One of the most engaging challenges for mobile operators today is how to manage the exponential data traffic increase. Mobile data offloading stands out as a promising and low-cost solution to reduce the burden on the cellular network. To make this possible, we need a new hybrid network paradigm that leverages the existence of multiple alternative communication channels. This entails significant modifications in the way data are handled, affecting also the behavior of network protocols. In this paper, we present a comprehensive survey of data offloading techniques in cellular networks and extract the main requirements needed to integrate data offloading capabilities into today's mobile networks. We classify existing strategies into two main categories, according to their requirements in terms of content delivery guarantees: delayed and nondelayed offloading. We overview the technical aspects and discuss the state of the art in each category. Finally, we describe in detail the novel functionalities needed to implement mobile data offloading in the access network, as well as current and future research challenges in the field, with an eye toward the design of hybrid architectures.

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Data Offloading Techniques in Cellular Networks: A Survey

The ongoing development of mobile communication networks to support a wide range of superfast broadband services has led to massive capacity demand. This problem is expected to be a significant concern during the deployment of the 5G wireless networks. The demand for additional spectrum to accommodate mobile services supporting higher data rates and having lower latency requirements, as well as the need to provide ubiquitous connectivity with the advent of the Internet of Things sector, is likely to considerably exceed the supply, based on the current policy of exclusive spectrum allocation to mobile cellular systems. Hence, the imminent spectrum shortage has introduced a new impetus to identify practical solutions to make the most efficient use of scarce licensed bands in a shared manner. Recently, the concept of dynamic spectrum sharing has received considerable attention from regulatory bodies and governments globally, as it could potentially open new opportunities for mobile operators to exploit spectrum bands whenever they are underutilized by their owners, subject to service level agreements. Although various sharing paradigms have been proposed and discussed, the impact and performance gains of different schemes can be scenario-specific, and may vary depending on the nature of the sharing players, the level of sharing and spectrum access scheme. In this survey, we study the main concepts of dynamic spectrum sharing, different sharing scenarios, as well as the major challenges associated with sharing of licensed bands. Finally, we conclude this survey with open research challenges and suggest some future research directions.

Licensed Spectrum Sharing Schemes for Mobile Operators: A Survey and Outlook

The Cognitive Radio and the Cognitive Radio Networks have recently become one of the most intensively studied paradigms in wireless communications. The main distinctive characteristic with respect to the radio environmental conditions in which the Cognitive Radio Network operates is the time/frequency/space-dependent availability of the spectral resources, a phenomenon commonly referred as spectrum hete-rogeneity. This phenomenon imposes redefinition of the protocol stack by introducing new communication protocols for the Cognitive Radio Network including new Medium Access Control protocols. The Cognitive MAC (C-MAC) protocols employ number of mechanisms that address spectrum heterogeneity and provide technical strategies for smart exploitation of spectrum's current underutilized time/space/frequency regions that enables large spectrum efficiency gains while maximizing the transparency of the Cognitive Radio Networks to the primary system. The classification and systematization of the existing C-MAC proposals is a complex task due to many C-MAC related aspects. This survey introduces and develops generic, modular and easily extensible layout for classification and systematization of C-MAC protocols referred as C-MAC cycle. Each C-MAC protocol can be easily fragmented, mapped and visualized using the C-MAC cycle, regardless of the operational scenario and settings. The survey offers extensive overview on the state-of-the-art advances in C-MAC protocol engineering by reviewing existing and up-to-date technical solutions, identifies their basic characteristics and maps them into the C-MAC cycle. The survey also highlights the role of regulative and standardization activities on C-MAC cycle.

Medium Access Control Protocols in Cognitive Radio Networks: Overview and General Classification

Self-organizing networks promise significant expenditure savings for operators when rolling out modern cellular network infrastructure, such as Long-Term Evolution (LTE) and LTE-Advanced systems. Savings in capital expenditures (CAPEX) and operational expenditures (OPEX) can be achieved in both the network deployment and network operation phase. Particularly, self-organized optimization of network coverage and network capacity is a key challenge to cope with the boost in mobile data traffic that is expected in the next years and to benefit from the growing market. We present a traffic-light-related approach to autonomous self-optimization of tradeoff performance indicators in LTE multitier networks. Introducing a low-complexity interference approximation model, the related optimization problem is formulated as a mixed-integer linear program and is embedded into a self-organized network operation and optimization framework. Tuning site activity, transmission power, and antenna downtilt are parameters of eNodeBs and Home eNodeBs. The optimization procedure is carried out considering time-variant optimization parameters that are automatically adapted with respect to changes in the network. Simulation-based evaluation of representative case studies demonstrates applicability and the benefit potential of our overall concept.

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Autonomous Self-Optimization of Coverage and Capacity in LTE Cellular Networks

The NarrowBand Internet of Things (NB-IoT) is one of the most promising technologies that fits the requirements of the low-power wide area networks (LPWAN). NB-IoT targets on supporting communications for small amount of data during a relatively long period of time (i.e., delay tolerant), which is one of the key features of IoT applications. Several studies have been conducted by some standard working groups to define the standards for NB-IoT. For example, the working group 3GPP aims to provide communication protocols with low energy consumption, good coverage penetration, and so on. Compared with the existing wireless communication protocols, less spectrum is allocated for NB-IoT. Thus, how to more efficiently use the resource/spectrum (i.e., resource allocation and scheduling) is one of the key issues. In this paper, we first describe the design of the physical layer for the downlink communication, especially the scheduling process. Secondly, we discuss the issues for resource allocation in NB-IoT while the delay requirement in the physical layer is satisfied. Thirdly, we discuss the open questions and possible solutions.

A survey on NB-IoT downlink scheduling: Issues and potential solutions

Much hype is spread about the performance of WiMAX, and many contrary statements are put forward A reason for the confusion is that little or no published material exists about WiMAX performance based on measurements in real life field trials We therefore set up a test-bed using WiMAX equipment now on the marked, and did extensive, real life field trial measurements This paper presents measured throughput and received signal strength under conditions typical for fixed WiMAX systems Based on the results, throughput is analyzed and analytical expressions representing the measurements are derived for easy use in models

Fixed WiMAX Field Trial Measurements and Analyses

The fifth generation (5G) of mobile radio technologies has been defined as a new delivery model where services are tailored to specific vertical industries. 5G supports three types of services with different and heterogeneous requirements, i.e. enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC) and massive Machine-Type Communications (mMTC). These services are directly related to exemplary verticals such as media, vehicular communications or the Industry 4.0. This work provides a detailed analysis and performance evaluation of 5G New Radio (NR) against a set of Key Performance Indicators (KPI), as defined in the International Mobile Telecommunications 2020 (IMT-2020) guidelines, and provides an overview about the fulfillment of their associated requirements. The objective of this work is to provide an independent evaluation, complementing the Third Generation Partnership Project (3GPP) contribution. From the original group of sixteen KPIs, eleven of them have been carefully selected, paying special attention to eMBB services. Results show that 5G NR achieves all considered requirements, therefore fulfilling the specific market's needs for years to come.

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5G New Radio Evaluation Against IMT-2020 Key Performance Indicators

Self-Organizing Networks (SON) is a collection of functions for automatic configuration, optimization, diagnostisation and healing of cellular networks. It is considered to be a necessity in future mobile networks and operations due to the increased cost pressure. The main drivers are essentially to reduce CAPEX and OPEX, which would otherwise increase dramatically due to increased number of network parameters that has to be monitored and set, the rapidly increasing numbers of base stations in the network and parallel operation of 2G, 3G and Evolved Packet Core (EPC) infrastructures. This paper presents evaluations on the use of some of the most important SON components. Mobile networks are getting more complex to configure, optimize and maintain. Many SON functions will give cost savings and performance benefits from the very beginning of a network deployment and these should be prioritized now. But even if many functions are already available and can give large benefits, the field is still in its infancy and more advanced functions are either not yet implemented or have immature implementations. It is therefore necessary to have a strategy for how and when different SON functions should be introduced in mobile networks.

https://downloads.hindawi.com/journals/jcnc/2012/862527.pdf

Benefits of Self-Organizing Networks (SON) for Mobile Operators

A key feature of the Long-Term Evolution (LTE) system is that the packet scheduler can make use of the channel quality information (CQI), which is periodically reported by user equipment either in an aggregate form for the whole downlink channel or distinguished for each available subchannel. This mechanism allows for wide discretion in resource allocation, thus promoting the flourishing of several scheduling algorithms, with different purposes. It is therefore of great interest to compare the performance of such algorithms under different scenarios. Here, we carry out a thorough performance analysis of different scheduling algorithms for saturated User Datagram Protocol (UDP) and Transmission Control Protocol (TCP) traffic sources, as well as consider both the time- and frequency-domain versions of the schedulers and for both flat and frequency-selective channels. The analysis makes it possible to appreciate the difference among the scheduling algorithms and to assess the performance gain, in terms of cell capacity, users' fairness, and packet service time, obtained by exploiting the richer, but heavier, information carried by subchannel CQI. An important part of this analysis is a throughput guarantee scheduler, which we propose in this paper. The analysis reveals that the proposed scheduler provides a good tradeoff between cell capacity and fairness both for TCP and UDP traffic sources.

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Ole Grondalen

Papers

Fixed WiMAX Field Trial Measurements and Analyses

5G New Radio Evaluation Against IMT-2020 Key Performance Indicators

Benefits of Self-Organizing Networks (SON) for Mobile Operators

Scheduling Policies in Time and Frequency Domains for LTE Downlink Channel: A Performance Comparison

Business case evaluations for LTE network offloading with cognitive femtocells