Architectural enablers and concepts for mm-wave RAN integration

Transcription

1 Architectural enablers and concepts for mm-wave RAN integration Editor: Krystian Safjan - Nokia Bell-Labs Authors: Patrik Rugeland, Miurel Tercero Ericsson Yilin Li, Jian Luo Huawei Claudio Fiandrino, Joerg Widmer IMDEA Miltiadis Filippou, Honglei Miao Intel Krystian Safjan, Arnesh Vijay Nokia Bell-Labs Isabelle Siaud, Anne-Marie Ulmer-Moll Orange Rui Li, Mehrdad Shariat Samsung Javier Lorca, María Teresa Aparicio Telefónica I+D Date: Version: 1.0

2 Executive Summary The following white paper discusses key architectural aspects of the mm-wave RAT (Radio Access Technology) working in frequency bands from 6 GHz to 100 GHz integrated with new and other legacy technologies. Five architectural enablers were identified. The first enabler is multi-connectivity that allows the integration of mmwave technology with low-band system and contributes for the improvement both in terms of reliability and performance. Second key enabler is a new mobility state, namely RRC_INACTIVE, which helps protect system from extensive signalling related to infrequent small packet data transmissions. The third enabler is mm-wave cell clustering, rendering a solution for dealing with propagation blockages and frequent changes of the serving access point. Mm-wave cell clustering helps to perform cell switching in a rapid fashion without introducing overwhelming amount of signalling towards the core network. A fourth enabler is network slicing, which will allow multiple logical networks to share a common physical infrastructure. The last enabler is self-backhauling which, when coping with ultra-dense and cost-effective deployments, is the best transport network solution in this scenario at the moment of writing. Apart from these key enablers, we present new network functions that bring significant benefits to mm-wave system operation. These functions are: power efficiency oriented KPIs, upper layer optimizations for mobility; reference signal design to support active mode mobility in beam-based Radio Access Network (RAN); low frequency-assisted initial access beam training; user position prediction; user localization; and environment mapping to improve mobility. Table of Contents 1 Introduction Generic Architecture Vertical Multi-RAT/RAN management Architectural enablers RAN functions and network integration Conclusions Acknowledgement References Page 2 / 26

3 List of Acronyms and Abbreviations 4G AoA AP AS AWGN BRS CH CN CP CSI DC DL ECM EIRP enb EPC E- UTRAN FEC GLB gnb GPRS GPS GTP ID KPI LA LoS LT LTE MAC MBB MC MCG MCM MCS MRS NAS NG NLoS NR Fourth generation Angle of Arrival Access Point Access Stratum Additive White Gaussian Noise Beam Reference Signal Cluster Head Core Network Control Plane Channel State Information Dual connectivity Downlink EPC Connection Management Emitted Isotropic Radiated Power evolved Node-B Evolved Packet Core Evolved UTRAN Forward Error Correction Green Link Budget NR base station General Packet Radio Service Global Positioning System GPRS Tunneling Protocol Identity number Key Performance Indicator Link Adaptation Line Of Sight Luby Transform Long Term Evolution Medium Access Control Mobile Broadband Multi-Connectivity Master Cell Group Multipath Channel Margin Modulation and Coding Scheme Mobility Reference Signals Non-access stratum Next generation Non Line Of Sight New Radio PDCP PDU PE PHY PLCP PLM PSS QoE QoS RA RACH RAN RAT RF RLC RRC RRM RS RSSI SBH SCG SDN SGW SS SSS TAI TCP TM TRP TTI UDP UE UL UP UTRAN VA WLAN WT xmbb Xn Packet Data Convergence Protocol Protocol Data Unit Power Efficient Physical layer Physical Layer Convergence Procedure Path Loss Margin Primary Synchronization Signal Quality of Experience Quality of Service Random Access Random Access Procedure Radio access network Radio Access Technology Radio Frequency Radio link Control Radio resource control Radio Resource Management Reference Signal Received Signal Strength Indicator Self-backhaul Secondary Cell Group Software defined Network Serving Gateway Synchronization Signal Secondary Synchronization Signal Tracking Are Identifier Transmission Control Protocol Transmission Mode Transmission reception point Transmission Time Interval User Datagram Protocol User Equipment Uplink User Plane UMTS Terrestrial Radio Access Network Virtual Access Point Wireless Local Ara Network WLAN Termination Extreme Mobile Broadband Inter-node interface Page 3 / 26

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5 1 Introduction The expectations on performance towards future 5G systems lead to giving attention to high-frequency bands, specifically, so-called mm-waves whose frequencies are defined between 6 GHz and 100 GHz in mmmagic 1. The range of use cases envisioned for the new generation of communication system, has expanded way beyond voice and mobile broadband applications. Designing new system (or planning an evolution) comes across various levels; starting from propagation analysis through various network layers and up to end-user applications. In this document, we are pointing at envisioned mandatory architectural elements (architectural enablers) for mm-wave RATs, working in frequency bands from 6 GHz to 100 GHz and integrated with other new and legacy technologies. There have been use case families envisioned for 5G [NGMN15][Nok15], but during 3GPP standardization process the use cases belonging to extreme mobile broadband (xmbb) gained the highest prioritization (also called enhanced mobile broadband, embb in 3GPP). In xmbb use cases defined in [MMMAG15-D11], such as media on demand, cloud services, immersive early 5G experience and smart office, both high connection density and high data rates are the challenges to be addressed from the RAN architecture perspective. In this white paper we present several architectural enablers which are specific for the mm-wave RAT, and we complement them with optional technology components and RAN functions. The connection density, traffic density and data rate challenges are to a large extent handled by densification of the network, and mm-wave self-backhauling is a key enabler for cost-efficient ultra-dense deployments. Another enabler helping to cope with these challenges is low-band integration e.g. help propagate control signalling and to speed-up initial access. A high number of connections can bring challenging episodes of intense control signalling this is mitigated with new, intermediate mobility state RRC_INACTIVE. Apart from new architectural solutions developed for 5G we need to integrate mmwave system with other RATs, primarily for reliability reasons. Integration of mmwave systems with LTE using multi-connectivity gives the opportunity to provide more reliable control signalling and faster initial access in beam-based RAN. 1 Strict definition of mm-wave bands include frequencies between 30 and 300 GHz, but the industry often use a looser definition including any frequency above 10 GHz. In mmmagic project the mm-wave range is referring to even larger range of frequencies: from 6 to 100GHz Page 5 / 26

6 2 Generic Architecture Figure 2-1 Generic mm-wave system architecture diagram - RAN perspective The 5G network architecture shown in Figure 2-1, is expected to consist several RAN entities. The RAN entities will in-turn comprise existing LTE enbs (evolved NodeBs), as well as access points (APs) supporting the next generation RAT, denoted New Radio (NR), which will be capable of supporting mm-wave frequencies. The name for the NR APs has recently been coined as gnb [3GPP TR ]. A brief description of the various 5G architecture elements such as gnb, Next Generation Core network and Interfaces are described in this section. gnb The gnb is an enhanced version of the LTE Rel-13 enb, which will be capable of supporting low and high frequency bands. Whilst the full set of existing features and functions supported by this entity can be obtained from [3GPP TS ]; some of its distinguishing features are: facility to support network slicing, tight interworking with E-UTRAN, capability to support multi-connectivity, session management, and its ability to support existing and new interfaces. Additionally, it is worthwhile to mention that the gnb in 5G systems can be expected to include one or more transmission/reception points (TRPs),Some gnb functionalities can be distributed across different TRPs, while others are centralized, leaving the flexibility and scope for specific deployments to fulfil the requirements for specific use cases. Next Generation Core Network (NG-CN) The NG-CN must be capable of supporting CP signalling towards the LTE and NR APs. Here, it is important for the NG-CN to store the UE context for both the LTE and Page 6 / 26

7 NR APs. To maintain mobility between different access networks, the NG-CN will be in-charge of establishing and retaining the inter-cn signalling. It will also be in-charge of supporting mobility features like, tracking area list management, UE time zone and location mapping. UE reachability in Idle mode, QoS and session management are the other features that must be supported. Additionally, the feature of service flow management and user gateway support functionality will also be included. Interfaces With enhancements in the functional blocks, the interfaces must be capable of establishing logical connections with several APs tailored to different technological systems. From the view point of 5G access points, two main interfaces shall be introduced: NG and Xn interface. The NG interface shall be open and must support the exchange of signalling information between the 5G-RAN and NG-CN. Whilst, the Xn interface must offer logical connectivity between enb and gnb. The NG interface must be capable of supporting CP and UP separation, at the same time have separate radio network and transport layer specifications. While on the other hand, the Xn interface must support the exchange of signalling information and data forwarding between the endpoints and gnbs. Lastly, the NG interface must be capable of carrying interface management, UE connect and mobility management functions; in addition to the enhanced features to support the transportation of NAS messages, paging and PDU session management. One rule applicable to both cases, is that they must be future proof to fulfil diverse requirements, services, features, and functionality. Specifically, for the 5G mm-wave RATs both standalone and non-standalone should be supported, i.e. mm-wave RAT should be fully operational without support of other RATs (standalone deployment); however, mm-wave RAT must be benefitted from tight integration with other RATs (typically low-band systems with better coverage properties), e.g. improved initial access or improved reliability due to usage of multiconnectivity with low-band system such as LTE. 3 Vertical Multi-RAT/RAN management The management of several RATs in a heterogeneous multi-rat network involves the use of dedicated Key Performance Indicator (KPI) to switch from one technology to another one, following dedicated criteria (power efficiency, flexible QoS, multiple Access Point (AP) connection to send and receive the data) and the integration in multi-rat architectures. The generic architecture described in Section 2, encompasses gnbs as well as enbs that require multi-rat management to perform mm-wave and LTE-A carrier aggregation. The control-plane may then forward the metric decision evaluated at the PHY layers to the gnb or enb and the decision is then activated to achieve data transport between communication entities. For that purpose, dedicated link adaptation metrics in charge of air interface and transmission mode (TM) selection have to be designed, evaluated and forwarded in the multi-rat management engine followed by integration in the generic architectures detailed in this paper. Page 7 / 26

8 3.1 Multi-RAT multi-layer management The multi-rat/ran management resorts from a vertical multi-layer management of interfaces and TMs depending on involved technologies in the RATs management [SVG+16][SUMP16] and optimization criteria (power and spectral efficiency, radio coverage, etc..). It may cover three independent abstraction layers, where the activated abstraction layer depends on functional blocks that are required to change the air interface and TMs to perform the transmission between the two communication entities. Link adaptation metrics are the input of the multi-rat/ran management processing in order to choose and activate the appropriate air interface and transmission mode, depending on propagation conditions and optimization criteria. The green link budget (GLB) metric [SUM16] is the candidate link adaptation metric for power efficiency optimization in the multi-rat context where independent interfaces may be considered to carry out the transmission. The GLB metric allows a link budget based comparison between interfaces exhibiting independent power sensitivity levels and different radio frequency spectrum operations. Innovative KPIs and multi-radio interface engine as recently introduced in the ETSI Reconfigurable Radio System (ETSI RRS) technical committee, are computed at the lowest layer, typically at the PHY layer based on Received Signal Strength Indicator (RSSI) and link budget elements deduced from involved interfaces in the multi-rat process. Figure 3-1 illustrates the architecture using 5G RAT link adaptation metrics to select the most appropriate technology (technology 1, 2 or 3 following a generic approach), to establish communications between the transmitter and the receiver. Link adaptation (LA) metrics are computed using available PHY parameters as the RSSI and context information provided by Physical Layer Convergence Procedure (PLCP) headers and signalling headers of every concerned RAT. Metrics are then forwarded to the appropriate layer to initiate air interface switching. The selection is done considering equivalent throughput schemes in accordance with the transported services [SUM16]. The power efficient link adaptation metric adopted in mmmagic to optimize power and cost efficiency is described in [SUM16], exhibiting important transmit radiated power gains for mm-wave and Wi-Fi hot spot deployments [mm-magic D3.1,16]. To transport decision, the existing X2-S1 and Uu interfaces are differently exploited, depending on emulated abstraction layer activation. Page 8 / 26

9 5G RAT LA metrics, RRM and NM metrics 5G PPP mmmagic Abstraction layer-3 Abstraction layer-2 Abstraction layer-1 5G RAT LA metrics computation and feedback Figure 3-1 Generic multi-layer architecture using 5G RAT link adaptation metrics for multiple RAT management Depending on involved technologies in the multi-rat scenario, each layer is able to manage interfaces having their own capabilities to exchange context information together. The abstraction layer 1 exploits PHY and MAC protocols to exchange information and forward the radio interface engine decision. Switching from one Modulation and Coding Scheme (MCS) to another in a single RAT may be possible in this configuration. A switching between IEEE ac TMs and IEEE ad TMs may be also implemented using the fast session transfer protocol designed in the IEEE ad standard. The abstraction layer-2 requires a L2.5 layer to manage the independent interfaces that do not benefit of a common context information exchange. The I-MAC layer [KBN12] which was designed in the ICT-FP7 OMEGA project, illustrates a concrete hardware and software implementation for indoor communications. The abstraction layer-3 utilises typically the generic architecture exposed in section 2 with control and data plane architectures using S and X1 interfaces to carry out multi- RAT carrier aggregation. An illustration of multi-rat abstraction layer-3 is detailed in [SUMP16] embracing mm-wave components in innovative control and user plane splitting schemes. The adaptor represented in Figure 3-1 is similar to the WT (WLAN Termination) specified in 3GPP Release 13 for LTE/WLAN RAN-level aggregation. The same GTP-U tunnelling is then utilized for data splitting. 4 Architectural enablers 4.1 Multi-connectivity A widely acknowledged limitation of mm-wave systems is the increased path-loss associated with the higher carrier frequencies [MMMAG16-D21]. Because of this, mm- Page 9 / 26

10 wave NR cannot be relied upon to provide ubiquitous coverage from a single transmission point. Mm-wave often has to provide line-of-sight (LOS) between the access point and UE, which can frequently be prone to blocking and fast fading. However, the strict 5G requirements on e.g. throughput will necessitate the use of the wider bands available at mm-wave frequencies. To address the coverage issues, mmwave NR need to support multi-connectivity where a UE can be connected to multiple nodes at once to facilitate either aggregation of carriers for increased throughput, fast switching between nodes to enable seamless mobility, or redundant transmission schemes where the same information is sent over multiple link to increase the reliability. In LTE Rel-12 there were two options for dual connectivity (DC): 1A (MCG and SCG bearer) and 3C (MCG-split bearer). In [MMMAG16-D31] we proposed that these options should be used for mm-wave NR. In addition, we introduced an alternative, namely SCG-split bearer which allows the user plane (UP) traffic to be sent over both links (similar to MCG-split bearer), without straining the processing capacity of the master node. Figure 4-1 Multi-connectivity bearer options. The proposed dual connectivity concept is a mandatory solution for the network design, in order to provide sufficient reliability for standalone mm-wave NR and to leverage on LTE coverage for non-standalone deployments. Which of the three options to use is a matter of optimization, and recently began to be discussed in 3GPP NR Study Item and are now part of [3GPP TR ]. Another extension of the DC concept, is the possibility to add additional cell groups beyond the master cell group (MCG) and the secondary cell group (SCG), also known as a multi-connectivity (MC). The complexity of balancing the load between multiple links will increase significantly compared to DC, but there are benefits to have a preconfigured backup link with redundant coverage. This will allow a quick handover in case of radio link failure on any of the initial links and will be especially useful for standalone mm-wave NR. The proposed 5G node, known as gnb will support both distributed and centralized deployments, where multiple transmission/reception points (TRPs) contain a configurable part of the protocol stack. This can provide pooling gains with centralized functionalities, for instance mobility handling or scheduling decisions, resulting in more demanding requirements on the backhaul in terms of e.g. capacity and synchronization. The deployment of the TRPs should provide some level of redundant coverage to enable this. Page 10 / 26

11 Yet another proposal is control plane (CP) multi-connectivity, also known as RRC diversity. This was studied for LTE Rel-12 [3GPP TR ] and is considered by mmmagic, given that it will play an important role in a mm-wave system, especially for standalone mm-wave case. In LTE, the RRC signal is always transmitted directly from the master enb (MeNB) to the UE, even for signalling related to the secondary enb (SeNB). With RRC diversity, part of the RRC message, or the entire RRC message can be sent via the primary link, the secondary links, or both. This allows for improved reliability using redundant messages, or reduced latency by transmitting independent messages related to the secondary node directly from the SeNB to the UE. However, an important aspect when considering RRC diversity will be how to handle race conditions, when multiple, contradicting, RRC messages are received via different links. The RRC diversity solution can be seen as optional feature for mm-wave NR which can increase the reliability at mm-wave frequencies. Since it will be challenging to provide ubiquitous mm-wave coverage with a reasonable deployment density it will be imperative to supplement the connectivity with low frequency support. As the mm-wave NR will initially be deployed in many areas already serviced by LTE, it will be beneficial to leverage on the incumbent installations and support a gradual deployment of mm-wave NR. By harmonizing the protocol stacks of LTE and NR, it will be possible to have a tight interworking between LTE and NR which will for instance, enable aggregation of carriers or fast switching between the RATs, proposed in mmmagic [MMM16-D31]. Work has since begun in 3GPP to support the interworking between LTE (and its future releases) and NR (which will operate in both low frequencies and mm-wave frequencies) [3GPP TR ]. Initial simulation results show that by co-deploying LTE at 2.6 GHz and NR at 15 GHz in a dense urban environment with DC capabilities, it will provide synergy effects greater than the sum of the capacity of either RATs as can be seen in Figure 4-2. Figure 4-2 Downlink performance for LTE-NR interworking. A similar evaluation comparing LTE DC at 2.6 GHz with LTE-NR DC at 2.6 and 28 GHz respectively show that the mm-wave RAT improves the median throughput by up to 17 times at high loads and between 1.5 and 2 times for the 5 th percentile throughput. Page 11 / 26

12 4.2 New mobility state: RRC_INACTIVE In [MMMAGIC16-D31] it was proposed to introduce a new RRC state to complement the existing states, RRC_IDLE and RRC_CONNECTED. The new state is referred to as RRC_INACTIVE and allows a UE to benefit from several aspects of the two original states. Similar to RRC_IDLE, the UE would perform cell-reselection based on measurements of reference signals without providing the network with measurement reports. Additionally, when the network needs to reach the UE, e.g. when DL traffic has arrived, the network pages the UE which in turn performs a random access (RA) to connect to the network. Likewise, when the UE needs to initiate UL traffic, it performs a RA to the current cell to synchronize and connect to the network. What differs for RRC_INACTIVE compared to RRC_IDLE is that the UE and gnb maintains configurations obtained in RRC_CONNECTED related to e.g. AS context, security, and radio bearers so that after the RA, the UE can resume its old configurations without much delay. In addition, the gnb can maintain the CN/RAN interface (NG-C and NG- U), further reducing the resumption latency. Since the UE resumption from RRC_INACTIVE to RRC_CONNECTED assumes that the old UE context can be reused, whichever cell the UE has re-selected must be able to retrieve the context from the old cell. If the context fetch fails, the network can instruct the UE to perform a RRC Connection Setup similar to the one performed from RRC_IDLE. Figure 4-3: State transition diagram Since the RAN/CN connection can be maintained in RRC_INACTIVE; the CN will assume that the UE is in ECM_CONNECTED. Whenever the network needs to reach the UE, e.g. when there is DL data available, the network will need to page the UE, as the RRC connection is suspended. However, as the CN assumes that the UE is in connected mode, the CN cannot initiate the page, but rather the RAN will have to initiate the notification. To facilitate a more efficient paging scheme, the RAN can assign a limited area, covering one or more cells, within which the UE can be paged by the RAN. While the UE moves within this RAN area it does not need to notify the network of its location. It is only when the UE moves outside the RAN area that it will have to signal the network of its new location and be assigned a modified RAN area. As the RAN notification area can be smaller than the CN Tracking Area, the RAN Page 12 / 26

13 paging message can be sent out in a smaller number of cells than a typical CN paging. This can also be used in conjunction with the Smart Paging procedures introduced in LTE Rel-13, where the UE reports its previously visited cells and time spent in these cells. This information can be used for statistical analysis to estimate a probable location of the UE (e.g. a stationary UE could be paged in only from its previous cell). 4.3 Mm-wave cell clustering In mm-wave communication it is challenging to provide continuous connectivity for the active user in dynamic environment especially due to changing position of the UE and other objects in the scene. In case of such beam-based prone to obstruction links, it is crucial to provide mechanism that can handle switching the serving cells in quick and transparent manner to CN. The mm-wave node clustering is therefore mandatory element of the network architecture. Detailed mm-wave cell clustering description has been provided in [D.31] and previous white paper [MMMAG16-WP31]. Here, we focus on architectural enablers related to mm-wave cell clustering. The layout and architecture of the cluster will depend on the quality of backhaul and coverage of the different nodes. If the backhaul is ideal with very low latency, the cluster can be coordinated by a central node, handling all scheduling between the nodes, deployed with a non-ideal backhaul, which may preclude a central scheduler. Instead, in such cases each node is responsible for the lower layers (MAC and PHY), and can relay packets through an evolved RLC layer to other nodes when a UE needs to switch APs. In the cluster one AP with the sufficient processing power and CN connection quality to support the cluster, will coordinate the mobility within the cluster. This implies provision of CN connection to that APs that allows flexible formulation of clusters and ensuring that each mm-wave node can a part of valid cluster. To ensure connectivity within the cluster, it may be necessary to rely on the wide area coverage of low-frequency RATs, e.g. LTE-A, when the mm-wave RAT has limited reliability e.g. due to signal blockage. The lower frequency can then relay traffic and control signals from the CH to the UE, and assist in intra-cluster mobility. This makes strong connection between inter-frequency multi-connectivity and mm-wave clustering. Additionally, the mm-wave access clustering is expected to work even with wireless self-backhauling, where the nodes may relay traffic using the mm-wave air interface. However, this may introduce additional latencies in the system which needs to be considered. 4.4 Network slicing Network slicing will be an important aspect of 5G networks, where multiple services and business operations can be realized independently on a shared infrastructure (including shared processing, storage, transport, radio spectrum, and hardware platforms). This will allow for a more cost- and energy-efficient asset utilization where the logical separation allows for a flexible and independent configuration and Page 13 / 26

14 management of slices without compromising stability and security. However, it is important that the configuration and maintenance of the slices add a minimum overhead as not to waste scarce RAN resources. It should be possible for an operator to configure a specific slice with a customized logical network optimized for a specific use case while still not preventing the operation of other slices. Even though a slice may be optimized for a single use case, the notion of network slicing should not be confused with the concept of different services. It is possible that a single slice supports multiple services with e.g. differing numerologies or KPIs, and it is likely that multiple slices on the same network provide the same service, e.g. multiple operator offer mobile broadband (MBB) services with independent logical networks on the same physical infrastructure. Since different network slices are to be operated as independent networks, it is important to ensure slice protection to prevent shortage of shared resources, (e.g. common signalling resources). This could be achieved using slice specific access class barring where the network configures UEs already associated to a specific slice with e.g. modified back-off timers. To facilitate an optimized slice selection, a UE can provide the network with a configured slice ID, which is obtained after its initial attach. On the absence of a valid slice ID, the UE should access using default configurations and the network will configure and redirect the UE to a proper slice. 4.5 Self-backhauling The new level of densification in 5G will require innovative approaches in radio resource, mobility, and/or interference management. A centralized operation of mobile networks, as implemented by C-RAN, allows for obtaining a globalized view on mobility and interference management in order to optimize the resource usage [BDO+13]. Aiming at centralization of the mobile network operation; high capacity links among access points of small cells and the centralized base station of macro cell are required, which is usually satisfied by optical fibre connections. Nevertheless, it may be too expensive or impractical to equip every cell with fibre connectivity. As an attractive, cost efficient alternative, wireless backhauling enables direct, low latency connections amongst access points and base stations and, hence provide them with a possibility for enhanced cooperation to achieve better performance, in addition to providing high data rate throughput to small cells. A further step of wireless backhauling is self-backhauling, which refers to a set of solutions to provide technology- and topology-dependent coverage extension and capacity expansion utilizing same frequency band for both backhaul and access links, as shown in Figure 4-4. Self-backhauling provides an efficient way to combat infrastructure constraints especially in dense network deployment, where access to fibre may be limited to only some APs. However, over time as the fixed infrastructure will become more available, the self-backhauling will gradually evolve. Page 14 / 26

15 Core Network Self-Backhauled Node Node with dedicated backhaul Figure 4-4 Concept of self-backhauling. The dynamics and self-autonomy of self-backhauling solutions can gradually evolve into Software Defined Networking (SDN)-based solutions, where one logical controller is supposed to monitor topology changes, node-to-node radio channel status and all the traffic needs in a real-time manner. In this case, backhaul networking for densely deployed small cells could be characterized by a ringed-tree topology with multiple backhaul links per node and different levels of backhaul links [SGV+16]. An example of a ringed-tree backhaul networking is illustrated in Figure 4-5. Figure 4-5 An example of ringed-tree self-backhauling. As shown in the Figure 4-5, a network node can have more than one backhaul link, and vertical links would have higher priorities in route selections than horizontal ones. Focusing on this backhaul networking, a high-level radio resource management procedure is considered as follows 1. Start-up configuration: Each network node decides if its backhaul links should be always-active or improvised, e.g., for high-level vertical backhaul links, they may be always-active, where other candidate backhaul links are improvised to reduce the signaling overhead of all on the scenario. Furthermore, radio measurement procedure and reference signal sounding are configured, and maximum number of simultaneous backhaul links (dependent on RF chains) for a specific node are specified. 2. AP side configuration: channel measurement for each possible backhaul link, and reporting the channel state information to the controller. Reporting bandwidth demands for access and backhaul respectively are also included. Page 15 / 26

16 BER Propagation Loss (db) 5G PPP mmmagic 3. Controller side procedure: end-to-end routing procedure to form backhaul networking for a cluster of nodes, plus routing policy broadcasting and radio resource allocation. 5 RAN functions and network integration 5.1 RAN functions Power efficiency oriented KPIs A power efficient link adaptation metric has been designed [SUM16] to perform dynamic multi-rat management under power and cost efficiency criteria guaranteeing QoS and radio coverage. This metric, denoted Green Link Budget (GLB) metric, carries out a selection of the most power efficient transmission mode and air interface by computing two normalized sub-metrics, the and sub-metric. The - metric covers extra power requirements to guarantee QoS on a given transmission mode when passing from AWGN to multi-path propagation conditions i.e. the Multipath Channel Margin, (MCM) and the extra required radiated power i.e. the Path- Loss Margin (PLM)), which is necessary to have a received power level equivalent to a free space path-loss situation. The selected TMs are associated with the minimum sub-metric values of concerned interfaces. The -metric computes the difference between the received power and the required power for the transmission mode initially selected by the -metric. A power control is then done by the use of numerical -metric value to adjust and limit the Emitted Isotropic Radiated Power (EIRP) at the AP or the gnb in small or macro-cell deployment. α = MCM + PLM 1E+0 85 Multipath path-loss 1E-1 1E-2 1E-3 Multipath Channel 80 PLM 1E E-5 1E-6 AWGN MCM SNR Free space path-loss distance d (m) Figure 5-1 Multipath Channel Margin (left) and Path Loss Margin (PLM) metrics visual interpretation Figure 5-1 gives the definition of the -metric. MCM is derived from link level performance in a multipath versus AWGN case for a given TM and technology Page 16 / 26

17 delivering the desired throughput to transmit data with a QoS translated in a Bit Error Rate target. PLM is the variation of measured RSSI and an idealistic RSSI linked to free space path-loss without any obstacles. The GLB metric has been applied upon the mm-magic multi-band system integration model in which each interface is enabling to operate upon several RF bands [MMMAG17-D13]. The GLB metric is then in charge of selecting the most power efficient RF band in connection with the environment to establish radio communication and available technologies in the multi-rat scenario. Another application is the access point selection to perform communications in multi-rat handover scenarios. The metric has been also integrated in radio engineering tools in order to optimize inter-cell distance for 5G multi-rat/ran deployment [UMS15] [MMMAG17-D13] Transport layer optimization to improve mobility mm-wave signals are more outage-prone compared to low-frequency carriers; blockage can be induced by trees, street furniture, transport traffic and even human body. Signal blockage (in either control or data channel) may lead to an abrupt reduction in link quality or to Radio Link Failures (RLFs) with drastic impacts on transport layer control protocols (e.g., TCP) resulting in degraded quality of experience (QoE) for end-users. In the context of mm-wave RAN, signal outages or RLFs are not only triggered in cell boundaries in case of high mobility, but also in any locations within the coverage area of a mm-wave AP as soon as the strong LOS or reflection channel component is blocked by dynamics of environment (even if the UE is stationary). One way to remedy the QoE from user perspective is to apply efficient forward error correction (FEC) schemes, known as Fountain codes to counterbalance the outage impacts. Fountain codes have been designed for lossy and varying channels with erasures. Luby transform codes (LT codes) are the first class of universal erasure codes out of them [MLU02]. The source for fountain codes will encode a file into streams of packets, each containing random parts of the original file. The fountain source keeps sending these encoded packets to the destination, without knowing which packets will be received. At the receiver s side, when the number of packets received is slightly higher than the original file size, the source file can be recovered. Combining such FEC schemes at application level, facilitates utilising simpler transport protocols (e.g. UDP) without congestion management or error check / control at transport layer. This in-turn can additionally improve user QoE by avoiding unintended cross-layer interactions when facing abrupt link quality changes (particularly, in mm-wave bands) as outlined. Figure 5-2 Sequence number per file received over time for TCP (left) vs. LT (right) Page 17 / 26

18 Our simulation analysis in equivalent settings suggests that LT codes can achieve complete and reliable file transmissions over UDP with lower levels of overhead (i.e. better throughput) in mm-wave bands (as shown in the figure above- right hand side). The red line depicts completion of each file (52 MB) in sequence. Furthermore, analysis also shows that in outage regime (of mm-wave bands) application on top of TCP barely receives all the packets transmitted out of each file as a large number of them are lost during the outages (as in the figure above- left hand side). On the contrary, LT (over UDP) provides complete file deliveries thanks to forward error correction mechanism, resulting in more consistent QoE Reference signal design to allow active mode mobility in a beam based RAN As the mm-wave access will need to rely on beam-formed connectivity to provide connectivity, coverage, and capacity to the UEs due to the increased path loss at higher frequencies, the mobility procedures need to be adapted to cope with this. In LTE, the mobility related measurements were based on periodic reference signals, transmitted omni-directionally by cells. If a UE was in RRC_IDLE state, it would select the best cell to camp on and if the UE were in RRC_CONNECTED, then the UE would send a measurement report to the network, if the signals surpassed certain network configured threshold, and the network would select the target cell for handover. For NR, it has been agreed that there will be two levels of mobility, with and without RRC involvement. Mobility without RRC involvement will be limited to scenarios where the mobility is between transmission/reception points (TRPs) belonging to the same gnb, where tight synchronization can be assumed. In these cases, beam management procedures, similar to intra-gnb procedures utilizing channel state information reference signals (CSI-RS) will suffice. To cater to the wide range of mobility requirement of the 5G use cases, the network will be able to configure the periodicity of the CSI-RS from a few milliseconds up to several seconds, or turn off completely, if there are no UEs active in the cell. However, as tight synchronization between nodes cannot be assumed to be ubiquitous, an asynchronous mobility procedure is needed which is provided by the RRC based mobility. These mobility reference signals (MRS) will need to contain a synchronization signal (SS) as well as a beam identifier (BRS (beam reference signal)) for the UE to be able to distinguish beams with different synchronization (e.g. from different nodes). The active mode mobility in NR requires frequent transmissions of reference signals in narrow beams to ensure prompt switching in case of poor coverage. However, if these reference signals were provided in every beam with the strictest periodicity required, the overhead and added interference would be prohibitive, not to mention the wasted energy in transmitting superfluous signals not used by the UE. Thus, unlike LTE, there is a need to distinguish between idle mode and active mode mobility. The requirement for the idle mode mobility is to provide means for accessing the network, which is much more latency tolerant than the active mode mobility where e.g. using a periodicity of 100 ms would be acceptable compared to 5-10 ms for high speed user during active mode mobility. Page 18 / 26

19 5.1.4 Low frequency assisted initial access beam training The initial access process comprises the three tasks of downlink timing and frequency synchronization, system information acquisition and uplink timing synchronization. During initial access a UE has to establish a RRC connection with the corresponding mm-wave AP. The performance of this procedure directly impacts the user experience. Therefore, on PHY layer a beam alignment must be achieved within short time. Exploitation of the limited a-priori information on the preferred transmission direction at both ends of the link will support this. In a non-standalone deployment, i.e., a heterogeneous network, where mm-wave small cells are located within the coverage area of a macro cell operating at low frequency, low frequency RAT assistance can improve initial access performance significantly. Especially UE power consumption and latency can be reduced. In the following, the three mentioned tasks of low frequency RAT assistance are highlighted Downlink synchronization For downlink synchronization the UE exploits synchronization signals transmitted by the AP. These are in particular time-frequency resources with a certain periodicity, which allow acquisition of symbol, slot and sub-frame timing. After achieving that, the UE is able to obtain the cell ID. If the UE is located in a low frequency RAT coverage area, the low frequency RAT can transmit information about frequency and cell IDs of mm-wave small cells within its coverage area. With this signalling, the UE does not need to perform an exhaustive search over the whole small cell ID space, but it only tries to detect the signalled cell IDs. As a consequence, the UE power consumption for downlink synchronization is significantly reduced System information transmission The second task of the initial access procedure is to acquire the system information which provides all the essential information for accessing the network to the UE. The coverage of the system information determines the coverage of the cell. Some of the system information components, e.g. the system frame number, are changing fast on the basis of one or several mm-wave RAT frames. Other system information components vary relatively slowly, so information about system bandwidth, random access resources, paging resources and scheduling of other system information components is typically semi-static. For this reason, it can be energy efficient to convey some of the slowly varying system information by exploiting the existing low frequency RAT. The fast changing system information components, however, need to be transmitted by the mm-wave RAT Uplink synchronization It is important that efficient uplink (UL) data transmission in the mm-wave RAT is supported as well, especially for UL data traffic dominant use cases, e.g., uploading content, such as high-resolution videos to social media during sports events, concerts etc. UL synchronization needs to be achieved prior to any UL packet transmission to ensure that all the co-scheduled UEs UL signals are time-aligned at the enb. A RACH Page 19 / 26

20 procedure, similar to that standardized in LTE can be used. Based on the RACH preamble transmitted by the UE, the enb can determine the timing advance value for the UE. The radio resources for the preamble transmission are typically part of the system information and such system information can be signalled by the low frequency RAT. This can be viewed as a basic assistance to the UL synchronization. To ensure a certain UL preamble coverage, if several preamble formats are supported by the system, the low frequency RAT can signal a particular preamble format to the UE in order to realize the network assisted preamble format selection. In case of contention free RACH, the low frequency RAT can signal the exact preamble sequence to be used by the UE. During the LTE-like RACH procedure, the RACH response signal can be also transmitted by the low frequency RAT. In addition to the above mentioned options for UL synchronization assistance, the low frequency RAT may also offer assistance to the possible beam alignment operations during the initial UL synchronization procedure User movement prediction Good propagation conditions and beam steering are necessary to achieve high data rates. In order to achieve this, accurate position estimation and position tracking is needed, especially for dense urban and high mobility scenarios. This poses a number of challenges related to the capability of accurately estimating the position and following the movement of the users, in order to maintain a stable mm-wave connection. Also, the beam-training overhead per user is independent of the one related to other users and depends only on the user s mobility. As the number of users increases, so does the beam training overhead. In high density mobile scenarios, this overhead may become prohibitively large, unless more intelligent beam-training strategies are used. From this perspective, mobility and user density are equivalent issues to be tackled by beam training and tracking algorithms, and special care is required when highly mobile users associate to APs that already serve a large number of mm-wave terminals. In particular, these scenarios yield three related issues: first, beam training procedures upon AP association can be too slow and result in suboptimal beam pattern choices, which in turn would lead to unstable channel and data rates; second, the changes of the optimal beam pattern induced by the movement of the users must be tracked in order to consistently maintain a sufficiently high link rate; third, links can be easily broken due to the users moving behind an obstacle or some blocking material, such as a building, vegetation, vehicles, or other users. In these cases, agile, possibly proactive AP re-association mechanisms should be provided, in order to avoid that a user loses connectivity over long time periods, and a complete beam training procedure needs to be re-initiated from scratch. Embedding history information about the users movement patterns into the beam training and tracking process at mm-wave AP can considerably improve the performance of mm-wave links and relieve part of the time burden caused by beam training procedures [PDW17]. The prediction of the movement of the users can be fully estimated at the AP side, without requiring any explicit feedback of position information from the users to the AP. This yields the two-fold advantage that it incurs no overhead, and that no interface is required between mm-wave communication systems and other positioning subsystems embedded in user terminals or vehicles, Page 20 / 26

21 such as Global Positioning System (GPS) receivers. In fact, no precise location information is required from external sources: the same can be reliably estimated by APs, using only some information from current beam pattern choices that would help drive future beam tracking procedures User localization and environment mapping to improve mobility mm-wave technology will play an essential role in indoor localization and mobility because of its unique characteristics. Propagation occurs in quasi-optical patterns, whereby reflections off the boundaries of indoor surfaces and obstacles are subject to limited scattering and the line-of-sight (LoS) component tends to be predominant over non-los (NLoS) components even in the presence of obstacles. Mm-wave signals are characterized by short wavelength and large bandwidth, thus even directional transmission may generate multiple reflected paths reaching the moving receiver with different delays and angles of arrival (AoAs). The information extracted by the phased antenna arrays typically used for mm-wave devices fits well with the purpose of localization. In a generic environment where different mm-wave APs are present, the signals transmitted by each AP typically reach a node via both LoS and NLoS paths. The antenna array of the node can be used to estimate the AoA of each multipath arrival from each AP, thereby providing a so-called AoA spectrum for each AP that illuminates the node. The AoA spectrum information can be directly passed on by a node s receiving hardware, or can be derived by processing beam tracking information (i.e., the sector ID of the phased antenna array). The latter can be forwarded by MAC protocols such as ad, which are aware of the sector ID. The algorithm estimates the location a mobile user in an indoor space working without any a priori knowledge about the surrounding and the location and number of access points available [PCW17]. Once the user location and the anchors have been estimated with sufficient accuracy, it is possible to reconstruct the shape of environment determining the location of reflective surfaces and walls. The intuition is as follows : the geometric relationship between physical APs and virtual APs (VAs) permits to estimate the location of the point on the wall where the signal of the physical AP reflects. The accuracy of the estimation is enhanced taking into account different user locations to see the reflection point on the wall from different angles. Accurate localization and tracking can also serve as a proxy for physical communication functions, such as beamforming, handovers and context switching. In Section 3.4 baseline architecture for the mm-wave AP clustering was described, in this section we extend it to support localization function. To optimize the cluster management, it could be beneficial to consider the extent of UE mobility and implement location information and heuristics to predict when and where a UE should perform handover; considering link quality and the overhead associated with the handover. Additionally, as the mm-wave RAT will be heavily reliant on beam-based transmission, the beam training and beam width adaptation strategies need to be evaluated to optimize the handover procedure for various mobility scenarios. As some of the APs within a cluster may be serving multiple UEs using overlapping beams will Page 21 / 26