach transceiver market segment, especially transceivers covering distances between 10 to 100 km. We summarize a few proposals for this market modulating and recovering an increasing number of degrees of freedom of the lightwave while maintaining self-beating direct detection. We conclude with remarks on the use of coherent technologies to address this market segment.

We present a mathematical framework for quantitative investigations of self-optimizing wireless networks (SON) with focus on the 3GPP long-term evaluation (LTE) system. Basic target functions, such as the signal-to-noise ratio distribution, the number of satisfied users, or energy efficiency are derived as a figure of merit, including the impact of adaptation of downlink transmit power adaptation, antenna tilt, and the handover parameter. The framework is exemplified by basic investigations on load balancing.