What is the software that we need to communicate between device and computer?

10.6.2 Channel bonding

Despite the abundance of underutilized TV channels available for opportunistic use, the small channel bandwidth forces CRs to operate at data rates of less than 20 Mbps. Dividing this between device-to-device communication and upstream communication can limit the achievable capacity of the entire network. To overcome this, channel bonding, which mimics spectrum aggregation in LTE, can be used. To properly protect incumbent users, the 802.22 standard limits channel bonding to adjacent channels, which is not always available, as shown in Figure 10.4. As was discussed in [BUD 08], non-contiguous OFDM can be easily used to concurrently use multiple disjoint spectrum channels without causing harmful interference to incumbent users. However, in the context of coexisting CR networks, this can lead to a challenging channel management problem.

Features and shortcomings of 5G wireless networks

5G systems come with a number of disruptive features which have direct impact in positioning capabilities [WSGD+17]. These advanced features include network densification, operation in mmWave bands and massive MIMO [ABC+14], and device-to-device communication [BHL+14]. The impact of such features on positioning capabilities is discussed next.

Higher bandwidth and new frequency bands: 5G systems include operation in new frequency bands in the mmWave spectrum (above 24 GHz), where more bandwidth is available than in the crowded below 6 GHz bands. This has a dual effect on positioning. On the one hand, larger bandwidths allow for a higher degree of delay resolution, so that individual multipath components can be estimated and tracked. On the other, higher carrier frequencies lead to more optical-like propagation, with reduced diffraction and very limited trough-wall penetration [RMSS15]. Hence, only few paths will be present and each path has a geometric connection to the physical propagation environment. In the sub-6 GHz band, large bandwidths will also be available with carrier aggregation, but more dominant propagation paths will be present.

More antennas: With higher carrier frequencies and shorter wavelengths comes the opportunity to pack more antennas into a given area [SRH+14]. Above 24 GHz, planar arrays with hundreds of antennas are feasible. Using more antenna elements provides the opportunity to increase the resolution of the channel in the spatial domain (angle of arrival and angle of departure, in azimuth and elevation), providing a new way to separate multipath components (other than in the delay domain). Hence, combined with higher carrier frequencies and large bandwidths, using more antennas leads to a high degree of resolvability and high accuracy of estimating multipath components, each with an associated delay, angle of arrival, and angle of departure. This implies that absolute positioning with respect to a single reference transmitter is possible, as well as identification of the sources of each reflected or scattered path (cf. Section 9.4).

Network densification: Increased area spectral efficiency is obtained from a denser deployment of base stations with a reduced coverage area and aggressive spectral reuse. This requires sophisticated solutions for interference and mobility management [BLM+14]. For positioning, ultra-dense networks are beneficial since the distance to reference transmitters is reduced. The reason is two-fold. Firstly, with ranges from 5-50 meters, the probability of having a line-of-sight connection is upward of 50% [Li16], which in turn is highly beneficial for localization as the delay and angle information from the optical line-of-sight path provide the most location-relevant information of all multipath components. Secondly, with a dense radio-access network seamless multi-connectivity can be established between terminals and base-station via multi-beam communication. This increases the robustness to line-of-sight obstruction and improves the localization accuracy.

Device-to-device communications: Since LTE Release 12, D2D communication is considered a candidate technology for proximity detection. In 5G, D2D will be native, for high-rate links between nearby users, benefiting from low path loss, low transmit powers, and extremely low latency [TUY14]. Such D2D links also provide an additional source of positioning information, where well-positioned users can serve as (noisy) location references for users out of direct coverage of base stations. Moreover, D2D links can provide relative positioning information as well as a mean to develop efficient cooperative positioning schemes for achieving higher accuracy.

2.1.2 Tunnel mode

In tunnel mode, the entire IP packet is encrypted and/or authenticated. It is then encapsulated into a new IP packet with a new IP header. Tunnel mode is used to create VPNs for network-to-network communications (e.g., between routers to link sites), device-to-network communications (e.g., remote user access) and device-to-device communications (e.g., private chat).

IPsec support is usually implemented in the operating system kernel. It was originally developed in conjunction with IPv6 and was originally required to be supported by all standards-compliant implementations of IPv6 but later it was made only a recommendation. IPsec is also optional for IPv4 implementations. The OpenBSD IPsec stack was the first implementation that was available under a permissive open-source license, and was therefore copied widely.

In 2013, as part of Snowden leaks, it was revealed that the US NSA had been actively working to “Insert vulnerabilities into commercial encryption systems, IT systems, networks, and endpoint communications devices used by targets” as part of the Bullrun program. There are allegations that IPsec was a targeted encryption system but no proof has been uncovered.

11.1 Introduction

Long-Term Evolution (LTE) is a new communication standard developed by the Third Generation Partnership Project (3GPP). Currently, LTE is becoming a 4G reference architecture due to its widespread adoption among leading operators of mobile telecommunications. LTE is therefore foreseen as an important foundation for future 5G networks. In the shift towards 5G, several open issues have to be worked out in LTE. They emerge due to severe requirements put on the infrastructure of the future networks. First, mobile users will expect high capacity channels, in which capacity is measured in several Gbps. Second, new applications will be considered with high densities of connected devices. Third, 5G networks will have to accommodate new types of connected devices such as household appliances, meters and connected cars. Fourth, direct device-to-device (D2D) communication will have to be formulated for sharing information in a local context. In the broader view, network-based communication in the licensed band can provide enhanced Quality of Service (QoS) for D2D scenarios. Fifth, extreme reliability (e.g. medical applications) and ultra-low latencies (e.g. VANET applications) have to be considered. Sixth, for Internet of Things (IoT) applications, communication with high energy efficiency is required. Finally, in current mobile networks, we are approaching Shannon’s capacity limit. Therefore, an enhanced channel capacity shall be provided through the adoption of a new spectrum range. According to the aforementioned picture, 5G will be a holistic ecosystem providing connectivity in a wide range of application use cases. It is therefore natural to seamlessly integrate Public Safety (PS) applications with 5G using LTE as a starting point.

LTE has been selected by the National Public Safety Telecommunications Council (NPSTC) in the USA as a basis for PS. Other regions of the world, such as the European Union, will most probably adapt LTE for PS as well. Currently existing PS systems such as Project 25 (P25) and Terrestrial Trunked Radio (TETRA) are already reliable in providing voice communication; however, new high bandwidth applications in PS can only be provided by LTE. Currently, LTE does not natively support PS, as it was designed to support commercial cellular networking. It does not allow for a required level of reliability, security and confidentiality. Moreover, device-to-device communication is also not appropriately taken into account. Hence, a new research area is emerging on an appropriate adaptation of LTE towards PS networking. 3GPP already addressed several of these issues in their studies such as device-to-device communication, Evolved Universal Terrestrial Radio Access Network (E-UTRAN) and Mission-Critical Push-to-Talk (MCPTT). 3GPP worked out specific properties of both the User Equipment (UE) and the evolved NodeB (the LTE base station eNB) that have to be taken into account in the provision of PS applications with respect to various availability levels of E-UTRAN. More specifically, 3GPP consider an isolated E-UTRAN scenario, in which an eNB operates with no access or limited connectivity to the LTE core (EPC). In such situations, there is a need for rapid provisioning of the LTE network. The 3GPP does not study, however, how distributed disconnected (isolated) eNBs exchange information. This is left for vendors to implement their own proprietary solutions [FAV 16].

Delay Tolerant Networking (DTN) and Information Centric Networks (ICN) can provide added value to LTE. Over the years, DTN has become an emerging push-based paradigm for challenge networks. When a disaster occurs, communication has to be reestablished to ensure PS in areas in which infrastructure is limited, power supplies might be damaged and/or the network is disconnected from its main core. DTN is an Internet architecture that overcomes technical difficulties that may exist in these challenge environments. In a disaster scenario, we must assume that nodes may be disconnected from their network and/or from each other. Hence, it is possible that information may not be immediately delivered to the destination due to a momentary lack of end-to-end connectivity.

The main advantage of DTN is that it enables communication in intermittent networks through its store-carry-and-forward mechanism. Every node in the network could store a message in its buffer when no connection is available. The node stores the message and can move to any direction, until a connection reappears. Then, the node forwards the message to other nodes so that the message can gradually approach the destination. In addition, another advantage of DTN includes the potential of working in heterogeneous networks (IP/non-IP) using the bundle protocol. Bundle protocol enables messages to be of variable sizes and enables multi-hop communication in order for a message to reach its final destination. This opportunistic model could change its routing decisions depending on the network topology. These two main advantages of DTN are exploited in PS to ensure that a message reaches rescue teams in disaster scenarios.

In addition, another concept addressing PS in disaster situations is ICN based. ICN provides a pull strategy for content retrieval using content description for addressing purposes. It is radically different from current networks, which use endpoint identifiers to locate the content. The store-carry-and-forward mechanism is an intrinsic property of ICN, since it does not rely on end-to-end communication, but instead communication is established based on the content of the exchanged messages and not on the location of the host. It can therefore support intermittent connectivity in a catastrophic environment, i.e. scenarios in which isolated nodes have to communicate with rescue teams.

In conclusion, the aforementioned advantages of 5G and DTN/ICN make their combination a perfect candidate to ensure PS in catastrophic scenarios. The rest of this chapter is structured as follows: in section 2, we present related work about MEC systems and DTN/ICN architectures; section 3 presents the proposed MEC system architecture; in section 4, we illustrate an example implementation of the MEC architecture, and finally we conclude in section 5.

4.7 New Scenarios

LTE was originally designed as a mobile broadband system, aiming at providing high data rates and high capacity over wide areas. The evolution of LTE has added features improving capacity and data rates, but also enhancements making LTE highly relevant also for new use cases. Operation in areas without network coverage, for example in a disaster area, is one example, resulting in support for device-to-device commination being included in the LTE. Massive machine-type communication, where a large number of low-cost devices, for example sensors, are connected to a cellular network is another example. V2V/V2X and remote-controlled drones are yet other examples of new scenarios.

4.7.1 Device-To-Device Communication

Cellular systems, such as LTE, are designed assuming that devices connect to a base station to communicate. In most cases this is an efficient approach as the server with the content of interest is typically not in the vicinity of the device. However, if the device is interested in communicating with a neighboring device, or just detecting whether there is a neighboring device that is of interest, the network-centric communication may not be the best approach. Similarly, for public safety, such as a first responder officer searching for people in need in a disaster situation, there is typically a requirement that communication should also be possible in the absence of network coverage.

To address these situations, release 12 introduced network-assisted device-to-device communication using parts of the uplink spectrum (Fig. 4.9). Two scenarios were considered when developing the device-to-device enhancements, in coverage as well as out-of-coverage communication for public safety, and in coverage discovery of neighboring devices for commercial use cases. In release 13, device-to-device communication was further enhanced with relaying solutions for extended coverage. The device-to-device design also served as the basis for the V2V and V2X work in release 14.

Figure 4.9. Device-to-device communciation.

4.7.4 V2V and V2X

Intelligent transportation systems (ITSs) refer to services to improve traffic safety and increase efficiency. Examples are vehicle-to-vehicle communication for safety, for example to transmit messages to vehicles behind when the car in front breaks. Another example is platooning where several trucks drive very close to each other and follow the first truck in the platoon, thereby saving fuel and reducing CO2 emissions. Communication between vehicles and infrastructure is also useful, for example to obtain information about the traffic situation, weather updates, and alternative routes in case of congestion (Fig. 4.10).

Figure 4.10. Illustration of V2V and V2X.

In release 14, 3GPP specified enhancements in this area, based on the device-to-device technologies introduced in release 12 and quality-of-service enhancements in the network. Using the same technology for communication both between vehicles and between vehicles and infrastructure is attractive, both to improve the performance but also to reduce cost.

10.2 Public safety ad-hoc networking

To date, viable commercial solutions for ad-hoc networking are non-existent. Instead, a number of community projects are being developed by academic institutions, public safety entities, non-profit organizations and individuals. As such, these projects are based mostly on open-source software that makes use of existing information and communication technologies to enable device-to-device communication. Table 10.1 provides a list of several projects that have recently received publicity due to their significant impact on disaster management.

Table 10.1. Community projects for ad-hoc networking

Project nameDevelopersTest sitesTechnology enablersFreifunk [FRE 16]Grassroots initiativeGermany, Afghanistan, Ghana, Vietnam, etc.WiFi mesh networkVillage Telco [ADE 11]Shuttleworth Foundation, in collaboration with DabbaSouth Africa, East Timor, Brazil, Puerto Rico, Colombia, NigeriaWiFi mesh network with analogue telephone adaptorsCommotion Wireless [GER 14]Open Technology InstituteUSA Communities including Washington, Brooklyn and DetroitWiFi mesh networkServal [GAR 13]Resilient Networks LabAustralia, USA, Nigeria, New Zealand, South AfricaWiFi ad-hoc and mesh network together with other long-range radiosSPAN [THO 12]The MITRE CorporationSmall communities worldwideWiFi ad-hoc network

Freifunk (“free radio” in German) was originally conceived as a method of providing communication to remote locations where infrastructure deployment was deemed not commercially feasible. Hence, its main focus was on fixed wireless communications based on WiFi mesh networking. Over the last 10 years, Freifunk evolved into a stable communication technology running under popular wireless networking protocols (including OLSR [CLA 03] and B.A.T.M.A.N [KLE 12] multi-hop routing protocols) that support Internet access.

Village Telco is another fixed WiFi mesh setup that was built to primarily support voice communication and voice messaging in regions where traditional cellular services were not affordable. From its inception, Village Telco has had to use WiFi technology that operates in unlicensed bands in order to keep costs down. To support basic handsets, the project developed analog telephone adaptors based on the OpenBTS [IED 15] technology for software conversions between the GSM protocol stack and the Internet protocols that are used on top of WiFi. At the same time, these adaptors act as repeaters for coverage extension.

Commotion Wireless is yet another WiFi mesh uptake that was purposefully developed to counteract the actions of regimes that tried to suppress freedom of speech. Similar to Village Telco, it also uses OpenBTS to support both feature handsets and WiFi-enabled devices. It has been successfully used by the Red Hook Initiative (RHI) for WiFi access after Hurricane Sandy. Luckily, the RHI building was one of the very few places that had managed to keep power and thus the network operations were maintained.

Serval is a more recent incarnation of Village Telco in which ad-hoc networking is persued to enable communications between mobile devices. Serval is being developed for use by smartphone devices using the Android operating system. Ideally, the software package can be downloaded from any other device that already runs Serval, is automatically installed to the device, and becomes immediately operational. However, the software is not compatible with all devices and thus custom mesh routers are being employed to establish communication and extend network coverage, similar to the case of Village Telco.

Finally, Smart Phone Ad-hoc Network (SPAN) is specifically designed for ad-hoc communication between smartphone devices. Like Serval, it only works on particular smartphone devices running Android and it also makes use of Internet protocols to support communication services. The novelty of SPAN is that it implements a generic networking architecture on top of which any routing algorithm can be implemented. At the same time, the SPAN operations are transparent to all layers above and thus no software updates are necessary for any of the applications installed on the devices. Of course, a number of other projects of similar nature also exist, including Project Byzantium (http://project-byzantium.org/), LifeNet (www.thelifenetwork.org/) and PodNet [HEL 10].

Both Freifunk and Village Telco have been created to support fixed access networks and thus reliability is their biggest concern. Commotion Wireless, Serval and SPAN aim for immediate network availability to allow instantaneous communication. Hence, network survivability is not their primary concern. Furthermore, all these projects are similar in the sense that they try to offer a common ground on top of which Internet protocols can run. Unfortunately, it is becoming increasingly clear that such an approach: (1) wastes valuable energy that is crucial for network survivability (especially for battery-operated mobile devices) (2) entails too much signaling overhead and (3) suffers from scalability issues [DAR 13].

8.4.3 Visible Light Communication and Li-Fi for Internet of Things

The number of IoT devices is predicted to be over 28 billion in 2020 and beyond. Because of the shortage of the conventional radio-frequency spectrum, VLC can be a better alternative to meet the tremendous demand for IoT. VLC integrated with IoT has the potential for a wide range of applications; for example, indoor, smart city, industry, hospital, and transportation. VLC applications for device-to-device communication require reliable uplink along with high-speed downlink, which uses LEDs and photodetectors integrated into the device. Some of the recently developed VLC work in darkness and therefore are much more energy efficient than the conventional VLC, and can be extremely suitable for IoT applications. A recently proposed system design to overcome the limitations of traditional VLC combines VLC in dark and an orthogonal frequency division multiplexing method for data transmission and mapping the serial data using quadrature amplitude modulation to accomplish a high data rate of 100 Gb/s or more as well as taking advantage of lower energy consumption [6] suitable for IoT. In some other applications IoT networks may only require very low data rate communication, for example, for transmitting sensing or identity information. For implementation of a VLC link on existing computer communication some of the standards and interfaces such as universal receiver/transmitter (UART) are used. A VLC-over-UART system has been discussed for these types of applications [7]. The details of VLC are described and discussed in an earlier chapter.

Li-Fi is a new technology that allows mobile devices and other connected objects to connect to each other by using LED lights, which transmit data by modulating the light signals. Light signals are received and converted back into data by a dongle connected to the device. Every one of the billions of light bulbs in use today in the world equipped with Li-Fi technology can be thought of as a wireless hotspot delivering connectivity at very high speeds. A Li-Fi–enabled light bulb can transmit data at speeds of 224 Gb/s (demonstrated in laboratory tests). The details of Li-Fi and the working principles were discussed in an earlier chapter and are not repeated here. Li-Fi is therefore a technology breakthrough with potential for a new future of global communications. With proper security to secure IoT infrastructures, the required level of reliability and privacy to the Li-Fi devices can be achieved. This concept will therefore provide a powerful solution for connecting global IoT implementing Li-Fi technology. Note that IoT is part of the Internet, which comprises billions of intelligent communicating things or Internet-connected objects with sensing, and data capabilities. Embedded sensors in each Internet-connected object will capture enormous amounts of data that need to be transmitting very quickly, which requires high bandwidth. Li-Fi can therefore provide the potential solution. Li-Fi can be used to connect with the Internet-connected objects to communicate quickly only in the local area. There is a need for a flow control protocol that synchronizes Li-Fi and Internet for very fast transmission and reception of information that requires design of a new protocol for this purpose. A Li-Fi node has strong communication and networking capabilities of optical wireless physical and above TCP/IP layers, which can connect things and everything anytime and everywhere in a secure manner. Any light source anywhere can be turned into an operational Li-Fi node that can communicate with the rest of the Li-Fi communication network and Internet infrastructure. A light node can be integrated with a controller area network bus in many objects. In short, Li-Fi communication and networking technology has the true potential element for IoT and ubiquitous communications.

Li-Fi consists of an array of FSO transmitters that modulate the Li-Fi–enabled LEDs placed directly under the ceilings of offices, airport terminals, entertainment centers, healthcare hospitals and clinics, and different buildings or homes equipped with security sensors. Fig. 8.4 shows an artist's concept of configuration of the Li-Fi–enabled transmitter array and the typical coverage areas of various buildings and terminals to be connected with the IoT devices assigned in each of these buildings. Also shown in the figure are the possibilities of mobile connectivity (with smart phone or from a car) with any of these IoT devices, which also can be achieved using streetlights converted to Li-Fi–enabled LEDs. To transmit data, each FSO transmitter creates the LED light cones about one square meter directly below in which the data can be received. Digital bits 1 and 0 are transmitted by switching the LEDs on and off at the modulating rate. The LED transmitters are connected to a >100 Gb/s Ethernet network controlled by the access point. Each Li-Fi receiver is equipped with a silicon pin photodiode, which converts light intensity into electrical currents that can be interpreted as the digital bits 0 and 1. The received data is decoded to get the intended message. For data transmission and reception, the readers are referred to an earlier chapter for details.

Expanding usage of IoT technology in extensive industry and everyday life applications is developing continuously. This fuels the IoT-enabled Li-Fi technology market with a positive effect. Also, the IoT-enabled Li-Fi technology market depends on the extensive accessibility through its cloud sending.

Terrestrial node connectivity, including moving platforms and people carrying iPhones, will need optical links for high bandwidth for connecting many hundreds and thousands of devices belonging to IoT.

4.1 Introduction

In Chapter 3, we introduced the concept of the non-Stand-Alone Architecture (NSA) also called EN-DC in 3GPP architecture specifications. In this architecture the EPS feature known as Dual Connectivity is used to connect 5G DC-capable devices via the 5G NR Radio NR with EPC. In this chapter we will briefly describe EPC and outline how it can be used to in context of 5G. Further information on EPC architecture, functions, and features are available in Olsson et al. (2012). The important concept of Dual Connectivity is further described in Chapter 12.

The key baseline functions for the EPC-based system include support of multiple 3GPP RATs (i.e., GERAN, UTRAN, and E-UTRAN), support for non-3GPP accesses such as W-LAN, and support of Fixed wireline access. All integrated with functions as Mobility management, Session management, Network sharing, Control and User plane separation, Policy control and Charging, Subscription management, and Security. Over the years, EPC has grown with additional features such as Machine Type Communications and Cellular Internet of Things (MTC and CIoT), support for Proximity Services with Device to Device communication and Vehicle to Anything communications support (V2X), Dedicated Core Network selection (DECOR) and Control and User Plane Separation for the GWs (CUPS). DECOR and CUPS are two key enablers for the base core network architecture that enhances EPC for 5G based on EN-DC due to the flexibility and versatility they provide for the operators for deployment of differentiated core networks towards specific targeted users. Figs. 4.1 and 4.2 illustrate the key EPS architecture and the simplified architecture of EPC for 5G, respectively.

As the radio network increases its throughput and bandwidth capacity for 4G and enhanced 4G Radio, operators seek more flexibility and different grades of requirements from the user plane functions provided by the GWs. Basic EPC provided separation of control and user plane to some extent, in particular by separating the session management, user plane functions, and external data connectivity into separate GWs but these GWs (e.g., Serving GW and PDN GW) still hold session management control plane functions. CUPS, as further explained in Section 4.4, enables the SGW and PGW functions to be separated as control and user plane components. The CUPS work was driven by operator requirements to scale control and user plane functions independently of one another and the ability to deploy user plane functions in a flexible manner independently of control plane functions.

The result enables the separation of the SGW and PGW (as well as TDF) control and user plane functions and the flexibility to have a single control plane function to control multiple user plane functions. This ability to scale the control and user plane independently allows increased user plane capacity in the network without affecting control plane components.

DEdicated CORE networks (DECOR and enhanced DECOR), meanwhile, enables operators to partition their core networks into separate dedicated core networks with potentially dedicated MME, SGW, and PGWs used for specific purposes such as dedicated core for CIoT and MBB. Together with the Dual connectivity function in the Radio Access network (for more details, see Chapter 12), where RAN can boost the throughput of the UE by adding a secondary RAT using NR 5G Radio for the UE, an operator is able to create the early 5G system using EPC. These combined features (i.e., DC, (e)DECOR, CUPS) in EPC with NR as Secondary RAT is being hailed as EPC for 5G as illustrated in Fig. 4.2.

One key aspect for the two features in EPS (DECOR and CUPS) is that both features were developed to minimize UE impacts (or have no UE impacts) and as CUPS functions developed it did not impact existing peripheral nodes such as the MME and PCRF. We discuss the details of these two features in Sections 4.3 and 4.4, respectively. In contrast, for DC to work, it requires support from the UE to simultaneously connect to the two RATs (LTE and NR), and optionally support in MME and GWs to enable additional DC related functions—this is described in Chapter 12.

Let us consider an example deployment use case where an operator plans to deploy NB-IoT and MBB. Some MBB users have IMS services, while others are using data services with high data volume requirements. An operator may decide to separate its core network components using DECOR principles into two core networks, one for NB-IoT and one for MBB. Within the MBB part of the core network, the operator additionally decides to deploy User Plane GWs for high data volume for the MBB APN and use another set of User Plane GWs for IMS services, both being controlled by a single Control Plane function. The operator may also decide to deploy DC to boost the radio. The combination of this functionality provides an EPC for 5G enabling early NR deployment, which also continues to support all 4G EPS features without any additional impacts to existing installations.

All these features together have impacts on the core network nodes selection functions (i.e., MME, SGW, PGW) and for DC, selection of the Serving and PDN GW can be further enhanced to serve dedicated UEs with DC capability and greater need to have a GW with larger capacity and throughput to support increased data traffic. This is also known as EN-DC in the 3GPP system and is further described in Chapter 12.

Without (e)DECOR and CUPS features, an example of basic selection function or these entities is illustrated in Fig. 4.3.

As we describe later, enabling flexible selection of the user plane GWs combined with dedicated core networks within a single PLMN enables some of the key core 5G enablers such as slicing, complete User and Control Plane separation, as well as enhanced benefit from dual connectivity of different RAT types. From an operator's perspective, the combined (e)DECOR, CUPS with DC allows separating the end to end system from 4G EPS and provides their early 5G subscribers differentiated experience. With some simple use of information in the UEs, such as, knowing when DC has been activated, it is possible to display an indication in the UE when the user is in such networks. From an end user perspective, early adopters of 5G may enjoy an enhanced experience and can look forward to even better service experience with a full 5G system.

8.1 Spectrum sharing for D2D communications

Device to device communication has attained significant attention recently due to its ability to expand the local services (Koskela et al., 2010; Hakola et al., 2010; Janis et al., 2009; Zulhasnine et al., 2010; Xu et al., 2010; Chen et al., 2010; Xing and Hakola, 2010; Doppler et al., 2010; Doppler et al., 2009; Janis et al., 2009; Min et al., 2010). It is becoming progressively more and more of interest primarily because of the desire to increase the spectral efficiency, in other words to reuse frequencies within a cell that otherwise couldn’t be reused (Li and Wu, 2014). It makes primary use of distance, variations in distance dependencies, whether two people are close enough to one another so that they can actually reuse the same frequencies that could be used in a cellular manner. Various spectrum sharing schemes can be used to enhance spectral efficiency in device to device communications such as Co-primary spectrum sharing for inter-operator device to device communication (Cho et al., 2017). There are various algorithms that have been presented for device to device spectrum allocation in Cho et al. (2015), Jokinen et al. (2014). In various works power allocation is studied for the device to device communication links and the cellular links for maximizing the throughput and improving spectrum sharing (Wang et al., 2013; Feng et al., 2013). So one problem it immediately causes is that of interference, in other words the downlink or the uplink frequencies have the same problem. To avoid this interference problem various architectures, algorithms have been given (Min et al., 2011; Min et al., 2011; Yu et al., 2009). Ultimately the uplink frequencies are used for d2d because the downlink frequencies are much more congested, especially for an application like video which is very bandwidth commanding. If we use the downlink frequency the d2d receiver gets interference from the base station and the cellular transmitter gets interference from the d2d transmitter. Centralized and distributed channel allocation and power allocation schemes have been proposed to regulate the interference caused by d2d transmission to cellular users (Yin et al., 2016).

In the centralized interference coordination scheme the BS acts as a central unit and obtains the global CSI. The resource allocation in the centralized scheme is done via the convex optimization method to improve the system performance. In the decentralized scheme the system is proposed as a Stackelberg game. In this game the BS is considered as the main unit and it decides the price of per unit interference caused on each subchannel to maximize its profit. The d2d pairs compete in a non-cooperative Nash game for maximizing their individual data rates depending on the set prices by BS. Variational inequality (VI) is used as the sufficient condition for finding the Nash equilibrium (NE). Then a distributed iterative scheme is used to find the unique NE. So the distributed resource allocation scheme is completed by combining the distributed iterative scheme and the pricing mechanism at the BS. If we compare the centralized and the distributed scheme for power and resource allocation it is observed that distributed scheme is more effective (Yin et al., 2016). Several factors are responsible for this:

a.The centralized scheme is complex in comparison to the decentralized as the CSI required is much more and is difficult to obtain.

b.The centralized scheme, also requires the interference CSI within the d2d pairs and interference CSI between the CUs and the d2d receivers, which is again complex to obtain.

c.For the decentralized scheme it is not difficult to obtain the CSI between the d2d transmitter and receiver.

d.The distributed scheme protects the CUs with limited signaling overhead.

e.With the increasing number of d2d pairs in a system, the spectrum efficiency achieved for the distributed scheme is more than that obtained in the centralized.

Which software is used to manage devices to communicate with computer?

Which software is used for communication?

Which software enables the communication between the user and the computer?

What is needed for a computer to communicate?