Refined Radio Innovation Areas for IMTAdvanced within the WINNER+ Project Afif OSSEIRAN1 Mauro BOLDI2 Alexandre GOURAUD3 Jose F. MONSERRAT4, Antti TÖLLI5 Jaakko VIHRIÄLÄ 6 1 Ericsson Research, Stockholm, 16480, Sweden 2 Telecom Italia, Turin, Italy 3 Orange Labs, France 4 Universidad Politecnica de Valencia - iTEAM, Spain 5 Centre for Wireless Communications, University of Oulu, P.O.Box 4500, Oulu, Finland 6 Nokia Siemens Networks, Kaapelitie 4, Oulu, 90630, Finland Abstract: This paper summarizes the latest candidate techniques for IMT-Advanced and beyond investigated in the WINNER+ project. The presented techniques cover five innovation areas: Advanced Antenna Systems (AAS), Advanced Radio Resource Management (ARRM), Relaying, Coordinated Multipoint (CoMP) transmissions and Spectrum Technologies. In AAS, under the framework of cellular multiuser MIMO systems, the proposals focus on how to make the CSI available at the transmitter and to reduce the pilot overhead. Within the CoMP transmissions, coordinated scheduling and/or beamforming and joint processing/transmission are briefly presented and analysed. In ARRM two concepts are analyzed, namely MAC for CoMP, and Carrier Aggregation. In the spectrum technologies special attention is given to the co-existence of macro-layer and femto-layer and consequently how to coordinate or manage the interference. Finally the performances of the new techniques are briefly presented. Keywords: Advanced Antenna Schemes, Advanced RRM, Coordinated Multipoint Systems, LTE, IMT-Advanced, Network Coding, Relaying, Spectrum Technologies.

1. Introduction The race towards International Mobile Telecommunications (IMT)-Advanced is progressing rapidly. At the 3GPP, the Long Term Evolution (LTE)-Advanced Study Item was launched in May 2008 and is expected to be finalized early 2010. In IEEE 802.16 standards, IEEE 802.16m is the IMT-Advanced candidate. It is described in the System Description Document (SDD) and was already finalized in September 2009. Both LTE-A and IEEE 802.16m were submitted to ITU (International Telecommunication Union) as IMT-A technology candidates. Note that ITU for Radio (ITU-R) is expected to announce the accepted terrestrial radio interface technologies through a Circular Letter in October 2010. The CELTIC WINNER+ (Wireless World Initiative New Radio) [1] project has been contributing to the definition of IMT-Advanced technology proposals and beyond, especially the 3GPP LTE-Advanced. WINNER+ maintains the technological development path by targeting IMT-Advanced technologies, their evolutions and assessment 1 . The first year of the project saw the development of innovative techniques integrated with the overall system functionalities [2]. In the second research phase of WINNER+, we are pursuing the 1

In particular WINNER+ is one of the ITU-R Evaluation Groups for the IMT-Advanced Technology Proposals.

development of promising AAS, ARRM, CoMP and Spectrum innovations techniques that will be applied in the future IMT-Advanced standards within the scope of the LTEAdvanced development process. The main goal is to harmonize the innovations within a WINNER+ system concept where the objectives can be summarized as: • research, system integration and evaluation of innovations in areas with high potential of exploitation in IMT-Advanced; • harmonization of innovations in the pre-standardization phase; • participation in the evaluation of selected technology proposals; • strong contribution to ITU-R WP5D (i.e. working party group on IMT systems) building on active past participation; • evaluation and demonstration of selected key technologies. This article provides an overview of the latest WINNER+ techniques within the above stated innovation areas. A more details summary of each of the described area can be found in [3][4][5][6]. The remainder of this paper outlines the main techniques associated with each area.

2. Advanced Antenna Systems One of the principal radio techniques to be considered when developing future radio systems is MIMO communication, based on multiple antennas both at the transmitters (TX) and the receivers (RX). The spectral efficiency of MIMO transmission can be significantly increased if channel state information (CSI) is available at the transmitter, allowing the system to effectively adapt to the radio channel and take full advantage of the available spectrum. Providing full CSI via feedback may cause an excessive overhead, and hence quantized instantaneous and/or statistical CSI are preferable in practice. A time division duplex (TDD) system uses the same carrier frequency alternately for transmission and reception, and thus the CSI can be tracked at the transmitter during receive periods, provided that fading is sufficiently slow and the radio chains are well calibrated. This section summarizes five innovative concepts in the framework of cellular multiuser MIMO systems, where a base station employing an antenna array communicates with user terminals, each equipped with one or more antenna elements. The framework of the presented solutions consists of spatial user multiplexing or scheduling, and beamforming by means of linear transmit precoding. The problem of acquiring the CSI at the Transmitter (CSIT), which is the main focus of the proposals, consists of multiple tasks, such as pilot signal design, channel state and quality estimation, as well as feedback signal design. All these aspects are addressed in order to enhance the system performance. A more detailed description of the proposed concepts can be found in [7]. The first concept, Multi-user (MU) MIMO downlink precoding for time-variant correlated channels, presents a method for low-rank modelling of the long-term CSI, estimated over a finite time and frequency bandwidth. Compared to the conventional direct averaging, the low-rank modelling provides a more useful reference for precoding, especially when the directional components are dominating in the spatial channel. It is shown that a significant performance improvement is achieved by the new approach compared to the state of the art, especially for the case when a user has a line of sight (LOS) channel. At the same time, the method provides a smooth transition from perfect instantaneous CSIT to statistical CSIT. This method requires dedicated uplink and downlink pilots to estimate the channel between the user terminal and all BS antennas, and to perform non-codebook based precoding at BS. The second concept or technique aims at reducing the pilot overhead for MU-MIMO systems in TDD mode. In fact MU precoding requires centralized CSIT of all the terminals. In the TDD mode, CSIT is provided by means of uplink CSI pilot signals which can be

used as a reference for scheduling as well. However, antenna-specific uplink pilot streams cause an extensive overhead that restricts the size of the practical user group and the terminal antenna setup that can be handled within the same time-frequency slot. The aim is to reduce the uplink CSI overhead by letting the terminals form a reduced number of uplink pilot beams by transmit precoding instead of transmitting antenna-specific pilots. This method improves the system performance while reducing the signalling overhead. This is due to the better energy efficiency of the sounding pilot, i.e., the same power can concentrate into a fewer pilot beams. Terminal has to estimate DL channel from common pilot which should be available across the entire spectrum. Furthermore, the concept requires that the terminal is capable of transmit beamforming. The third proposal deals with predicting future channels for Adaptive MIMO transmission in time-varying channels. In fact, in a practical system, evaluation of the SINRs at the terminal will be carried out based on the channel measured at time instant while the scheduling decision will be applied at the subsequent time instants, resulting in a delay. During this time, the channel may change, so that the SINR conditions determined from the measured channel may no longer be valid. In this method, a practical channel prediction method is proposed. For channel prediction, the channels measurements gathered up to a given time instant as well as statistical information on the channel dynamics can beneficially be used. This method concerns predictive estimation of the channel and CQI in a specific setup, where a vehicular terminal has uniform linear array antenna setup, i.e. correlated antennas within half wave length distance to each other. The two remaining proposals deal how to optimize the CSI estimation performance by exploiting long-term statistics in the pilot signal design; and on how high space time code rate can be obtained by imitating network coding at the space-time encoder [7].

3. Coordinated Multi-Point Transmissions CoMP transmission and reception is one of the most promising techniques currently proposed in order to increase the data rates especially of the cell edge users. CoMP refers to a system where the transmission and/or reception at multiple, geographically separated antenna sites is dynamically coordinated in order to improve system performance. The CoMP framework encompasses all the system designs allowing tight coordination between multiple radio access points for transmission and/or reception. The coordination can either be distributed, by means of direct communication between the different sites, or by means of a central coordinating node. At a high level, downlink coordination schemes can be divided into two categories: coordinated scheduling and/or beamforming and joint processing/transmission (see Figure 3-1).

v

v

user&control data exchange

control data exchange

Figure 3-1 Coordinated scheduling/beamforming (left) and Joint Processing (right) CoMP in WINNER+.

The first category is characterized by that data to a single user equipment (UE) is instantaneously transmitted from a single transmission point, and that scheduling decisions and/or generated beams are coordinated in order to control the interference. The main advantages of these schemes is that the requirements on the coordination links and on the backhaul are significantly reduced, since typically only information on scheduling decisions and/or generated beams need to be coordinated, and user data do not need to be made available at the coordinated transmission points. The joint processing/transmission category is characterized by that data to a single UE is simultaneously transmitted from multiple transmission points, so as to coherently or noncoherently improve the received signal quality and/or cancel actively interference for other UEs. This category of schemes puts higher requirements on the coordination links and the backhaul since user data need to be made available at the multiple coordinated transmission points. The amount of data to be exchanged over the coordination links (e.g. channel knowledge and computed transmission weights) is substantial. In coordinated beamforming, the first area to be considered is transmission strategies in a Radio over Fiber (RoF) based CoMP architecture. In this study, different low-complexity transmission strategies in a distributed antenna system based CoMP scheme are evaluated. The second area in focus is coordinated beamforming where different concepts are studied. Both centralized and decentralized as well as non-codebook based and codebook based approaches are investigated [8]. One of the major drawbacks related to the implementation of joint processing as the number of users and BSs increases is the large signalling overhead required for the interbase information exchange and the amount of feedback needed from the users. Therefore, one of the main challenges is the design of efficient algorithms that could reduce the complexity requirements. To achieve this goal, the network may be divided into clusters of cells, and the joint processing schemes are implemented within the BSs included in each cluster. The achievable performance for this type of CoMP is generally better than that of coordinated scheduling/beamforming [8], but an important effort shall be dedicated to ensure that these results are obtained not at the expense of an intolerable increase in system complexity. Partial joint processing schemes are then introduced, limiting the number of nodes involved in the joint processing with still fairly good performances for each user and consequently the data exchange among the nodes as well [11]. As an example Figure 3-2 shows an estimation of the number of nodes for partial joint processing with maximum three cooperating sites varying the power threshold. 2 2.5

1.8 2.5

1.4

1.5

1.2 1

1

0.8

0.5

2

2.5 Average BSs/user

2 Average BSs/user

3

1.6

2 1.5

1.5 1

1

0.5 0.6

0 1

0.4 0.5 0.5

0

0.2

0

-0.5 [Distance/R]

-0.5 -1

-1

0 1 0.5

1

1 0

-0.5

0 [Distance/R]

[Distance/R]

0.5

0.5

0 -0.5 -1

-1

0 [Distance/R]

Figure 3-2 Average number of BSs in the partial joint processing scheme transmitting to each user versus user position in the cluster area. Threshold value 10 db (left) 20 dB (right), see [8].

4. Relaying Relays in LTE-Advanced continue to be designed, and most of the work has been focused on the backhaul link. In WINNER+ Relaying four schemes are treated and analyzed: a multiple user multiple relay (MUMR), where relays plays the role of network coding node, Two-Way Relaying with MIMO, Relaying in the framework of CoMP, and Distributed LDPC coding. In the following, we will limit the description to the first two schemes. A multiple user multiple relay (MUMR) technique is presented in [7] wherein the performance of MUMR is studied using outage probability and frame error rate as metrics. Linearly independent codes are used in each relay, which is showed to be optimal from the diversity perspective, and codes are not binary but chosen in the Galois Field GF(4) which is better at high SNR. It is expected that higher gains are achieved with a higher number of relays and users. Although the system limitations are always useful to understand how systems work, the main drawback of this scheme is its cost. In fact MUMR requires two relays instead of one as currently envisaged in LTE-Advanced. The two-way relaying scheme with MIMO proposed here [7] is based on a two steps procedure. Two nodes (UE or BS indiscriminately) wish to exchange data using an intermediate node called the relay. In the first step the two nodes send their data to the relay node on the same resources, and they interfere. In the second step, the relay sends back the data to both nodes. A key feature of this scheme is the use of amplify and forward (AF) relays which has lower costs. In order to minimize the interferences of the two streams exchanges on the same resource through the relay, a channel estimation period using pilot symbol is needed before the transmission. Although amplify and forward relays are targeted for this innovation, it is not clear how such analogue devices can memorize the signals for the assumed two step procedure and for channel estimation. Problems may arise as well if, for instance, the access scheme is not the same in uplink and downlink as it is the case now in LTE-Advanced.

5. Advanced Radio Resource Management Due to the huge complexity of the WINNER+ system, the innovative algorithms related to resource allocation are referred to as Advanced Radio Resource Management (ARRM) techniques. Four main ARRM concepts were identified [9], namely Coordinated Multipoint (CoMP) Systems, Cross-layering for QoS, Carrier Aggregation and Enhanced Single Frequency Network (SFN) Multicasting. [9] represents the main activities addressed in WINNER+. In the remaining of this section we will elaborate on the first and third ARRM innovation areas (see [9] for more details). MAC issues in Coordinated Multipoint Systems One major challenge in providing ubiquitous broadband wireless access in cellular networks is to mitigate detrimental effects of cellular interference. Coordinated Multipoint (CoMP) Systems tackle this problem by allowing for the cooperation between transmitters. Within this concept two scheduling and resource allocation techniques are considered. CoMP scheduling for interference avoidance consists of a joint per-cluster resource allocation algorithm for coordinated scheduling. The considered approach takes into account system throughput and also fairness in terms of user throughput. The main limitation of this proposal is that complete channel information at all the coordinated cells cluster is required. Finally, CoMP and self organized infrastructure-less resource assignment presents an interference aware MIMO-OFDMA concept, where BSs select the spatial precoding such that ongoing transmissions in neighbouring cells are not disturbed. The interference aware beam selection is accomplished by means of receiver feedback in which potential interferers in adjacent cells can assess the amount of interference their transmission would

cause. Apart from receiver feedback, no other inter-cell information exchange is necessary. This technique requires the existence of a frame structure where Busy-Burst is included. Carrier Aggregation Carrier aggregation implies transmitting data on multiple contiguous or non-contiguous sub-bands, called component carriers. Each component carrier occupies up to 20 MHz of bandwidth in which information towards LTE or LTE-Advanced mobiles can be transmitted. In [9] the concept of carrier aggregation has been deeply studied specifically from physical layer, MAC layer and signalling perspectives. Three are the proposed techniques: 1. Spectrum aggregation from the physical layer perspective where the viability of using LDPC codes with longer size blocks is investigated. It is shown that transport block segmentation should be avoided as much as possible. Further, the improvement achieved with LDPC is minor and in most case less than 0.5 dB. 2. Spectrum aggregation from the scheduling perspective where different aggregation strategies and related scheduling approach are compared. A significant advantage of non-contiguous carrier aggregation over contiguous aggregation has been observed, mostly due to the higher spectral diversity of the former strategy. 3. CQI signalling in Carrier Aggregation: where a method to define the CQI report granularity in the time and frequency domain is proposed.

Figure 5-1: Advanced Radio Resource Management Activities in WINNER+.

6. Spectrum Technologies Flexible spectrum use (FSU) and spectrum sharing are promising candidates for increasing spectral efficiency of a cellular network on the system level. An important technique in the area of FSU is that of femtocells. Femtocells are low-cost, low-power, short-range, plugand-play base stations, which can be used for offloading traffic from the macro cells, thus resulting in throughput gain. Femtocells offer several benefits to both consumers and operators. For consumers, they provide improved mobile coverage and QoS in small-office, home-office (SOHO) environments. No changes to their existing mobile handsets are required. For operators, in addition to offloading traffic from macro cells, femtocells offer an effective way of increasing coverage and capacity at home. Since the macro-layer and Femto-layer coexist on the same frequency at the same time, the main problem with femtocells is interference. There are two solutions to this problem: the first is coordinated femtocells, where interference is coordinated by using inter-cell interference coordination (ICIC) between femtocells and Femto- and macro-layers. The

second solution is to blindly estimate the potential interference and use resources which cause minimal interference to the macro network. This is referred to as self organization. Interference channel offers an interesting optimization problem: given a primary operator, and at least one secondary operator, how to allocate subcarriers and power to each Trasmitter-Receiver pair in such a manner that maximizes sum capacity? Game theory provides a different point of view: by anticipating what other players do, it may be possible to increase the capacity of all users [10]. In the following Flexible spectrum use with both coordinated and uncoordinated femtocells, and spectrum sharing using game theory are described. Coordinated Femtocells with ICIC One approach to control the interference in a femtocell deployment (in order to protect macro-cells) is based on explicit ICIC signalling between cells [10]. The idea is that the macro UE (MUE), when detects an interfering femtocell, sends a report to the eNB. The eNB then sends an event driven high interference indication (HII) to the femtocell(s), which stop using the resources causing interference (see [10]). Also optimized HII signalling scheme was introduced. MUEs make reference signal received power (RSRP) measurements, hereby identifying surrounding cells, and notify the detected cells to the macro eNodeB. Thereafter the macro eNodeB uses the X2 interface to signal the femtocells which physical resource blocks (PRB) are to be avoided using downlink high HHI (DLHII) messages. Consequently the X2 interface needs to be extended to the Femto-layer, and the DL-HII message format needs to be standardized. The positive aspect of this innovation is the optimization of interference signalling (HII messages on X2) leading to reductions in terms of overhead. The interference coordination between the eNB and HeNB will lead to the reduction of outage probability for the MUEs.

ort p e r   1. eNB MUE HUE HeNB 1

‐HII 2. DL Figure 6-1. ICIC signalling example.

Uncoordinated Deployments Self organization with TDD underlay [10] does not require X2 connection between macroand femtocells, or any other means to control interference. Instead, we use self organization (cognitive radio) in the femtocell to avoid femto-to-macro interference. Femto users measure the path loss from the DL of macro base stations to Femto UE’s (FUE). Results are combined at the Home eNB to create an estimate of the femto-to-macro interference. Femtocells use the uplink band of the macro cell in a TDD mode. If the estimated Femtoto-Macro interference is small (path losses are large), femtocell operation is allowed with small transmission power. The results [10] clearly confirmed that the deployment of femtocells based on self organization will lift the overall system performance. Furthermore, the results indicated that the performances are affected by the number of FUEs. Spectrum Sharing from a Game Theoretical Perspective

The problem of spectrum sharing for operators sharing the same frequency band is modelled as a strategic non-cooperative game [10]. Two types of equilibriums are compared: Nash equilibrium and Stackelberg equilibrium for primary and secondary operators. The analysis shows that the Stackelberg approach provides better performance than Nash equilibrium or the classical water-filling method. The main disadvantage of the method is that the primary operator needs to know the channels of the secondary operators in order to perform its maximization.

7. Conclusions This paper assessed the WINNER+ year two innovation areas for IMT-Advanced technologies: advanced antenna schemes (AAS), relaying systems, coordinated multipoint (CoMP) systems, advanced RRM (ARRM) and spectrum technologies. Some of the techniques within each of these areas were described briefly and analyzed. In AAS few innovations were presented. These techniques focused mainly on how to make the CSI available at the transmitter. A major drawback of these innovations is that they require dedicated uplink and/or downlink pilots. In Relaying, two schemes were treated and analyzed: a multiple user multiple relay (MUMR) where relays plays the role of network coding node, and Two-Way Relaying with MIMO. In the CoMP, joint processing schemes and coordinated beamforming schemes were identified as the two main areas. The latter schemes were more closely investigated due to their simpler and its quicker foreseen implementation. In ARRM, two ARRM concepts were analyzed: MAC aspect in CoMP Systems, and Carrier Aggregation. Finally three spectrum related technologies were summarized and analyzed: spectrum sharing using game theory; flexible spectrum use with femtocells coordinated and uncoordinated deployments. Further in both deployments performance gain were obtained.

Acknowledgements This article has been written in the framework of the CELTIC project CP5-026 WINNER+. The authors would like to acknowledge the contributions of their colleagues.

References [1] WINNER Project IST 2004-507581, WINNER II Project IST-4-027756 and WINNER+ Project CELTIC CP5-026, http://projects.celtic-initiative.org/winner+/ [2] A. Osseiran et al., “Radio Innovation Areas for IMT-Advanced & Beyond: WINNER+ System Concept”, Proc. of ICT Mobile Summit 2009, Santander, Spain, June 2009 [3] P. Komulainen et al., “CSI Acquisition Concepts for Advanced Antenna Schemes in the WINNER+ Project”, Proc. of Future Network & Mobile Summit 2010, Florence, Italy, June 2010. et al. [4] M. Boldi et al., “Coordinated Beamforming for IMT-Advanced in the Framework of WINNER+ Project”, Proc. of Future Network & Mobile Summit 2010, Florence, Italy, June 2010. [5] J. F. Monserrat et al., “Advanced Radio Resource Management for IMT-Advanced in WINNER+ (II) ”, Proc. of Future Network & Mobile Summit 2010, Florence, Italy, June 2010. [6] J. Vihriälä et al., “Spectrum Technologies for IMT-A”, Proc. of Future Network & Mobile Summit 2010, Florence, Italy, June 2010. [7] Celtic CP5-026 WINNER+, Intermediate Report on Advanced Multiple Antenna Systems, Deliverable D1.7, November 2009, http://projects.celtic-initiative.org/winner+/deliverables_winnerplus.html [8] Celtic CP5-026 WINNER+, Intermediate Report on Coordinated Multipoint and Relaying in the Framework of CoMP, Deliverable D1.8, November 2009, http://projects.celticinitiative.org/winner+/deliverables_winnerplus.html [9] Celtic CP5-026 WINNER+, Intermediate Report on System Aspect of Advanced RRM, Deliverable D1.5, November 2009, http://projects.celtic-initiative.org/winner+/deliverables_winnerplus.html. [10] Celtic CP5-026 WINNER+, Intermediate Report on Flexible Spectrum Use, Deliverable D1.6, November 2009, http://projects.celtic-initiative.org/winner+/deliverables_winnerplus.html [11] C. Botella, T. Svensson, X. Xu, H. Zhang, “On the performance of joint processing schemes over the cluster area”, in Proc. IEEE Vehicular Technology Conference, Taipei, Taiwan, May 2010.