Device-to-Device Discovery Based on 3GPP System ... - IEEE Xplore

Globecom 2013 Workshop - International Workshop on Device-to-Device (D2D) Communication With and Without Infrastructure

Device-to-Device Discovery Based on 3GPP System Level Simulations Meryem Simsek† , Arvind Merwaday†, Neiyer Correal‡ , and ˙Ismail G¨uvenc¸† Department of Electrical & Computer Engineering, Florida International University† Motorola Solutions, Inc., 8000 W. Sunrise Blvd., Plantation, FL‡ Email: [email protected], [email protected], [email protected]‡, and [email protected]

Abstract—Device-to-device (D2D) communication as an underlay to cellular networks has gained increasing popularity as a technology component to LTE-Advanced. Through D2D communications, user equipments (UEs) in close proximity to each other, may communicate directly instead of through the eNodeB. This helps to achieve better performance than that offered via eNodeB (two-hops) by offloading eNodeB resources, and enables new types of services. This paper provides an overview of the new agreements in 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) Radio Access Networks (RAN) related to evaluation methodology and channel modeling for D2D discovery and communications. We also present a system level simulation environment based on 3GPP assumptions and a performance evaluation of three different D2D discovery algorithms. Index Terms—Public Safety Communications, ProSe., D2D Discovery, System Level Simulations

I. I NTRODUCTION Device-to-device (D2D) communications is viewed as a key technology for providing seamless, high quality, robust data transfer in next generation wireless systems. Through D2D communications, wireless devices can communicate with one another via direct D2D links over both licensed and unlicensed spectrum. As opposed to traditional short-range D2D technologies such as Bluetooth and Zigbee, D2D communications in cellular networks is expected to provide high capacity, guaranteed quality of service (QoS) over long ranges, and new proximity-based services. D2D communications is particularly critical for scenarios with little or no infrastructure support such as emergency response and disaster relief operation [1]. Due to its promise in proximity services (ProSe) and public safety communications, and the emerging social-technologial trends, in December 2012, a study item was created in the 3rd generation partnership project (3GPP) radio access network (RAN) standardization group to study long term evolution (LTE) D2D communications [2], [3]. Hereby, ProSe consists of D2D discovery and D2D communication of devices in close physical proximity. The objective of this study item is to examine the feasibility of LTE D2D communications for both public safety and non public safety applications, considering both in-network and out-of-network coverage scenarios. Since D2D communication channels have different characteristics compared to cellular communication channels, a major goal of this study is to define channel models and evaluation methodologies for D2D scenarios. Subsequently, the study aims to identify physical layer options to enable energy 978-1-4799-2851-4/13/$31.00 ©2013IEEE

efficient D2D discovery and communication techniques and protocols. Comparisons with the existing D2D mechanisms (e.g., Bluetooth and WiFi Direct) are also targeted, for example in terms of energy efficiency and signaling overhead. Single and multi-operator scenarios (e.g., a carrier shared by multiple operators) and frequency (FDD) vs. time division duplexing (TDD) operations are some of the other items within the scope of the study item. The main goal of the present paper is to provide an introduction to the LTE ProSe channel modeling and evaluation methodology framework/assumptions recently developed in the 3GPP RAN standardization and to evaluate three D2D discovery algorithms based on these assumptions. In particular, path loss, shadow fading, and small scale (e.g., power delay profile (PDP), angle of arrival/departure spreads, K-factor, and Doppler spread) channel characteristics agreed upon in 3GPP for the simulation of ProSe will be reviewed. Evaluation metrics that compare the performance of different D2D discovery and communication proposals will also be described. In order to initiate any D2D communications and to enable proximity-based services, D2D neighbor discovery carries critical importance [4]–[6]. After covering the D2D channel modeling assumptions and evaluation methodology in 3GPP, the paper will review basic D2D discovery techniques and associated trade-offs. Finally, some preliminary D2D discovery performance results using a 3GPP-compliant system-level D2D simulator will be presented, along with a discussion of assiciated tradeoffs. II. D2D E VALUATION M ETHODOLOGY AND C HANNEL M ODELS IN 3GPP In this section, we summarize simulation layout options, use cases, evaluation scenarios, channel models, power consumption model, discovery procedures, and signal transmission timing agreed in 3GPP for studying D2D discovery and communications. These agreements may also be found in the meeting reports from April 2013 [7] and May 2013 [8] 3GPP RAN1 meetings. A. Simulation Layout Options & User Equipment (UE) Drops The following simulation layout options are agreed in 3GPP RAN1 for simulating D2D scenarios [9]: • Option 1: Urban macro (500 m inter-site distance (ISD)) + 1 remote radio head (RRH)/Indoor hotzone per cell

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Option 2: Urban macro (500 m ISD) + 1 Dual stripe building per cell • Option 3: Urban macro (500 m ISD) – all UEs outdoor • Option 4: Urban macro (500 m ISD) + 3 RRH/Indoor Hotzone per cell • Option 5: Urban macro (1732 m ISD) • Option 6: Urban micro (100 m ISD) All layout options consider a hexagonal grid, 3 sectors per site, with 19 or 7 macrocell sites. The total number of active UEs per (active) cell are specified as 25 for options 1, 2, 4, and as 10 for options 3, 5, 6. UE Dropping: The UE dropping for public safety and non public safety scenarios are performed differently. • Public safety scenarios: Layout option 5 is selected as mandatory, while option 3 and option 1 are specified as optional layouts in decreasing order of priority. • General scenarios: Layout option 1 is selected as mandatory, while option 2, option 3, option 4, and option 6 are specified as optional layouts with decreasing priority. For simulation layout options 1, 2, and 4, two-third of the UEs are uniformly randomly dropped within the clusters of small cell(s), while one-third of the UEs are uniformly randomly dropped throughout the macro geographical area, with 20% of the UEs being outdoors and 80% of the UEs being indoors. On the other hand, for layout options 3, 5 and 6 UEs are dropped in two different ways: • Uniform drop: All UEs are uniformly randomly dropped throughout the macro geographical area • Hotspot drop: Within each macrocell area, a hot spot circular region with a radius of 40 m is generated with randomly distributed locations. Two-third of the UEs are uniformly randomly dropped within this hotspot area, while the remaining one-third of the UEs are uniformly randomly dropped outside of the hotspot area within the macrocell. For UE-to-UE associations with unicast, groupcast, broadcast, and relay communications, a random pairing of the UEs is considered [9]. Minimum association Reference Signal Received Power (RSRP) for D2D communications is set to −114 dBm. The total number of active UEs (with wide area network (WAN) traffic) per cell area is assumed to be 25 for layout option 1, and 10 for layout option 5. For D2D discovery purposes, the total number of UEs (including active UEs) are taken as 150 for both option 1 and option 5 [8].

•

•

• •

Subscribers from Different Public Land Mobile Networks (PLMNs): Discovery between UEs camped on different PLMNs. Roaming between Different PLMNs: Discovery between UEs in different PLMNs under roaming conditions. Network ProSe Discovery: The ProSe discovery service is provided by the 3GPP network for ProSe-enabled UEs.

C. Evaluation Metrics

B. Use Case Scenarios

Different metrics are agreed upon to evaluate the performance of D2D discovery and D2D communication techniques. For D2D discovery, the following metrics are considered [7]: • Performance target – Open discovery: Number of UEs discovered as a function of time (system-level) and the cumulative distribution function (CDF) of number of UEs discovered as a function of time (system-level). – Closed discovery (i.e. knowing the UEs to be discovered): Discovery probability as a function of time. • Range and reliability: Probability of discovery vs pathloss (link and system level) and the probability of false alarm (link and system level). • Impact on Wide Area Network (WAN): Amount of resources used (system-level). Throughput loss and interference metrics are further work. • Power consumption: Modeled through ON time or equivalent power consumed (transmit/receive powers to be captured differently, which is for further study). For discovery purposes, the same metrics are used for innetwork, partial network, out of network, and (non-) public safety cases, with possible differences in emphasis. For D2D communications the following evaluation metrics are defined: • D2D throughput and spectral efficiency: User throughput (mean, 5%, CDF) for full buffer (system-level), perceived (application-to-application) user throughput (mean, 5%, CDF) for FTP (system-level), and the VoIP system capacity (system-level). • Range and reliability: Performance vs pathloss or distance (link and system level; only full buffer used for link-level). • Call setup latency: Physical layer latency for call setup for out of coverage only (link and system level). • Impact on WAN: Change in cell throughput/cell spectral efficiency (system-level) and CDFs of perceived per-user throughput for FTP with and without D2D. • Power consumption: See Section II-F. D. Channel Propagation Modeling

Use case scenarios of D2D in 3GPP are agreed upon as follows [10]: • Restricted ProSe discovery: A basic ProSe discovery scenario, that requires explicit permission by the UE being discovered. • Open ProSe discovery: The UEs can discover other discoverable UEs without any specific permission from other discoverable UEs.

The UE-to-UE channel propagation properties for D2D scenarios are different from the typical cellular propagation channels between the eNB and the UEs, primarily due to 1) low antenna heights at both UEs, 2) UE density and proximity, and 3) mobility of both UEs. Considering these factors, new path-loss, shadowing, and fast fading models have been specified to simulate D2D scenarios for outdoor-to-outdoor (O2O), outdoor-to-indoor (O2I), and indoor-to-indoor (I2I) links [8],

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Outdoor to outdoor ITU-1411-6 or Winner+ B1

Path loss LOS probability

ITU-R IMT Umi

Outdoor to indoor Dual strip, or Winner+ B4, or Winner II A2 ITU-R IMT Umi

Shadowing 7 dB lognormal, or 10 dB lognormal

7 dB log-normal

Fast fading

ITU-R IMT UMi O2I

ITU-R IMT UMi LOS and NLOS

Indoor to indoor

Table I: Channel model assumptions for simulating D2D scenarios.

as summarized in Table I. For the 700 MHz channels (used for public safety scenarios), a 20 log(fc ) correction factor can be applied to the path loss values obtained for 2 GHz central frequency (unless otherwise specified). UE speed for channel modeling purposes is considered to be 60 km/hour (outdoor UEs in option 5) and 3 km/hour (all other cases). Shadowing correlation is left for further study [8]. E. Assumptions on Duplexing, Bandwidth, and Partial Network Coverage An important agreement in [8] is that D2D will operate in the uplink spectrum in case of FDD, or uplink subframes of the cell in case of TDD1 , except when the UE is out of coverage. Moreover, D2D transmission/reception on a particular carrier is assumed not to use full duplex (FD), i.e. it is assumed UEs are half duplex (HD). This means that while a UE is transmitting a discovery signal in a subframe, it will miss any discovery signal transmitted by any other UE in the same subrame. The following additional agreements were reached for evaluation of partial network coverage scenarios [8], [11]. • System bandwidth: – In-coverage and partial coverage scenarios: 10 MHz (FDD), 20 MHz (TDD). – Dedicated spectrum for out-of-coverage scenarios: 10 MHz. • Network operation for partial network coverage: 80% of the eNBs are disabled in a clustered pattern (3-site clustered eNB enabling pattern for 19 cells layout). • Out-of-coverage criterion: -6 dB average SINR. • Wraparound: Wraparound is used for all other cases, except for partial network coverage scenarios. F. Power Consumption Modeling Power consumption modeling for both in-coverage and out of coverage scenarios was agreed upon in [8] as follows: • Sleep power = 0.01 units per sub-frame • Receive power = 1 unit per sub-frame (8 subframes are assumed to be accumulated for synchronization with WAN, with synchronization being reliable for 0.5s) 1 Use

of downlink subframes in case of TDD is further work.

Transmit power – 20 units per sub-frame (for 31 dBm) – 1 unit per sub-frame (for 0 dBm and below) – Linearly scaled between 1 unit per sub-frame and 20 units per subframe for transmit power between 1 mW and 103.1 mW. • Global positioning system (GPS) power = 0.08 units per sub-frame (average power consumption for GPS, which is assumed to be always ’on’ independently of other communications) • D2D discovery, D2D communication, WAN signaling for D2D and non-D2D-related WAN signaling will all use same values as above. The number of subframes assumed for each type of power usage is further work. • Paging cycle is assumed to be 1.28 seconds. G. Discovery Procedure •

Dual strip, or InH (TR 36.814), or Winner II A1. ITU-R IMT UMi, or ITU-R IMT InH, or Winner II A1 LOS: 3 dB lognormal, or NLOS: 4 dB log-normal ITU-R IMT InH LOS and NLOS

The following two types of discovery procedures are initially defined to facilitate further discussions [8]: 1) discovery resources are allocated on a non-UE specific basis (for all users, or a subset of users), and 2) discovery resources are allocated on a per-UE specific basis. How the discovery resources are allocated and by which entity are an implementation issue and not restricted by these definitions. H. D2D Signal Transmission Timing To determine the signal transmission timing, cases with and without a synchronization reference are considered [12]. When there is a synchronization reference, a UE is assumed to begin transmission at a time instant T1 −T2 , where T1 is the reception time of the synchronization signal, and T2 is an offset time, which can be positive, negative or zero. The synchronization reference can be obtained from the downlink transmission of an eNB (when the UE is within network coverage), from single or multiple other UEs, or from an external source (e.g., global navigation satellite system (GNSS)). III. D2D A LGORITHMS To characterize the device discovery performance in 3GPP based D2D scenarios, we compare three different methods. The discovery slots consist of a total of NF × NT discovery resources (DRs) multiplexed in both frequency and time domains. NF represents the number of available DRs in the frequency domain and NT is the number of discovery subframes. The total system bandwidth of NRG resource groups (RGs) is divided into subbands each covering 180 kHz. We consider D devices which select a DR to periodically transmit their peer discovery information. Each DR is identified by a PDRID (Peer Discovery Resource ID). Each device transmits its peer discovery information on one DR and listens to the remaining DRs to discover its peers. Fig. 1 depicts the device discovery timing structure for a subframe duration of NFrame . In the following we discuss three different D2D discovery approaches: • Random PDRID selection: In the random PDRID selection method, all devices in the system select their PDRID for transmission randomly over the NF × NT DRs.

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NFrame

800

Data

600 Discovery

Data

Data Discovery Resource (DR) ͘͘͘

NRG

400 distance [m]

Control

1

−400

͘͘͘

−600 NF

͘͘͘ 1

2

0

−200

2

͘͘͘

200

−800

NT

hotspot

−1000

Figure 1: Device discovery timing structure.

−1000

−500 0 distance [m]

500

Figure 2: Layout option 5 for hotspot UE distribution. •

•

Greedy PDRID selection: The greedy PDRID method, based on received signal power measurement over all DRs, is aligned to the FlashLinQ protocol discussed in [5]. In this method, the first NF ×NT devices select the DRs based on their order, so that each DR is selected by one device. The remaining devices measure the received signal powers over all DRs and select the DR with the minimum measured received power for transmitting its own discovery signal. Coordinated PDRID selection: In the coordinated PDRID selection method, the eNodeB assigns the DR to each device for transmission based on a brute force search. It is assumed that the eNodeB knows the positions of each device (see e.g. estimated cell ID positioning [13]), so that the estimated received power prx (m, k) from each device m to each device k is calculated according to: ptx , (1) prx (m, k) = d(m, k)α where d(m, k) is the distance from device m to device k and α = 4 is the estimated pathloss exponent. We define for each device n the total power of all devices transmitting in DR r as pDR rx(n) (r) and the leakage power from devices transmitting in adjacent DRs r′ 6= r and ′ {r, r′ } ∈ NT as pDR rx(n) (r ). The selection of PDRID r for device n is based on: 1 DR ′ arg min = pDR , (2) rx(n) (r) + prx(n) (r ) · r β

where β = 100 is the leakage coefficient [5]. For each PDRID selection method we consider the HD and FD cases for device discovery. In HD, devices cannot transmit and receive at the same time, i. e. devices transmitting in the same time over different frequency bands cannot discover each other, as agreed upon in 3GPP RAN1 [8]. In FD, we assume that devices transmitting at the same time over different frequency bands can discover each other. A device is assumed to be successfully discovered if the signal-to-noiseplus-interference-ratio (SINR) exceeds a given threshold γth (assumed 10 dB in the simulations):

P

2 pDR rx(n) (r) · |hn(r),m(r) (t, r)| k6=n

2 2 pDR rx(k) (r) · |hk(r),n(r) (t, r)| + σ

≥ γth ,

(3)

where |hn(r),m(r) (t, r)|2 is the channel gain between device n and device m at frequency band r at time t, and |hk(r),n(r) (t, r)|2 is the channel gain between device k and device n at DR r. While the random approach is likely to result in high interference since some devices pick randomly the same DR, the greedy approach is a distributed approach to minimize interference. The coordinated approach is a centralized approach to minimize interference. IV. S IMULATION R ESULTS This section, presents system level simulation results for device discovery based on the 3GPP simulation and layout assumptions described in Section II [2]. Our analysis is based on simulation layout options 2, 3 and 5 with uniform and hotspot UE distribution as introduced in Section II A. We consider a macrocell consisting of three sectors with different ISDs for each simulation layout. Fig. 2 depicts, as an example, the simulation layout option 5, in which two-third of the UEs are dropped within a radius of 40 m and the remaining UEs are uniformly distributed within the macrocellular area. Throughout the simulations we assume that NF = NRG (unless stated otherwise), i.e. all available RGs are used for discovery. Further details about system level simulation parameters are provided in Table II. Fig. 3 depicts the reference signal received power (RSRP)2 for different layout options assuming that UEs are transmitting with maximum power ptx and the RSRP is larger than -114 dBm. This is the range for UE reselection in D2D communication [9]. Layout option 2 shows the smallest RSRP range because of the I2I and O2I penetration losses. Layout option 2 and 3 have the same ISD and the same minimum RSRP. However, layout option 3 achieves higher RSRP values due to the lack of penetration 2 While UEs do not transmit cell specific reference signals (CRS) in LTE, we define RSRP to refer to the maximum transmit power minus path loss.

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Table II: Simulation parameters.

Carrier frequency System bandwidth Subframe duration Number of RGs Number of macrocells Maximum transmit power ptx Number of UEs per sector Path loss model Shadowing correlation Shadowing standard deviation Minimum distance UE-UE Thermal noise density

450 Average number of discovered UEs

Parameter Cellular layout

Value Hexagonal grid, 3 sectors per cell, reuse 1 700 MHz 10 MHz 1 ms 50 3 23 dBm 150 Winner channel model see [8] Spatially correlated see Table I. 3m -174 dBm

400 350

300

250 200

150 100

Layout 0.9 option 5 0.8 uniform drop

Layout option 5 hotspot drop

400

0.6 CDF

0 2

450 Average number of discovered UEs

0.7

350

Layout option 3

300

0.4 0.3

3

4

5

6 NT

7

8

9

10

Coordinated - FD Coordinated - HD Random - FD Random - HD Greedy - FD Greedy - HD

250

0.2

200

Layout option 2

0.1 0 −120

50

Figure 4: Average number of discovered UEs in layout option 2.

1

0.5

Coordinated - FD Coordinated - HD Greedy - HD Random - FD Random - HD Greedy - FD

150

−100

−80

−40 −60 RSRP

−20

100

0

Figure 3: CDF of RSRP for different layout options.

50 0 2

losses for outdoor UEs. A similar behavior is observed for layout option 5 hotspot and uniform UE drop. The minimum RSRP is the same because of the same ISD and the maximum RSRP is larger in case of hotspot UE drop due to small UE distances. Fig. 4 and Fig. 5 show the performance of the D2D discovery algorithms discussed in Section III in terms of average number of discovered UEs versus NT for layout options 2 and 5 hotspot UE drop. In both figures, the solid lines represent the HD case and dashed lines the FD case. For each D2D discovery algorithm, it can be observed that the FD case always outperforms the HD case due to the fact that devices transmitting in the same time slot can also be discovered in FD. For small NT the algorithms show similar performance. For larger NT the random PDRID selection method shows the weakest performance due to collisions during random DR selection of UEs. The greedy and coordinated PDRID selection algorithms yield similar performance. This means that the coordinated DR selection algorithm, which is a centralized algorithm based on path loss estimation using known D2D distances, obtains slightly better performance than the greedy approach, which is a distributed approach based on known received powers.

3

4

5

6 NT

7

8

9

10

Figure 5: Average number of discovered UEs in layout option 5 hotspot.

In Fig. 6 to Fig. 9 we depict for layout options 2, 3 and 5 (hotspot and uniform UE drop) the CDF of the number of discovered UEs for different NF − NT value combinations, when the total number of DRs NF × NT is constant in case of coordinated and greedy PDRID selection, respectively. With increasing NT (decreasing NF ) the number of discovered UEs increases for all cases, because of the HD assumption. The number of discovered UEs increases with larger NT at the expense of discovery delay. V. C ONCLUSION In this paper, we provide an overview of the LTE ProSe channel modeling and evaluation methodology framework, which has been recently discussed/agreed upon in the 3GPP RAN standardization group. We present a system level simulation environment based on 3GPP assumptions and discuss three preliminary DR selection algorithms, namely: the random, the greedy and the coordinated algorithms. The performance evaluation of these algorithms is performed based

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1

1

0.9

0.9

0.8

0.8 Layout option 3

0.7

0.7

0.5

0.4 0.3 0.2 0.1 0 0

NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 10 20 30 40 50 60 70 80 90 100 Number of discovered UEs

0.4 0.3 0.2 0.1 0 0

Figure 6: CDF of number of discovered UEs for layout options 2 and 3 in case of coordinated PDRID selection.

1

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0.7 0.6 Layout option 5 0.5 uniform

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CDF

0.3

NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 10 20 30 40 50 60 70 80 90 100 Number of discovered UEs

Figure 8: CDF of number of discovered UEs for layout options 2 and 3 in case of greedy PDRID selection.

1

0.4

Layout option 3

0.6 Layout 0.5 option 2

CDF

CDF

0.6 Layout option 2

NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 60 100 120 140 40 80 Number of discovered UEs

0.3 0.2 0.1 0 0

20

NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 NT = 2 NF = 50 NT = 4 NF = 25 NT = 10 NF = 10 40 60 80 100 120 140 Number of discovered UEs

Figure 7: CDF of number of discovered UEs for layout option 5 (hotspot and uniform drop) in case of coordinated PDRID selection.

Figure 9: CDF of number of discovered UEs for layout options 5 (hotspot and uniform drop) in case of greedy PDRID selection.

on a 3GPP compliant system level simulation environment. The random approach gives poor results due to collisions when compared to coordinated and greedy techniques. The discovery performance can be improved by stacking the DRs in time rather than in frequency in case of HD.

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