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IEEE ICC 2013 - Next-Generation Networking Symposium

Efficient Small Data Access for Machine-Type Communications in LTE Sergey Andreev† , Anna Larmo , Mikhail Gerasimenko† , Vitaly Petrov† , Olga Galinina† , Tuomas Tirronen , Johan Torsner , and Yevgeni Koucheryavy† †

Tampere University of Technology, Tampere, Finland;  Ericsson Research, Jorvas, Finland

Abstract—In this paper, we address the emerging concept of Machine-Type Communications (MTC), where unattended wireless devices send their data over the Long Term Evolution (LTE) cellular network. In particular, we emphasize that future MTC deployments are expected to feature a very large number of devices, whereas the data from a particular device may be infrequent and small. Currently, LTE is not optimized for such traffic and its data transmission schemes are not MTC-specific. To improve the efficiency of small data access, we propose a novel contention-based LTE transmission (COBALT) mechanism and evaluate its performance with both analysis and protocol-level simulations. When compared against existing alternatives, our data access scheme is demonstrated to improve network resource consumption, device energy efficiency, and mean data access delay. We conclude that COBALT has the potential for supporting massive MTC deployments based on the future releases of the LTE technology.

I. I NTRODUCTION AND BACKGROUND Machine-Type Communications (MTC) may be defined as information exchange between a device and another entity in the Internet or the core network, or between the devices themselves, which does not necessarily require human interaction. As such, MTC is a very distinct capability that enables the implementation of the Internet of Things (IoT). The mobile network operators are increasingly interested in the IoT applications to bridge in the growing revenue gap, as ARPU of traditional services continues to shrink. Due to its huge market potential, cellular technologies are currently developing air interface enhancements to support the IoT. In particular, Third Generation Partnership Project (3GPP) is becoming increasingly active in this area with several work items defined on MTC, especially for Long Term Evolution (LTE) Release 12 [1]. Related research in [2] suggests that a service optimized for MTC is expected to be considerably different from that for conventional Human-to-Human (H2H) communications. This is particularly true for smart metering applications autonomously reporting usage and alarm information to grid infrastructure [3]. For instance, a potentially very large number of unattended meters, with little traffic per device, may introduce a surge at the serving base station when accessing the network nearly simultaneously [4]. The motivating smart metering use case therefore serves as a valuable reference MTC scenario [5] covering many characterizing MTC features. Together with effective measures for overload control in smart grid, the LTE system shall also

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provide mechanisms to lower power consumption of smallscale battery-powered wireless meters. As transmitted data bursts may be extremely small in size, the network should additionally support efficient transmission of such packets with very low overhead. Accounting for the fact that MTC transmissions may be infrequent with large amounts of time between them, in this paper we target efficient support for small data access within the 3GPP LTE system. Also we emphasize that MTC devices should consume very low operational power over long periods of time and address energy-related performance across our study. We note that these important research problems are insufficiently highlighted in the existing literature which has only been focusing on overload control (see e.g., [6] and [7]). In our previous work [8], we conducted thorough analysis of the overloaded random access channel in the LTE network. In this paper, we continue our investigations with an emphasis on small data access when the network is not experiencing an MTC overload. We propose and detail an efficient small data transmission mechanism which may be used as an alternative to the conventional signaling thus significantly improving the MTC performance. In particular, the contributions of our paper are (i) a novel integrated simulation-analytical framework for evaluating MTC data access mechanisms; and (ii) an efficient MTC-specific data access scheme, which we name contentionbased LTE transmission (COBALT). Below we continue with reviewing the conventional LTE data channels and detailing the proposed COBALT scheme. II. R EVIEW OF LTE SIGNALING PROCEDURES A. Summary of LTE data access channels 3GPP LTE is a relatively novel wireless technology, which is now mature enough to enable ubiquitous cellular connectivity. Currently, the LTE system defines the smallest physical resource element and, depending on the configuration, 72 or 84 of them are combined into a single Resource Block (RB). In the uplink, one RB includes 12 subcarriers in the frequency domain and 6 or 7 SC-FDMA symbols in the time domain. In this research, we limit our investigation to a popular configuration of 5 MHz bandwidth with 25 RBs in frequency (see Figure 1). In the time domain, an RB is 0.5 ms in length, while an RB-pair (2 adjacent RBs) is forming a subframe of 1 ms and is the smallest schedulable unit. Ten subframes compose a radio frame of 10 ms. In Figure 1, the frame resources are split between the three channels described below.

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Fig. 1.

1 3 5 7

t

After sending its SR, the device needs to wait until the eNodeB (base station) answers it with a corresponding scheduling grant (see Figure 2, left and Figure 3). The main benefit of the SR transmission via PUCCH is very high reliability and nearly deterministic data delay values. However, when the number of devices is large, the PUCCH resources may quickly deteriorate.

4 RBs in every subframe

6 RB-pairs th every 5 subframe

25 RB-pairs per subframe

2 4 6

PUCCH format 1 PRACH configuration 6 PUSCH for COBALT

7 5 3 1

Subframe 1

f

PUSCH for other signaling

6 4 2

Subframe 6

18 SRs in RB

Distribution of resource blocks across data access channels.

Device # 1

The Physical Uplink Control Channel (PUCCH) is dedicated to carry the uplink control information including (i) channel quality information for adaptive control of modulation and coding schemes (MCSs) and power, (ii) Scheduling Requests (SRs) to demand system resources, (iii) indicators for MIMO control, and (iv) Hybrid Automatic Repeat reQuests (HARQ) feedback. Out of several PUCCH configurations, we are only interested in type 1 used for SR transmission (see Figure 2, left). UE

Delay SG Rx + processing

Scheduling grant (SG)

Data transmission

Response window + backoff window

RAR Rx + processing

Scheduling opportunity

Fig. 2.

Ramping failure Ramping failure Msg1: Preamble Collision Msg1: Preamble retransmission

Delay

Scheduling opportunity

Scheduling request

eNodeB

Traffic arrival Periodicity

Traffic arrival

UE

eNodeB

Msg2: Random access response (RAR) Msg3: Layer 3 message Msg4: Contention resolution identity

2

SR

B. Conventional data access in LTE The default mechanism to allocate a part of PUSCH resource for uplink (UL) data transmission is based on prior SR transmission. In case a device already has uplink time alignment and a dedicated PUCCH allocation, it may use this allocation for sending its SR (see Figure 2, left), otherwise, PRACH will be used (see Figure 2, right). The periodicity of PUCCH RB availability for the SR transmission depends on SR configuration index and may vary from 1 to 80 ms (subframes). Moreover, several SRs from different devices can be aggregated into a single PUCCH RB and in our research we assume that up to 18 requests may be multiplexed [10].

Data 1-2 Tx

4

Data 3-5 Tx

5 SR

T0 SG

T Energy consumption of # 1

P P3 P2 P1 P0

Fig. 3.

SR Uplink

SG

Downlink

Energy consumption of # 5

Example PUCCH time diagram.

When the PUCCH resource becomes insufficient to support every active device in a particular cell, another RB pair can be allocated or SR periodicity may be lengthened. In either case, SR transmission via PUCCH is expected to consume much system resources when the device population is growing. In the extreme, the PUCCH resources may become depleted even for longer periods and higher RB multiplexing orders. As mentioned earlier, an alternative method for SR transmission is the Random Access (RA) procedure over the PRACH. Consequently, a device starts (see Figure 2, right and Figure 4) by sending one of 54 preambles (Msg1). Further, if a preamble is transmitted successfully the eNodeB answers with a Random Access Response (RAR, Msg2) where it indicates the resource to transmit Msg3. Finally, the device is expecting the response to its Msg3 within a Msg4 [4].

PUCCH (left) and PRACH (right) example signaling.

The Physical Random Access Channel (PRACH) is used by a device for SR transmission instead of PUCCH in case of initial network entry, as well as whenever the device does not have PUCCH resources allocated. Generally, a device selects a pseudo-random preamble and transmits it in the contentionbased mode to later access the network with its uplink data (see Figure 2, right). The Physical Uplink Shared Channel (PUSCH) is occupied by actual data transmissions and partly by control messages. Typically, PUSCH incorporates the remaining RBs not currently in use by PUCCH or PRACH. Depending on the channel conditions, different MCSs can be used for the data transmission. Consequently, the number of bits carried by a single PUSCH RB-pair varies between 16 and 712 [9].

Delay 2 Delay 1

3

Device # 1 2

P P3 P2 P1 P0

3 456

6 7 Preamble Tx opportunity

8

Delay 8* Delay 6* Delay 1* 78 Preamble Tx 9

10

Energy consumption of # 2

Fig. 4.

1

2

3

Delay 2* Backoff window

Preamble Tx

Waiting window 4 5 6 7 Radio frame 1

6 4

8

7 3

8

9

10

1

2

3

5 2

4

5

Uplink Downlink

Example PRACH time diagram.

By contrast to PUCCH, the PRACH transmission is unreliable and may be unsuccessful not only when sending Msg1 (due to collision or insufficient transmit power), but also due to problems in the transmission or reception of the later messages required to finalize the procedure. All failures during the RA procedure lead to restarting it after a random time. Upon a restart, the backoff timer is chosen uniformly within the backoff window size of 20 ms [4]. Despite its limited reliability, the main advantage of the PRACH procedure is that it consumes a fixed amount of RBs. For example, one PRACH allocation may occupy exactly 6 RB-pairs per subframe (see Figure 1 and [4]) and the devices may attempt to transmit their preambles only in subframes 1 and 6. However, with the increasing number of devices or their traffic arrival frequencies, the collision probability may become high, as well as access delay and power consumption due to retransmissions. Additionally, the extensive use of PRACH for the data access may block other MTC or H2H users performing initial network entry. Therefore, below we propose an alternative data access scheme for MTC devices.

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C. Proposed contention-based access for MTC

III. E VALUATION METHODOLOGY

The main idea behind the proposed contention-based LTE transmission (COBALT) is sending the small data packets directly over PUSCH instead of spending time and power on extra PUCCH/PRACH signaling. The idea itself has originally been proposed by [11] in the context of latency reduction in LTE. In this work, however, we tailor the COBALT mechanism to the MTC scenario when the devices are many and the traffic is infrequent and small. We expect that in these extreme conditions the proposed scheme would allow for lower network access delays and, more importantly, reduced signaling and power consumption of small-scale battery-powered MTC devices. For the sake of a fair comparison, we have decided to reuse the PRACH-related timings where appropriate in order to contrast the proposed scheme against PRACH in similar conditions. The overall COBALT procedure is summarized in Figure 5. Initially, the eNodeB is expected to broadcast a specific control message to all the associated devices indicating where and how many RBs are available for the proposed contention-based transmission. Generally, such messages may be periodic or on-demand depending on the system dynamics, but we simplify our investigation to the static scenario where the number of RBs available for the COBALT per subframe is constant.

Fig. 5.

Proposed contention-based LTE transmission (COBALT) signaling.

When using the RBs allocated for COBALT, two or more devices may send their data in the same RB. Consequently, a collision occurs and the acknowledgment from eNodeB is not received. In this case, the collided devices initiate the backoff procedure (the PRACH-specific random-access procedure is assumed here) and then retransmit their data. When the acknowledgment is received successfully after some fixed time offset, the COBALT procedure is ended (see Figure 6). We emphasize again, that with the proposed contentionbased data access only the PUSCH resource is used. Consequently, the main parameters during the COBALT operation are (i) the number of available PUSCH RBs per subframe (we assume the minimum feasible amount of 4 RBs or 2 RBpairs) and (ii) the periodicity of such availability (we assume the smallest period of 1 subframe). The backoff window size, as well as the associated timings, are considered similar to the PRACH procedure. Device # 1

P3 P2 P1 P0

2 Collision 1,2

Response window

1: RB # 1 2: RB # 1

Delay 1

Delay 3

Delay 2

3 Data 1, 3 Tx Backoff 2 Backoff 1 1: RB # 1 3: RB # 2

Data 2 Tx

Uplink

Processing 1,3

Processing 2 Energy consumption of # 1

Fig. 6.

Example COBALT time diagram.

A. Simulation paradigm and simulator capabilities The three considered data access schemes are studied via protocol-level simulations, as well as by analytical modeling. For the purpose of conducting extensive evaluations, we develop our own simulator based on the simulator used earlier in [8]. The main property of our tool is its flexibility in the choice of the parameters of interest, including number of devices, signaling timings, processing mechanisms, and system settings. Recently, 3GPP has released a comprehensive evaluation methodology [4] for LTE PRACH performance evaluation. The motivation behind this document was to identify the parameters of a verification scenario, as well as to present calibration data providing a baseline for various 3GPP member companies. In our previous work [8], we started a novel PRACH simulator building on the calibrated baseline and conducted thorough evaluations of the RACH performance under the MTC overload. The current version of that tool has considerably extended functionality, adding PUCCH and COBALT implementations, as well as many important features summarized below. B. System model and assumptions Addressing the performance of the data access mechanisms under comparison, we consider M identical MTC devices deployed within a cell of 3GPP LTE Frequency Division Duplex (FDD) system [4]. Specifically, we focus on 1000 (1K), 5000 (5K), and 10000 (10K) devices. All the devices are present in the system throughout the entire simulation duration and the metrics of interest are collected over that total time. This work focuses on the reference MTC UL traffic model in accordance with the recent 3GPP technical report [12], as the methodology in [4] defines only overloaded network entry patterns leaving open the actual device traffic model. The document [12] suggests that the packet inter-arrival time distribution is exponential with the constant mean value of 30 seconds. The data packets of 256 bits are transmitted at the fixed MCS level of 16-QAM to take exactly one RB-pair [9] (1 subframe in the time domain) over the 5 MHz band. The data arrival flow thus constitutes a stationary, memoryless Poisson process, representing the number of packet arrivals occurred by an arbitrary time moment t. Given the properties of this process, the probability p0 that the number of arrivals within a slot of length t0 equals 0, is given by: p0 = Pr{X(t, t + t0 ) = 0} = e−λt0 ,

(1)

where X(t, t + t0 ) is the number of arrivals over the time interval [t, t + t0 ) and λ is the arrival flow rate. The PUCCH and PRACH implementations closely follow the respective 3GPP reference documents. In particular, PUCCH is based on the timing values from Table B.1.2.1.1-1 of [13], while PRACH timings are taken from Table B.1.1.11 of [13] and from [4]. Some ideas on COBALT have been discussed in [11]. Important evaluation parameters are summarized in Table I.

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TABLE I C ORE SYSTEM PARAMETERS Notation λ t0 M s L1 W 1-ptx L3 b K K0 tpr ttx T0 T

Parameter Arrival flow rate for an MTC device Subframe size Number of MTC devices Total number of preambles/COBALT RBs Max. number of preamble/data attempts PRACH/COBALT backoff indicator HARQ retransmission probability for Msg3 and Msg4 (non-adaptive HARQ) Max. number of HARQ Tx for Msg3 and Msg4 (non-adaptive HARQ) Periodicity of PRACH opportunities PRACH/COBALT response window Period of Tx and pausing (PRACH/COBALT) Processing time before Msg3 Tx/ COBALT Ack decoding and processing Time of Msg3 Tx, waiting, and Msg4 Rx PUCCH procedure duration PUCCH SR periodicity

Value 1/30 s−1 1 ms 1K, 5K, 10K 54/4 10/4 20 ms 10% 5 5 ms 5/1 ms 3 ms 5/3 ms 6 ms 8 ms 10 ms

ALOHA protocols. As such, we had to adopt the equivalent memoryless models for both schemes. Owing to a large number of available preambles in PRACH, taking into account all the transitions between the system states is unnecessarily complicated. Therefore, we study the PRACH-based data access from the point of view of a particular backlogged MTC device and its contention behavior by abstracting away most transitions through averaging. The obtained approximation is generally suitable for the low system loads, as long as the collision probability remains sufficiently small. By contrast, the probability of collision during the COBALT-based access is higher due to more efficient resource utilization. Hence, in order to provide a better solution, we consider all possible transitions between the system states and analyze the steady-state distribution.

Our MTC device energy model is based on four different B. Analysis of PUCCH-based data access power states (see Figures 3, 4, and 6) with the power consumpThe PUCCH-based transmission is not susceptible to collition values of a possible future MTC device taken from [14]. sions and does not include backoff periods. The data packet We differentiate between (i) the idle state (P0 = 0.01 mW) transmission time is assumed to take 1 subframe. We thus when the traffic buffer is empty and there is no data to transmit, calculate the mean packet delay as follows: (ii) the fine clock state (P1 = 10 mW) when the traffic has E[τ ] = T /2 + T0 + 1, (2) arrived, but the device does not transmit it currently waiting where T is the PUCCH procedure duration (see Figure 3), T 0 for a transmission opportunity, (iii) the reception (Rx) state is the SR periodicity, and 1 stands for the transmission time. (P2 = 100 mW) when the device is listening for the eNodeB To estimate the power consumption, we obtain the time transmissions and processing the acknowledgments, and (iv) fraction that a device spends in every state: the transmission (Tx) state (P3 = 300 mW) when the device q1 = (T /2 + 3) · λ, q2 = (T0 − 3) · λ, q3 = 2 · λ. (3) is transmitting its preambles/data. The total amount of energy spent by the device may thus Importantly, the actual power consumption figures in every be derived from the expressions above as follows: state may depend on specific implementation and we consider (4)  =P2 q2 +P3 q3 +P1 q1 +P0 (1−q3 −q2 −q1). this model only to give a comprehensive example. To indicate the potential for improving the real-world device implemen- C. Analysis of PRACH-based data access tations, below we consider the optimal power consumption in We describe the PRACH system reusing the approach from the sense that a device can immediately fall back to the fine our previous work [8] considering contention-based transmisclock state, i.e., it does not have to listen to the downlink sion of s preambles and data from M MTC devices activating activity in every subframe. In other words, we ideally assume according to the arrival process described above. that the device is aware of when the feedback is coming from The overall delay in such system can be decomposed into the eNodeB and may adjust its power level accordingly. two separate components: E[τ ] = E[τ (1) ] + E[τ (2) ]. (5) Below we continue by studying the primary performance (1) ] is the approximate mean time before Msg3 Here, E[τ metrics with both analysis and simulation. We focus on the as: consumption of RBs (including the number of RBs allocated processing and can be obtained  M −j M −1 j−1 M  (1 − ρ) by the system for either data access mechanism and the j−1 ρ (1)   , (6) number of actually used RBs), the MTC device power con- E[τ ] = (1−e−λt0)+ aj (K +K0 + w)+ ¯ b−K ¯ −1 2 −w j=1 sumption, and the data access delay values (defined as the time where w ¯ = c2 (c2 + 1) + (c2 + b + bc3 )(W − bc3 − c2 ) + bc3 c2 , between the data arrival and its successful UL transmission). c1 ∼ = 1.42, c2 = b (K +K0 )/b−K−K0 , c3 = (W − c2 )/b, and other parameters are given below. IV. A NALYTICAL BENCHMARKING Variables p∗j , aj , and the approximate device load ρ can be calculated as follows: A. General remarks     p∗j = 1−s−1 (K0 +K + w) ¯ −1 j−1 1−(1−e−λt0 )s−1 M −j, (7) The below analysis of the three data access schemes has  n−1  L1  1  1 been conducted with three different approaches. Whereas the ∗ n 1− n (1 − p∗j (1 − i )), (8) aj = pj e e evaluation of the PUCCH-based mechanism is close to trivial, n=1 i=1 b−K the analysis of the contention-based schemes (PRACH and ¯ + ρ = (1 − e−λt0 )(c1 (K + K0 + w) − w), ¯ (9) 2 COBALT) is much more challenging. Due to the inherent memory of the contention process, addressing it straightfor- where M , L1 , and s are the parameters as per Table I. wardly has not been successful before even for much simpler The mean time of Msg3 and Msg4 Tx E[τ (2) ] is given by:

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ttx  1 − (1 − ptx )L3 (1 + L3 ptx ) . (10) ptx Regarding device power consumption in PRACH, the PUCCH-specific approach may be modified accordingly without any significant difficulty. E[τ (2) ] = tpr +

Using the steady-state distribution Ω = {ωi }M i=0 of the process we find the mean number of backlogged devices and the steady-state success rate as: Sout =

We consider the transmission phase when a device detects a contention-based grant, performs L2 and L1 processing of the data to be transmitted, and transmits its data on PUSCH. We assume that COBALT grant can be received in every slot. Note that COBALT operation does not feature the power ramping procedure. We assume a collision when two or more MTC devices choose the same COBALT grant and transmit their data over PUSCH. All the collided transmissions are considered failed. If a transmission fails, the MTC device uniformly selects a backoff counter within [0, W −1]. If the device transmits successfully, it flushes its packet buffer. Firstly, we obtain an approximation of the mean data access delay. In order to establish an estimate for the delay in the system with memory, we adopt the following simplified equivalent model. We assume that every backlogged device attempts its transmission in each subframe with the probability 1 p = K0+K+(W+1)/2 , while the probability of obtaining at least one new packet equals σ = 1−p0 and p0 is given by (1). Let N (t) be a random process representing the total number of backlogged devices in the system at time t. In our case, N (t) is the Markovian process with the state space {0, 1, .., M }. The elements of transition matrix Π = {πij }M i,j=0 for the discussed Markov chain is given in the Table II.

i+1 i+2 i+z

2

The expected channel success rate in the state i, Sout (i), is calculated as: Sout (i) = (1−p)i (M−i)σ(1−σ)M−i−1 +ip(1−p)i−1 (1−σ)M−i +     M −i i   i z k+z i−z i p (1−p) σ z (1−σ)i−z + + k+z−1 z z 2 z=0 k=min(0,3−z)   M−i−1 i−1 M−i i p2 (1−p)i−2 + (M −i)σ(1−σ) ip(1−p) +(1−σ) 2   M −i 2 σ (1−σ)M −i−2 (1 − p)i . (11) + 2

iωi .

(12)

i=0

V. C OMPARISON OF DATA ACCESS SCHEMES In this section, we compare the proposed COBALT scheme against the conventional LTE data access mechanisms over PUCCH and PRACH. The results herein are based on protocol-level simulations (at least 100 minutes of LTE time per a simulation run) and have been confirmed by the analytical findings of Section IV. We begin with evaluating the number of resource blocks allocated by the system for either data access channel and also give the number of RBs actually used by the MTC devices in Table III. For PUCCHbased access, the network should allocate an excess amount of RBs to support the growing MTC population, whereas the efficiency of RB usage remains extremely low due to the infrequent nature of the considered MTC traffic. Importantly, when the number of MTC devices is very large, the system will not be able to support all devices with the chosen parameter settings due to the prohibitive levels of overhead. In particular, for a 5 MHz bandwidth, the RB numbers needed to support 5K or 10K devices are higher than what is available in a subframe. TABLE III C OMPARISON OF RB CONSUMPTION RB usage per subframe [allocated : used] PUCCH PRACH COBALT

Value 0   2 M−i i i−2 1 , 2 p (1−p) 2 (1 − σ) M−i−1 i−1 1 (M − i)σ(1 −σ) ip(1−p) + 2 

i k i−k k +(1 − σ)M −i [ip(1 − p)i−1 + ik=3 k−1 ] k p (1 − p) 2  M −i 2 M−i−2 i M−i−1 i (1−σ) (1−p) +(M −i)σ(1 −σ) [(1−p) + σ 2    i k

+ ik=2 k+1 p (1 − p)i−k ]+(1−σ)M−i [ 2i p2 (1−p)i−2+ 2k   k2  

i i 1 i i−2 k +(1−p) + 2 2 p (1−p) + k=3 (1− k−1 ) ki pk (1−p)i−k ] 2  M −i 2 

i k σ (1−σ)M−i−2 ik=1 k+2 p)i−k ]+ k+1 k p (1 − 2 2

  (M−i)σ(1−σ)M−i−1[ 12 ip(1−p)i−1+ ik=2(1− k+k1) ki pk(1−p)i−k] 2    M −i 2

+2 ) ki pk (1−p)i−k ] σ (1−σ)M−i−2[ 12 (1 −p)i+ i k=1(1− k 2k+1 2M −i

i k k+z M−i−z i i−k σ(1 −σ) ] k=0 (1− k+z−1 ) k p (1 − p) z

M 

The average access delay in the system is then given by: E[τ ] = tpr + K0 + K + n ¯ /Sout + 1/2. (13) The power consumption can again be obtained by modifying the expressions for PUCCH.

TABLE II T RANSITION PROBABILITIES πij = Pr{N (t) = j|N (t − 1) = i}

i

Sout (i)ωi , n ¯=

i=0

D. Analysis of COBALT-based data access

j i−z i−2 i−1

M 

1K

5K

10K

12 : 0.0036 2.4 : 0.50 4 : 0.07

56 : 0.018 2.4 : 1.66 4 : 0.34

112 : 0.036 2.4 : 2.18 4 : 0.73

By contrast, the PRACH-based data access takes advantage of a fixed RB allocation with much higher usage efficiency. Note, however, that PRACH-related figures in Table III are the best estimate, as in reality Msg3 transmissions would also consume some PUSCH capacity. Furthermore, increasing PRACH load results in the growing number of preamble collisions. This may jeopardize H2H users which might then suffer from excessive network entry delays unless preventive measures are put in place. Our proposed COBALT scheme is expected to relieve PRACH congestion and allow the MTC devices to enjoy higher network access probabilities while at the same time protecting the H2H communications. In Table III, we see that even with the minimal feasible number of RBs allocated for COBALT, the LTE network has no difficulty supporting a very large population of MTC devices. We continue by an assessment of the power consumption of the COBALT small data access mechanism. From Figure 7, we learn that COBALT power consumption is significantly lower than the energy expenditure of the PRACH-based scheme, especially at lower loads. More interestingly, the COBALT

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Fig. 7.

    !"   Power consumption for different access schemes.

energy performance is even slightly better than that of the PUCCH-based access which is contention-free and, therefore, extremely power efficient. This is due to the reduced number of signaling messages transmitted/received by an MTC device when sending small infrequent data with COBALT. Additionally, we emphasize that the power consumption growth for the increasing MTC population is minimal, which is due to a very low collision probability. This indicates the considerable potential of the COBALT mechanism with respect to supporting small data MTC deployments. 

  

    



 Fig. 8.

   

    Data access delay CDF.



Finally, we also investigate the data access delay of all the three alternatives under study (see Figure 8 and Table IV) to conclude that COBALT-based data access results in significantly lower packet latency values. Even though the most MTC traffic is foreseen to be delay-tolerant, there may still be situations where latency becomes critical for ensuring the desired quality of user experience (e.g., alarm messaging and vehicular applications) and our COBALT scheme improves over the PUCCH latency for around 85% of the cases. TABLE IV C OMPARISON OF MEAN ACCESS DELAY Mean access delay, ms [simulation : analysis] PUCCH PRACH COBALT

1K

5K

10K

14.00 : 14.00 29.08 : 29.13 7.72 : 7.74

14.00 : 14.00 29.48 : 29.26 8.81 : 8.81

14.00 : 14.00 29.95 : 29.50 10.51 : 10.38

VI. C ONCLUSION Summarizing, in this work we have reviewed the conventional data access mechanisms which may be used by 3GPP LTE devices to transmit their data. We emphasized that neither the default PUCCH-based scheme, nor the alternative PRACH-based scheme is optimal for supporting massive MTC deployments where the traffic arrivals are infrequent and small. To mitigate the anticipated performance degradation, we have proposed a novel contention-based LTE transmission mechanism, which we termed COBALT. Our scheme takes advantage of the simple implementation and thus fewer number of LTE signaling messages. Consequently, it demonstrates significantly better usage of network resources, lower power consumption for the MTC devices, and often reduced latency performance. Conducted protocol-level evaluations, with both simulation and analysis, confirm that the proposed contention-based mechanism has the potential of improving small data access across the increasing number of MTC-based LTE applications. Our future intention is to continue demonstrating the benefits of the proposed approach when accounting for the coexistence of the MTC and the H2H users, as well as to detail the optimal COBALT implementation within the LTE signaling and the realistic device power saving operation. ACKNOWLEDGMENT This research was conducted within the Internet of Things program of Tivit (Finnish Strategic Centre for Science, Technology and Innovation in the field of ICT), funded by Tekes. R EFERENCES [1] Machine-Type and other Mobile Data Applications Communications Enhancements. 3GPP Technical Report (TR) 23.887, August 2012. [2] K. Zheng, F. Hu, W. Wang, W. Xiang, and M. Dohler, “Radio resource allocation in LTE-Advanced cellular networks with M2M communications,” IEEE Commun. Mag., vol. 50, pp. 184–192, July 2012. [3] S. Andreev, O. Galinina, and Y. Koucheryavy, “Energy-efficient client relay scheme for machine-to-machine communication,” in Proc. of the 54th IEEE Global Communications Conference (GLOBECOM), 2011. [4] Study on RAN Improvements for Machine-Type Communications. 3GPP Technical Report (TR) 37.868, September 2011. [5] D. Niyato, L. Xiao, and P. Wang, “Machine-to-machine communications for home energy management system in smart grid,” IEEE Commun. Mag., vol. 49, pp. 53–59, April 2011. [6] S.-Y. Lien, T.-H. Liau, C.-Y. Kao, and K.-C. Chen, “Cooperative access class barring for machine-to-machine communications,” IEEE Trans. Wireless Commun., vol. 11, pp. 27–32, January 2012. [7] M.-Y. Cheng, G.-Y. Lin, H.-Y. Wei, and A. Hsu, “Overload control for machine-type-communications in LTE-Advanced system,” IEEE Commun. Mag., vol. 50, pp. 38–45, June 2012. [8] M. Gerasimenko, V. Petrov, O. Galinina, S. Andreev, and Y. Koucheryavy, “Energy and delay analysis of LTE-Advanced RACH performance under MTC overload,” in 2nd IEEE IWM2M Workshop at GLOBECOM, 2012. [9] Physical layer procedures. 3GPP Technical Specification (TS) 36.213, June 2012. [10] LTE Radio Access Network (RAN) enhancements for diverse data applications. 3GPP Technical Report (TR) 36.822, September 2012. [11] Ericsson, R2-096759, Details of Latency Reduction Alternatives. [12] Study on provision of low-cost MTC UEs based on LTE. 3GPP Technical Report (TR) 36.888, June 2012. [13] Feasibility study for Further Advancements for E-UTRA (LTEAdvanced). 3GPP Technical Report (TR) 36.912, September 2012. [14] T. Tirronen, A. Larmo, J. Sachs, B. Lindoff, and N. Wiberg, “Reducing energy consumption of LTE devices for machine-to-machine communication,” in 2nd IEEE IWM2M Workshop at GLOBECOM, 2012.

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