Public safety users’ priority-based energy and time-efficient device discovery scheme with contention resolution for ProSe in 3GPP LTE-A systems Zeeshan Kaleem1, 2, Yunpeng Li1, KyungHi Chang1* 1
Electronic Engineering Department, Inha University, Incheon, Korea Electrical Engineering Department, COMSATS IIT, Wah Campus, Pakistan * Corresponding Author:
[email protected], +82-32-860-84221 2
Abstract: A device-to-device discovery scheme is a key enabler for proximity-based services in 3rd generation partnership project (3GPP) long-term evolution advanced (LTE-A) systems for public safety and general LTE scenarios. The deployment of device-to-device (D2D) networks results in severe co-channel interference between conventional cellular users and D2D users, and also faces proximity interference management challenges because of the co-existence of multiple D2D users. In this paper, we propose a time and energy-efficient contention-resolving device discovery resource allocation (TEECR-DDRA) scheme that has the capability to enhance the success ratio for discovery of D2D users by reducing collisions among users. Moreover, the proposed TEECR-DDRA scheme has the ability to prioritize public safety (PS) users to meet their QoS and latency requirements. Furthermore, multi-channel slotted ALOHA with energy sensing can be used to increase the probability of successful discovery of non-PS users. This ability helps to reduce the discovery time of PS users under disaster scenarios, and also reduces the energy consumption of non-PS users by minimizing the number of beacon retransmissions. System-level simulations show that the proposed TEECR-DDRA scheme performs remarkably well under a densely deployed D2D network. Compared with the conventional random access scheme, the proposed scheme almost doubles the discovery range and significantly improves the success ratio for discovery of D2D users. 1. Introduction The incredible popularity of smart phones and the concept of the internet of things (IoT) has encouraged a 1000× increase in the aggregate data rate for next-generation mobile communications (5G) systems [1]. To achieve that data rate, a major paradigm shift is required in conventional homogeneous macrocells that is evolved eNodeB (eNB)-based network architecture. D2D communications was identified in third generation partnership project (3GPP) Release 12 [2] as the new driver in the wireless networking and mobile market for offloading traffic from the conventional overloaded eNB-based cellular network architecture. There are several motivating factors behind 3GPP adopting D2D, such as the popularity of proximity-based services (ProSe) for social networking applications, context-aware applications, high spectral-efficiency and lower-delay applications, enhancement of the user experience, and as an enabler technology for IoT in 5G systems [3]. Another motivation for incorporating D2D into Long term evolutionadvanced (LTE-A) comes from the urgent needs of providing public protection and disaster relief (PPDR) during disasters conditions and for mission-critical situations. Currently, in the market many ad-hoc network-based technologies such as WiFi or Bluetooth, provide D2D communications functionality.
This manuscript has been edited by Nurisco (http://www.nurisco.net) regarding English corrections.
1
Figure 1 Different types of D2D discovery schemes based on the level of operator control in 3GPP ProSe LTE.
However, these technologies work in the unlicensed band, and thus, interference is uncontrollable, they cannot guarantee quality of service (QoS), and they are less secure. In order to improve this situation, D2D discovery underlaying cellular architecture has different levels of operator controls to combine the benefits of both the ad-hoc and controlled networks. The selection of the level of operator control depends upon two main conditions. First is D2D coverage scenarios, such as in-network coverage, partial network coverage, and out-of-coverage scenarios [4]. Second is user service requirements, such as QoS, latency, public safety (PS) applications and use cases, and interference situations. In 3GPP Release 12 [4], D2D discovery for PS and non-PS user equipment (UE) is currently only possible in-network coverage scenario, as shown in Figure 1. Thus, in this paper we will focus only on in-network coverage deployment scenarios for both PS and non-
PS UE deployments. For example, in case of in-network coverage deployment scenario, two schemes are possible. In fully operator-controlled link establishment, or UE-specific type-2 discovery [2], the operator has full control during discovery phases in the sense of radio resource allocation and other mechanisms, and thus interference can be well managed, and QoS can be guaranteed. In the partially operator-controlled scenario or non UE-specific type-1 discovery [2], the radio resources will be initially allocated by the operator to the group of users, and there will be contention among the users to get resources for discovery, as shown in Figure 1. The partially operator-controlled situation is beneficial because there is less feedback overhead and complexity but more interference, compared to fully controlled situation. Since, the number of UE demanding D2D services will be very high in the future, type-1 discovery is the best choice for non-
2
PS users. Furthermore, for users demanding priority radio resources in disaster situations, type-2 discovery will be a better choice for this deployment. 2. Literature review In the literature, one of the major design challenges for D2D discovery is radio resource allocation, where each device selects one of the discovery resources to transmit its discovery signal. Most of the existing radio resource allocation solutions, like fractional frequency reuse [5], power control schemes [6], and cooperative scheduling schemes [7], are based on the conventional eNB architecture. These solutions are not suitable for D2D scenarios because of their suitability only under the fully operator-controlled scenario. Similarly, a number of recent works in D2D have focused on the issue of radio resource management related to D2D communications [8], for example, interference-aware resource allocation schemes [9], joint scheduling and resource allocation [10], and distributed power control [11]. However, relatively less attention has been given to D2D discovery, which is the key enabler for the new proximity-based services. The major design goals of the D2D discovery scheme are energy efficiency, a long discovery range, QoS improvements, and suitability for both PS and non-PS scenarios. In order to achieve these goals, some schemes, like location-based discovery schemes [12], energy-efficient discovery by considering the proximity area [13], inter-cell interference coordination-based D2D discovery schemes [14], D2D discovery for proximity services [15], collision resolution schemes for D2D discovery [16], and D2D communications for public-safety [17], have been proposed. Although, some of the proposed D2D discovery solutions [1217] result in energy savings, proposed new discovery architectures, simplicity, and time-efficient discovery, these schemes pose many challenges. For example, [13-14] increased the number of devices discovered by avoiding collisions or interference and by considering users’ location information, the frame structure considered by these schemes is not in line with the agreements within the 3GPP [4]. Hence, these schemes are not suitable for future D2D discovery schemes based on 3GPP LTE-A. Although, the frame structure of [16] is in line with the 3GPP standard, their proposed frame structure is not suitable for discovering a greater number of devices, because it reserves some specific resources for beacon collision detection. Furthermore, most of the proposed schemes focus on random channel access, which results in more collisions, and hence, results in more energy consumption due to retransmissions. Moreover, all the proposed schemes are static in nature, because they independently consider the resource allocation problem for PS users and non-PS users, that is, no priorities have been given to PS users while allocating resources. Contributions: Therefore, motivated by these challenges, in this paper we propose a time and energyefficient contention-resolving device discovery resource allocation (TEECR-DDRA) scheme by using multi-channel ALOHA with optional energy sensing (MCALOHA-ES) for ProSe in 3GPP LTE-A. The
3
Figure 2 D2D scenarios for PS and non-PS UEs in 3GPP LTE Rel. 12 [2].
main advantages of the proposed TEECR-DDRA scheme, compared to other solutions presented in the literature [12-17] are : 1) We dynamically adjust and reserve discovery resources (DR) by considering the number and priority of PS users sending the connection request for device discovery which reduces contention among PS users and thus have very less chances of collisions, 2) we use the concept of MCALOHA-ES if the counter exceeds a certain threshold, in order to avoid beacon collisions that is, if nonPS users fail to access the channel after some attempts, then the channel access scheme will switch from random access (MCALHOHA) to random access with energy sensing (MCALOHA-ES). This scheme will help to reduce time and energy consumption by avoiding collisions, and will not waste energy on beacon retransmissions. As far as we know, the centralized D2D discovery scheme based on the MCALOHA-ES has not been proposed in any of the literature, 3) The proposed TEER-DDRA scheme can be readily applied to 3GPP LTE-A based systems without any modification because it has been designed by following 3GPP specifications [4]. This paper is organized as follows. In Section 3, we discuss the D2D discovery scenario and the proposed frame structure. In Section 4, we provide a detailed description of the D2D discovery system, channel, and priority models for 3GPP LTE ProSe. In Section 5, we propose the TEECR-DDRA scheme
4
using MCALOHA-ES for ProSe in 3GPP LTE-A. The simulation results of the proposed scheme are presented in Section 6. Finally, in Section 7, we draw conclusions. Table 1 D2D Scenarios Descriptions. Scenarios 1A: Out-of-Coverage 1B: Partial-Coverage 1C: In-Coverage-Single-Cell 1D: In-Coverage-Multi-Cell
Device 1 Out-of-Coverage In-Coverage In-Coverage In-Coverage
Device 2 Out-of-Coverage Out-of-Coverage In-Coverage In-Coverage
3. D2D discovery scenario, frame structure, & resource allocation in 3GPP LTE ProSe 3.1. D2D discovery scenario
In this paper, we consider in-network coverage scenario 1D with multiple-cell deployment form the four possible deployment scenarios [2] shown in Figure 2. In this scenario, all devices that need to discover each other lie inside the network coverage area. The detailed descriptions of the scenarios are summarized in Table 1. D2D discovery is the initial step for D2D communications, where UE wishing to be discovered by other users in its proximity broadcast will broadcast a beacon containing identification (ID) information on the allocated DR. The other UE trying to perform discovery will scan the DR during that beacon transmission period. To successfully decode the received beacon, the signal-to-interference-plus-noise ratio (SINR) should be above a certain threshold (SINR is discussed in the system model section). Due to the half-duplexing constraint, UE transmitting the beacon cannot scan the DR to discover other UE in its proximity. D2D discovery is categorized as two main types: type-1 and type-2 as discussed above. In the type-2 discovery scheme, the discovery resources, the power allocation for the DR, and other mechanisms are centrally controlled by the eNB. For the type-1 discovery scheme, initially, the DR are reserved by the eNB, but latter, there is contention between the users to access the resources. Hence, type-2 is suitable when there are fewer users owing to more signaling overhead and complexity, whereas type-1 is suitable for ultradense network (UDN) deployment. In this paper, we consider type-2 discovery for PS users (PUs) and type2 for non-PS users (NPUs) because of two different types of UE in our scenarios. 3.2. Frame structure for D2D discovery
The 3GPP agreed to use LTE uplink (UL) radio resources for D2D discovery [4]. Hence, in this paper, D2D UE (D-UE) utilizes the uplink resources to discover devices in its proximity. In order to guarantee performance for D2D discovery, UL resources will be reserved periodically after every TDis
10sec , with
frequency domain reserved resources of N Dis 44 resource blocks and time domain resources of f
5
t N Dis 64 subframes in 10 MHz LTE system bandwidth. The remaining resources are reserved for the
conventional cellular UEs (CUEs) connected to the eNB for UL transmission, as shown in Error! Reference source not found. (a). Since, in our proposed scheme, we have PUs and NPUs, we further divided the DR into two portions that will be dynamically adjusted according to the number of PUs sending the emergency connection request to the eNB. 3.3. Resource allocation in 3GPP LTE ProSe for D2D discovery
There are two main categories for D2D discovery resource allocation in 3GPP ProSe: random resource allocation and sensing-based resource allocation. In case of random resource allocation, all devices in the system randomly select their DRs for beacon transmission from the available DRs. This has the benefits of low latency time and low feedback complexity, but at the cost of more chances for collisions among the users sending the beacon while accessing the same channel at the same time. On the other hand, in sensingbased discovery resource allocation UE u considers its received energy levels on the available DRs during the discovery slot and selects its DR d based on the minimum received energy as follows:
arg min EuRx .
(1)
d
Sensing-based resource allocation results in fewer chances of collisions between users, but at the cost of high feedback complexity. Thus, in this paper, to combine the benefits of random and sensing-based channel allocation, we utilize both resource allocation schemes based on the number of unsuccessful beacon transmissions. For random resource allocation, we utilize the multi-channel slotted ALOHA (MCALOHA) [18], and for sensing-based resource allocation, we add the functionality of sensing to MCALHOA (MCALOHA-ES) for smart D2D discovery. 4. D2D discovery system, channel, and priority models in 3GPP LTE ProSe 4.1. System model for D2D discovery
In this paper, the UL of an LTE-A system is considered. In LTE-A, the physical resource block (PRB) is defined as a group of 12 consecutive subcarriers in the frequency domain while the subframe or transmit time interval (TTI) duration is 1 ms which consists of 14 OFDM symbols in the time domain. Due to the fixed size of PRBs, there are 50 PRBs for a system bandwidth (BW) of 10 MHz. For D2D discovery, each UE requires a minimum of 2 PRBs to transmit and receive the beacon [2]. Because D2D discovery is using UL resources, at 10 MHz BW, 6 PRBs out of 50 are required to transmit physical uplink control channels (PUCCH), while the remaining 44 PRBs are DRs that are available to transmit and receive the beacons, as shown in Figure 3 (b). In this paper, we assume that all users are in the radio resource control (RRC)
6
connected state, that is the D2D link setup procedure is not considered. Moreover, we also assume that all D-UEs are synchronized and using scenario 1D, where all UEs lie inside network coverage. The synchronization reference is obtained from the eNB downlink (DL) transmission. Synchronous discovery has the advantage of consuming less energy, because by using synchronous discovery, D-UE wakes up only during the predefined discovery time. Performance statistics, such as the number of discovered UEs and the probability of successful discovery of D-UEs is gathered only from the region of interest (ROI), where the center cell with three sectors is considered as ROI. In each sector, the set of indices for UE u involved in D2D discovery is denoted by U. This set consists of a total N number of UEs, which includes both the D2D PS UEs (DPUs) and D2D Non-PS UEs (DNPUs) which can be represented as: N
U
DPUsi , DPUsi
1
, ......., DNPUsN 1 , DNPUsN .
(2)
i 1
Tar
In this paper, due to half-duplexing constraint the target discoverable UEs ( S j ) consists of N UEs except the K UEs simultaneously transmitting the discovery beacon during the j-th subframe of discovery period T. Thus, the discoverable UEs set for UE u can be represented as: K
SuTar ,j
ukTx ,
N
(3)
k 1, k u
During the discovery period, UE u can be either transmitter u considered to be discovered by u SINR threshold (
thres
Tx
, if the receive SINR (
), where the value of
thres
Rx u
Tx
or receiver u
) at user u
puTx (d ) huTx ( d ),u Rx ( d ) ( j, d )
(d ) v
Tx
p (d ) huTx ( d ),v Rx ( d ) ( j, d ) u
where pu (d ) is the transmit power of D-UE u and u
Rx
is
is greater than the prescribed
Tx
to UE u
Rx
is given as:
thres 2
2
,
(4)
and huTx ( d ),u Rx ( d ) ( j, d ) is the channel gain between u
Tx
on PRB d during the j-th subframe. The interference from the neighboring D-UEs is represented as 2
v
Tx
Rx
2
2
Tx v
where u U . UE u
4.5 dB is selected based on simulations as explained in
Section 6. Thus, the SINR of the beacon transmitted on DR d from UE u
Rx u
Rx
Rx
pTx (d ) huTx ( d ),vRx ( d ) ( j, d ) , whereas the noise power is given as u v
2
.
7
(a)
(b) Figure 3 D2D discovery frame structure. (a) D2D discovery uplink frame structure for PS and non-PS UEs. (b) Detailed view of the device discovery frame structure with PUCCH showing the dynamical adjustment of the discovery resource by considering DPUs priority.
The D2D discovery system for DNPUs cannot be centrally controlled because there is no coordination between D-UEs and no signaling from the eNB during the discovery procedure. Moreover, there is a lot of DNPUs using same PRBs at the same time; hence this results in collision or interference, which results in degradation of signal quality. In our proposed D2D discovery system, during each discovery period T, each D-UE u the beacon with probability p and listens to the other beacons with probability 1
Tx
can transmit
p . Collision will occur
8
if two D-UEs concurrently transmit beacons on the same DR [19]. Thus, the probability that D-UE u discover its neighbor u
Rx
Tx
can
out of N neighboring D-UEs during the G discovery periods, is calculated as
follows:
PuTxu Rx
1
1 p(1 p) N
1 G
(5)
Thus, the probability of discovering the maximum number of D-UEs with Equation (5) is upper bounded at:
1 N 1 (1 N 1 ) N
1
max PuTxu Rx p
1 G
(6)
Thus, from Equation (6) we conclude that for a large number of users N in a D2D discovery system, the discovery time will be large because of more collisions which results in beacon retransmissions. The discovery success ratio (DSR) of user u is defined as the ratio of the number of discovered users in the region of interest to the total number of users in the ROI, except for the discoverer. Thus, DSR is calculated after using Equation (3) as follows: DSRuTx, j
No. of discovered users in ROI Total users in ROI except discoverer max_ TTI
j 1
SuTar , j u, j
(7)
N 1 0, uRx thrsh where u , j Rx thrsh 1, u
where
u , j is the detection indicator for a user u during a subframe j, and max_TTI is the total number of
subframes in discovery period T. Similarly, discovery failure ratio (DFR) is a metric that help to find the number of unsuccessful discovery attempts by the user. This metric is calculated by using Equation (7) as follows:
DSRuTx, j 1 DSRuTx, j
(8)
4.2. Channel model for D2D discovery
The channel model represents the propagation loss that occurs when the signal travels from the transmitter to the receiver. The general equation to model the channel gain (G) is given as:
G(dB)
AG PL Shd
F,
where antenna gain (AG) of the D-UE and CUEs is AG
(9)
0 dB from using an omni-directional antenna.
Pathloss (PL) from transmitter to receiver is due to the distance between D-UEs or between the CUE and
9
the eNB. In this paper, to calculate PL of the UEs connected to an eNB, the urban area model [20] is considered and calculated as follows:
PL(dB)
15.3 37.6 log10 ( R),
(10)
where R is the distance between eNB and CUEs in meters. To calculate PL between D-UE u
Tx
and D-UE
u Rx the line-of-sight WINNER+B1 case is used [2], which can be represented as follows: PL(dB)
35.4 22.7 log10 ( R1 ),
where R1 is the distance between D-UE u
Tx
and D-UE u
(11) Rx
in meters.
In Equation (9), shadowing ( Shd ) is caused by obstacles in the paths between the UEs and the eNB/UEs. This is usually modeled by a log-normal distribution with a mean of 0 dB and standard deviation X dB, i.e., different channel models have different X values [2]. Fast fading ( F ) is a consequence of the constructive and destructive combination of randomly delayed, reflected, scattered, and diffracted signal components. This type of fading is relatively fast and is responsible for short-term signal variations that can occur when UEs or reflectors in an environment move short distances. In this paper, to model fast fading we used the Pedestrian-B (PedB) channel model [21]. Table 2 Commercial and public safety users priority table in 3GPP ProSe LTE-A. User Priority
User Identification
Traffic Class
PS First Responders
PS Emergency; PS1 to PS5
12-14
Commercial User Emergency
Commercial User Emergency
10
Commercial User Non-Emergency
Commercial User Non-Emergency
0-9
Barring (RACH) Barring For Special Barring For Special Low Barring Factor
Establishment Cause High Priority Access Emergency Mobile Originating
4.3. D2D public safety users priority model for LTE-A radio access
LTE-A is strongly considered as a suitable candidate for PS networks [22], and currently many emergency services are working under LTE. For example, Motorola and other active professional PPDR organizations tested the suitability of PS LTE for transferring videos and other information from the incident location to the central control station using helicopters [23]. Then, this information is further distributed to PS teams like police, firefighters, and ambulance services to prepare themselves for the incident situation. In this realm, the requirement is to develop systems that are highly robust and can address the specific communications needs of emergency services. The main advantage of using LTE for a PS network is its
10
capability to efficiently and centrally manage radio access by considering the emergency users’ priority, latency, and QoS requirements. In order to enhance the capability of PS LTE, D2D or ProSe is strongly considered as a candidate for the PS LTE network [2]. Thus, it is necessary to investigate the impact of D2D communications on enhancing performance of PS LTE. There is the possibility of having two types of D2D scenario for PS LTE as explained in section 1. Thus, in this paper, we consider the situation where DPUs reuses the same spectrum as CUEs. In order to avoid these collisions, PS users in a shared network needs special priority in resource allocation during critical situations, such as disasters and scheduled events like the Olympics and soccer’s World Cup. The main steps in allocating more priority to PS users as compared with commercial users, is described in Figure 4. To prioritize emergency services for DPUs in commercial mobile networks, there must be a solution to limit the amount of connection attempts, as well as to allow priority access for high priority users, including emergency responders. There are two main mechanisms for providing high priority to users in terms of resources: first is in terms of controlling the resources to access the air interface [24], and the other is in terms of resources for service-level prioritization [25]. Because, in this paper our problem is related to D2D discovery and not communications, we will prioritize the network based on accessing the air interface rather than service-level prioritization. Service-level prioritization will be discussed in our future work on D2D communications. The purpose of giving radio access priority to certain users is to give services to the users in case of emergency. Broadcast messages should be available on a cell-by-cell basis indicating the classes or categories of subscribers barred from network access. The use of these facilities allows the network operator to prevent overload of the access channel under critical conditions. It is not intended that access control be used under normal operating conditions [24]. To allocate resources users are classified based on their priorities; that is, all UEs are members of one out of ten randomly allocated classes for commercial users, defined as access classes 0 to 9. The class number is stored in the universal subscriber identity module (USIM). In addition, UEs may be a member of one or more of 5 special categories (classes 11 to 15), which are also stored in the USIM [24]. Brief summaries of each access class, explaining the radio link establishment cause and its priority, are described in Table 2. The PS users inside the special categories are further classified as follows. PS priority 1: executive leadership and policy makers; PS priority 2: disaster response and military command and control; PS priority 3: public health, safety, and law enforcement command; PS priority 4: public services/utilities and public
11
Figure 4 Main steps to prioritize the shared radio access network among the PS and commercial users (NPUs) in ProSe LTE.
welfare; PS priority 5: disaster recovery (e.g. national communications systems). Details regarding services that come under each class in the special categories are provided in Table 3. 5. Proposed TEECR-DDRA scheme by using MCALOHA-ES for ProSe in 3GPP LTE-A The existing communications schemes under the cellular network architecture have targets such as high data rates for users, improvement in link reliability, and decreases in outage probability. For D2D discovery, the main goals are to increase the number of users detected and discovered by D-UE u
Tx
in its
12
Table 3 Public safety priority table for special categories in radio access classes. PS User Priority
PS Priority 1: Executive Leadership PS Priority 2: Disaster Responses PS Priority 3: Emergency Command PS Priority 4: Public Services PS Priority 5: Communications Systems
User Identification
Traffic Class
Reserved
15
PS Emergency (All)
14
PS1
14
PS2
13
PS3
13
PS4
12
PS5
12
Barring (RACH) Barring For Special Barring For Special Barring For Special Barring For Special Barring For Special Barring For Special Barring For Special
Establishment Cause High Priority Access High Priority Access High Priority Access High Priority Access High Priority Access High Priority Access High Priority Access
surroundings, in less time, with fewer beacon retransmissions, at farther distances from D-UE u
Tx
,
considering the priority of DPUs, and by consuming less energy. Thus, in this section, to achieve all these aims, we propose the TEECR-DDRA scheme using MCALOHA-ES. This scheme has the capability to dynamically adjust the DRs by dividing them into two parts based on user’ priority: 1) reservation of the non-contention-based separate resources for high priority DPUs and 2) contention-based resources for DNPUs. But this scheme can avoid or reduce contention by using efficient MCALOHA-ES schemes that can help to smartly discover the neighboring D-UEs. The other prominent features of the proposed scheme are already explained in the section 2. The main steps of the proposed TEECR-DDRA scheme are as follows:
Figure 5 System-level simulation environment for performance evaluation of the proposed TEECR-DDRA scheme.
13
Table 4 TEECR-DD Scheme by using MCALOHA-ES for ProSe in 3GPP LTE-A TEECR-DD Scheme for Efficient Device Discovery 1. Initialization T 1, No. of DPUs 1, 2,....., M
M 1, M 2,....., N 1, 2,....., P
No. of DNPUs No. of DRs
2. Discovery Resources Request In the current T , the DPUs send the request to the eNB for resource allocation. 3. Contension-based Discovery Resources Allocation If {No. of DRs < No. of DPUs} eNB will reserve all the available DRs for the DPUs in the upcoming first DTP (E.g., T=2). The remaining non-scheduled DPUs will send the ERMs to the eNB again in the upcoming first DTP, and get the EDRs in the upcoming second DTP (E.g., T=3). The DNPUs will contend for the DRs in the upcoming second DTP by using MCALOHA / MCALOHA-ES schemes. T T 1 DNPU i
_C
DNPU i
_C
1
Repeat the Procedure from step. 2. else eNB reserves R EDRs for the DPUs, and remaining (P - R) DRBs for NPUs in the upcoming first DTP. 3.1 Intra-DNPUs Resource Allocation Scheme If {DNPU i > W } The corresponding DNPUs select the DRs by using MCALOHA-ES scheme to reduce collisions. else DNPUs will select the DRs by MCALOHA scheme. end end 4. Discovered Users Computation If {SINR i < SINR threshold } The unsuccessful DNPUs will get DRs in the upcoming second DTP. T T 1 DNPU i
_C
DNPU i
_C
1
Repeat the Procedure from step. 2 until all users are discovered. else Desired users are discovered. end
Initialization: In this step, DPUs and DNPUs are deployed inside the network coverage area by using urban macro scenario 3, which is a common and suitable scenario for both general and public safety situations [4], and a total of 125 UEs deployed per sector. The details regarding the deployment scenario are
14
discussed in the performance evaluation section of this paper. The discovery time period (DTP) T and the retransmissions counter for DNPUs are initialized to T
1 and DNPU _ C 0 , respectively.
Discovery resource blocks allocation for DPUs & DNPUs: During the resource allocation step, the requests from DPUs are given priority by the eNB while reserving resources; that is, the resources will be dynamically adjusted according to the number of DPUs sending emergency connection requests. If there are more number of DPUs compared to DRs, then during the j-th subframe of the discovery period T, no resources will be reserved for DNPUs, and the DNPUs will be served in the upcoming discovery period. After reserving the resources, the round robin scheduler is used to allocate the resources among the DPUs. For DNPUs, MCALOHA and MCALOHA-ES is utilized to allocate resources in order to avoid contention. Condition for switching from MCALOHA to MCALOHA-ES for DNPUs: To provide more diversity in channel access to DNPUs, the switching concept is utilized when there is severe contention for channel access. That is, when the number of unsuccessful attempts of DUE u
Tx
exceeds the predefined
counter value W, then channel access protocol switches from MCALOHA to MCALOHA-ES in order to avoid the contention. This results in a reduction of unnecessary transmission energy. The detailed steps of the proposed scheme are shown in Table 4. 6. System-level simulations for performance evaluation of the proposed TEECR-DDRA scheme 6.1. Simulation environment and assumptions To evaluate the performance of the proposed TEECR-DDRA scheme, the system-level simulations are performed based on 3GPP specifications and assumptions under the urban macro layout scenario [4]. We evaluated the results by designing the MATLAB based system-level simulator that take cares of the 3GPP specifications [4] requirements for simulator design. The main simulation parameters are summarized in Table 5. We focus on the urban macro layout scenario because it is mandatory for both the general and public safety scenarios. The deployment layout consists of 7 eNB sites following a hexagonal layout with an inter-site distance (ISD) of 500m. Each site consists of three hexagonal sectors with antenna boresights pointing in three horizontal directions, separated by 120 degrees. In the deployed scenario, the center cell with 3 sectors is considered as the region of interest, with UEs in other cells only providing interference. The ROI consists of eNBs, DPUs, and DNPUs with all UEs (that is, DPUs and DNPUs) deployed outdoor, and the number of deployed D-UEs in a cell is 125 [2]. The system-level simulation environment in Figure 5 where green UEs represent PUs and gray UEs are NPUs. We assume that each UE can transmit discovery signals with equal probability. Moreover, in this scenario, each UE is interested in discovering all other UEs
15
Table 5 System-level Simulation Parameters. Parameters
General & Public Safety Scenarios
LTE Layout
Hexagonal grid, 7 cell sites, 3 sectors per site Option 3: Urban macro (500m ISD) (uniform outdoor UEs)
Carrier Frequency
2 GHz
Network Synchronization
eNBs are synchronized with each other
System Bandwidth, No. of PRBs
10MHz Uplink, 50 PRBs
Discovery Signal Bandwidth
2 PRBs
Network Operation
100% eNBs enabled
UE Mobility
3 Km/h
UE RF Parameters
Max Tx Power: 23 dBm (PS and Non-PS UEs) Antenna gain: 0 dBi, Noise Figure: 9 dB
Total Number of UEs for Discovery per Sector
Uniform (Outdoor): 125 PS UEs: 30% Non-PS UEs: 70%
Discovery Resource Pool Configuration, Discovery Period
44 RBs over 64 Subframes, 10 sec
Simulation Length
64 Subframes (TTI), 20 Drops
Discovery Resource Selection Schedulers
PS UEs: RR Non-PS UEs: MCALOHA/MCALOHA-ES
UE Drop Pathloss Model Shadowing Standard Deviation
Uniform drop: All UEs are randomly and uniformly dropped throughout the macro geographical area. All UEs are dropped outdoors. No buildings are dropped. WINNER + B1 7dB Log-Normal
Fast Fading
Ped B
Priority Modeling
Using Access Class Barring Models
in the ROI, and each D-UE periodically transmits a discovery signal to maximize the discovery probability in every period T. We also assume that UE is defined to be discovered by other UE if it is discovered once during period T. Due to the half-duplexing constraint, the UEs sending a beacon on DR d during the j-th subframe of the discovery period T is not to be able to receive the discovery signals that are transmitted in that subframe by other UEs. Hence, for N D-UEs, the maximum number of D2D links is N
2
N , which has
a polynomial growth rate.
16
(a)
(b)
(c)
Figure 6 (a) SINR detection threshold selection based on the target LTE scenarios. (b) CDF of the number of users discovered. (c) Discovery time vs. number of discovered users.
For the purpose of verification of the proposed scheme, we considered simulation scenarios with 30% of the PUs users in the ROI while the remaining 70% of the UEs are DNPUs. In order to select the DR, there are three different options for selecting DR d according to the priority of the users: a) conventional random channel selection using MCALOHA for all users, b) channel selection by using the proposed TEECRDDRA scheme by giving priority to PS users, and c) energy sensing-based smart DR d selection under the proposed TEECR-DDRA scheme for users without PS priority. We evaluated the performance of the proposed TEECR-DDRA scheme under the urban macro layout scenario in terms of average number of discovered UEs, the range of the discovered UEs, the ratio of successful discovery of the UEs, and the UEs missed detection ratio.
17
6.2. SINR threshold selection for UE detection under various LTE scenarios The discovery range of the discoverer UE sending the beacon varies by changing the SINR threshold. In 5G systems, users have diverse requirements; for example in a general LTE scenario, most of the users want to discover a nearby user to establish a D2D communications link, and discoverer wants to broadcast the beacons within a small range but with high QoS requirements. UEs under a PS-LTE scenario desires a high discovery range during disaster situations because there is no general network coverage. Thus, the discoverer under the PS-LTE scenario wants to send the beacon as far as possible with minimum QoS requirements. In this paper, since we focused on a mixed scenario by deploying both the PUs and NPUs, the SINR threshold in this scenario will lie in between these two scenarios. Thus, we selected an SINR threshold of 4.5dB for the mixed scenario, because it provides the best trade-off between the number of discovered UEs and the received signal power for a better D2D communication link, as shown in Figure 6 (a). All the simulation results discussed in Section 6 are plotted by using this SINR threshold. 6.3. Number of discovered UEs under the proposed TEECR-DDRA scheme The number of users discovered during the discovery period depends upon the interference situation in the network. In order to discover more users, the discovery scheme should be dynamic in nature so it can avoid interference by intelligently allocating the DR between users, and so collisions between users can be avoided. The discovery scheme should also have the capability to consider user priority so that high-priority users can be scheduled on time by meeting their delay and QoS requirements. By considering this situation, we propose the TEECR-DDRA scheme, which has the capability to dynamically adjust the DR based on PS priority of the users. The average number of discovered UEs with respect to discovery time under the proposed TEECRDDRA scheme is shown in Figure 6. The simulation results are compared with the baseline conventional random access (RA) scheme without giving priority to PS UEs. In the baseline scheme, each user (PUs or NPUs) will randomly access the DR without having any priority in accessing the DR. Thus, this access scheme will result in more delay in discovering the users in a system, because there is a greater chance of collisions between users. To efficiently access the DR, the proposed TEECR-DDRA scheme gives priority to the PS UEs in a system by reserving a specific portion of the DR by using type-2 discovery. The amount of resources is dynamically adjusted based on the number of PS UEs sending a priority connection request to the eNB. Thus, we can see from Figure 6 (b) that the number of discovered UEs increases compared to the conventional RA scheme. Our proposed scheme also considers the delay and QoS requirements of the non-PS UEs by enabling energy sensing among non-PS UEs when the counter exceeds a certain limit. Thus,
18
its effect can be seen from Figure 6 (b) where, by applying energy sensing for Non-PS UEs, the maximum number of discovered users increases to 430. Similarly, the average number of discovered UEs with respect to the discovery time under the proposed TEECR-DDRA scheme, is shown in Figure 6 (c). The simulation results clearly show the benefit of the proposed TEECR-DDRA scheme, in terms of timely efficient discovery of the UEs. From Figure 6 (c), we can see that around 26 more UEs are discovered by using the proposed TEECR-DDRA as compared to the conventional RA scheme, when the simulation results are compared at the 40th subframe. The number of discovered UEs even increases to 71 when energy sensing is combined with the proposed TEECR-DDRA scheme. By applying energy sensing, the interference level on each resources is checked before allocating the DR to non-PS UEs. Thus, the proposed TEECR-DDRA scheme discovers more UEs in less time as compared to the conventional RA scheme, which also results in less energy consumption for the UEs because of fewer beacon retransmissions due to fewer collisions among UEs. 6.4. Discovery range of the proposed TEECR-DDRA scheme There are two important factors that affect the discovery range of the discoverer broadcasting a beacon for discovery: 1) the SINR threshold as discussed above, and 2) the collision avoidance capability of the discovery schemes. In this paper, the proposed TEECR-DDRA has the capability to reduce collisions between users by dynamically allocating DR d to both PUs and NPUs based on priority and energy sensing. For PUs, the emergency situation priority is considered to increase the chances of successful discovery; and for NPUs, energy sensing is used to decrease the collision probability. From Figure 7 (a), we observe that the proposed TEECR-DDRA clearly outperforms the conventional RA scheme by discovering D-UEs that are farther away. The simulation results are compared at 50% of the cumulative distribution function (CDF), where we find that the discovery range of the conventional RA scheme reached its maximum at 100 m. However, for the proposed TEECR-DDRA scheme with PS priority, the distance increases to 120 m. Furthermore, the discovery range further increases to 155 m by combining gains obtained by giving priority to PUs and energy sensing for NPUs. Therefore, by using TEECR-DDRA, the discovery range of all users participating in discovery is increased, compared to the conventional RA scheme. 6.5. Discovery success ratio of the proposed TEECR-DDRA scheme The discovery success ratio (DSR) defined in (7) is used to calculate the performance of the proposed Tx
scheme. The higher the DSRu , j ratio, the more users are successfully discovered. A device is assumed to be successfully discovered only if the beacon’s received SINR ( u ) exceeds the SINR decoding threshold Rx
19
(
thrsh
); that is u Rx
thrsh
. Thus, u , j 1 if a user is successfully detected; otherwise u , j 0 . Therefore,
DSRuTx, j increases when the user is successfully detected; otherwise, DSRuTx, j decreases.
(a)
(b)
(c)
Figure 7 Comparison of proposed TEECR-DDRA scheme with conventional RA scheme. (a) Users’ discovery distance. (b) Users’ discovery average success ratio. (c) Users discovery average failure ratio.
DSRuTx, j is plotted versus the SINR detection or decoding threshold ( thrsh ) in Figure 7 (b). The Tx simulation results clearly show that by increasing the SINR detection threshold, DSRu , j decreases and Tx finally reaches almost zero at a very high threshold. DSRu , j decreases as the SINR decoding threshold (
thrsh
increases, because most of the users cannot meet the high SINR decoding threshold requirements due to low channel gain. This occurs usually to the users located far from the discoverer users, or when the users are blocked by high buildings or penetration losses. The simulation results in Figure 7 (b) are plotted for a range
20
)
of SINR decoding thresholds, that is, between -15 to 15 dB. From the results, we notice that at
thrsh 15 dB the DSR for the conventional RA scheme is around 36%, while for the proposed TEECRDDRA scheme with PS priority and with energy sensing, it increases to 38% and 40%, respectively. The simulation results follows a similar trend for other SINR decoding points, and finally, at
thrsh
15 dB we
notice that DSR for the conventional RA scheme and the proposed scheme reaches 0.3% and 1.9%, respectively. These gains are achieved because of the capability of the proposed TEECR-DDRA scheme to dynamically adjust the DR based on the number of PS users, allocation of DR by considering the priority of the PS users, and by using energy sensing for the non-PS users. Thus, the simulation results proves the collision avoidance capability of the proposed TEECR-DDRA scheme, compared to the existing RA schemes. 6.6. Discovery failure ratio of the proposed TEECR-DDRA scheme The Discovery failure ratio (DFR) is a metric that help to find the number of unsuccessful discovery attempts by the user. The metric used to calculate is already describe in Equation (8). From Figure 7 (c), we can see that the proposed TEECR-DDRA scheme always has a lower DFR ratio, compared to the conventional scheme. The simulation results are compared at the various SINR detection thresholds, and we found that the proposed TEECR-DDRA scheme results in a 7% decrease in DFR, compared to the conventional RA scheme. DFR decreases because the TECCR-DDRA schemes take cares of the users’ channel conditions and the priority of the PS users while allocating DR among the users. This results in fewer collisions between users, which in turn increases the discovery range and decreases the DFR of the discoverers. 7. Conclusions In this paper, we address the problem of severe co-channel interference in D2D discovery for ProSe in 3GPP LTE-A by prioritizing PS users and implementing energy sensing for non-PS users. We compare the performance of the proposed TEECR-DDRA using the conventional RA scheme as a baseline. Systemlevel simulations are performed under a practical dense D2D network scenario by deploying PS and non-PS users. The simulation results show a remarkable improvement in the number of discovered devices; that is, approximately 28% more devices are discovered, compared to the conventional RA scheme. Moreover, the proposed TEECR-DDRA scheme increases the discovery success ratio and the discovery range by approximately 4% and 50%, respectively, compared to the conventional RA scheme. Furthermore, the discovery failure ratio of users is reduced by 7% under the TEECR-DDRA scheme. The main reasons for
21
the improvement with the proposed TEECR-DDRA scheme are its ability to dynamically adjust and reserve the discovery resources by considering the priority of PS users sending the connection requests for device discovery, and by implementing the concept of switching from random access to energy sensing if unsuccessful discovery attempts exceed a certain threshold, in order to avoid beacon collisions for non-PS users. Hence, we conclude that the proposed TEECR-DDRA scheme is suitable for future mobile communications systems because of its design based on the 3GPP specifications and its capability to guarantee time delay requirements by reducing the number of collisions and providing performance improvement from various aspects, as mentioned above. 8. Acknowledgments This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-H8501-16-1019) supervised by the IITP (Institute for Information & communications Technology Promotion). 9. References [1] Andrews, J., Buzzi, S., Choi, W., Hanly, S., Lozano, A., Soong, A. C. K., Zhang, J. C.: ‘What will 5G be?’, IEEE J. Sel. Areas Commun., June 2014, 32 (6), pp. 1065–1082 [2] 3GPP, ‘Study on LTE device to device proximity services; Radio aspects’, 3GPP TR 36.843 v 12.0.1, 2014 [3] Asadi, A., Wang, Q., Mancuso, V.: ‘A Survey on Device-to-Device Communication in Cellular Networks’, IEEE Commun. Surveys Tuts., Nov. 2014, 16 (4), pp. 1801-1819 [4] 3GPP, ‘LTE Device to Device Proximity Services; User Equipment (UE) radio transmission and reception’, 3GPP TR 36.877 v 2.0.0, 2015 [5] Kaleem, Z., Hui, B., Chang, K. H.: ‘QoS priority-based dynamic frequency band allocation algorithm for load balancing and interference avoidance in 3GPP LTE HetNet’, EURASIP J. Wireless Commun. Netw., Nov. 2014, 2014, pp. 1-18 [6] Ahmad, I., Kaleem, Z., Chang, K. H.: ‘QoS priority based femtocell user power control for interference mitigation in 3GPP LTE-A HetNet’, J-KICS, Feb. 2014, 39A (2), pp. 61–74 [7] Sakr, A. H., Hossain, E.: ‘Location-aware cross-tier coordinated multipoint transmission in two-tier cellular networks’, IEEE Trans. Wireless Commun., Nov. 2014, 13 (11), pp. 6311-6325 [8] Phunchongharn, P., Hossain, E., Kim, D. I.: ‘Resource allocation for device-to-device communications underlaying LTE-Advanced networks’, IEEE Wireless Commun., Aug. 2013, 20 (4), pp. 91–100 [9] Li, Y., Kaleem, Z., Chang, K. H.: ‘Interference-aware resource-sharing scheme for multiple D2D group communications underlaying cellular networks’, Wireless Per Commun, Feb. 2016, DOI 10.1007/s11277-0163203-2 pp. 1–20 [10] Song, L., Han, Z., Zhao, Q., Wang, X.: ‘Joint scheduling and resource allocation for device-to-device underlay communication’, Proc. IEEE WCNC, Shanghai, China, Apr. 2013, pp. 134–139 [11] Fodor, G., Reider, N.: ‘A distributed power control scheme for cellular network assisted D2D communications’, Proc. IEEE GLOBECOM, Houston, TX, USA, Dec. 2011, pp. 1–6 [12] Hu, L.: ‘Resource allocation for network-assisted device-to-device discovery’, Proc. VITAE, Aalborg, Germany, May 2014, pp. 1–5 [13] Prasad, A., Kunz, A., Velev, G., Samdanis, K.: ‘Energy-efficient D2D discovery for proximity services in 3GPP LTE-advanced networks: ProSe discovery mechanisms’, IEEE Veh. Technol. Mag, Dec. 2014, 9 (4), pp. 40-50
22
[14] Babun, L., Simsek, M., Guvenc, I.: ‘Intercell Interference Coordination for D2D Discovery in LTE-A HetNets’, Proc. IEEE WCNC, Istanbul, Turkey, April 2014, pp. 2202–2207
[15] Choi, K. W., Han, Z.: ‘Device-to-Device Discovery for Proximity-Based Service in LTE-Advanced System’, IEEE J. Sel. Areas Commun., 33 (1), pp. 55-66, Jan. 2015 [16] Hong, J., Park, S., Choi, S.: ‘Novel power control and collision resolution schemes for device-to-device discovery’, Peer-to-Peer Netw. Appl., June 2015, 2015, pp.1-10 [17] Fodor, G., Parkvall, S., Sorrentino, S., Wallentin, P.: ‘Device-to-Device Communications for national security and public safety’, IEEE Access, Dec. 2014, 2, pp. 1510-1520 [18] Yue, W.: ‘The Effect of Capture on Performance of Multichannel Slotted ALOHA Systems’, IEEE Trans. Commun., June 1991, 39 (6), pp. 818-822 [19] Zou, J., Wang, M., Zhang, J., Shu, F., Wang, J., Qian, Y., Sheng, W., Chen, Q.: ‘Discovery Signal Design and its Application to Peer-to-Peer Communications in OFDMA Cellular Networks’, IEEE Trans. Wireless Commun., July 2013, 12 (8), pp. 3995-4009 [20] 3GPP, ‘Radio Frequency (RF) System Scenarios’, 3GPP TR 36.942 v 12.0.0, 2014 [21] ITU, ‘Guidelines for evaluation of radio transmission technologies for IMT-2000’, ITU-R M.1225, 1997 [22] 3GPP, ‘Technical Specification Group Services and System Aspects; Feasibility study for Proximity Services (ProSe)’, 3GPP TR 22.803 v 12.2.0, 2013 [23] Motorola, ‘Barricaded suspect incident analysis: enhancing critical incident response with public safety LTE’, 2011 [24] 3GPP, ‘Technical specification group services and system aspects; service accessibility’, 3GPP TS 22.011 v 13.2.0, 2015 [25] 3GPP, ‘Group services and system aspects, policy and charging control architecture’, 3GPP TS 23.203 v 13.5.1, 2015
23
