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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, ?Ericsson Research

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. INTRODUCTION 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

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 the 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.REVIEW 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.

	2	1				t
	4	3
subframe	6	5
		7		sh	e	4 RBs in every
				rt
				i 5 m
				a	a	subframe
			6	p y r
				- r f
				B e b
				v u
				R		PUCCH format 1
per				e s
						PRACH
RB-pairs
						configuration 6
						PUSCH for
						COBALT
25	7	6				PUSCH for
	5					other signaling
	3	4
	1	2
	Subframe 1		18 SRs in RB			Subframe 6
	f
Fig. 1. Distribution of resource blocks across data access channels.

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	eNodeB
	Traffic	Scheduling opportunity
	arrival	Periodicity
	Delay	Scheduling request
		Scheduling grant (SG)
	SG Rx
	+
	proces-
	sing	Data transmission
		Scheduling opportunity

	UE	eNodeB
	Traffic
	arrival
	Response	Ramping failure
		Ramping failure
	window +
	backoff	Msg1: Preamble
	window	Collision
	Delay	Msg1: Preamble
		retransmission
	RAR Rx	Msg2: Random access
		response (RAR)
	+
	proces-	Msg3: Layer 3 message
	sing
		Msg4: Contention
		resolution identity

Fig. 2. 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 vary between 16 and 712 [9].

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 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].

After sending its SR, the device needs to wait until the eNodeB (base station) answers it with a corresponding scheduling grant (see 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.

Delay 2

Delay 1

Data 1-2

5

Data 3-5

Device #1

2

3

4

Tx

SR

SR

Tx

SR

T0

Uplink

SG

SG

P

T

Energy consumption of # 5

Downlink

P3

Energy consumption of # 1

P2

P1

P0

Fig. 3. 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 increased. 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 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].

															Delay 8*
												Delay			6*
																			Delay 2*
									Delay 1*															Backoff window
Device #1 2			3		456		78			Preamble								Waiting window											Preamble
												Tx																		Tx
6			7		8		9			10	1			2		3	4	5	6	7		8	9	10	1	2	3	4	5	Uplink
	Preamble Tx																Radio frame

P	opportunity	1	6	8	7	5	Downlink
P3	Energy consumption of # 2		4		3	2
P2
P1
P0

Fig. 4. 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 will 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 RBs 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.

C. Proposed contention-based access for MTC

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 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 batterypowered 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.

Delay 3

Response

Delay 1

Delay 2

Collision

3

Data 1, 3

Device #

1

2

Data

2

Uplink

window

1,2

Backoff

2

Tx

Tx

Backoff 1

1: RB # 1

1: RB # 1

Processing

Processing

P3

2: RB # 1

3: RB # 2

1,3

2

P2

Energy consumption of # 1

P1

P0

Fig. 6. Example COBALT time diagram.

III.EVALUATION METHODOLOGY

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 taking advantage of extensible modular structure for improved scalability. 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 comprehensive PRACH simulator building on the calibrated baseline and conducted thorough evaluations of the RACH performance under MTC overload. The current version of the 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.1.1.1- 1 of [13] and from [4]. Some ideas on COBALT have been discussed in [11]. Important evaluation parameters are summarized in Table I.

TABLE I

CORE SIMULATION PARAMETERS

Notation	Parameter	Value
λ	Arrival flow rate for an MTC device	1/30 s−1
t0	Subframe size	1 ms
M	Number of MTC devices	1K, 5K, 10K
s	Total number of preambles/COBALT RBs	54/4
L1	Max. number of preamble/data attempts	10/4
W	PRACH/COBALT backoff indicator	20 ms
1-ptx	HARQ retransmission probability for	10%
	Msg3 and Msg4 (non-adaptive HARQ)
L3	Max. number of HARQ Tx for	5
	Msg3 and Msg4 (non-adaptive HARQ)
b	Periodicity of PRACH opportunities	5 ms
K	PRACH/COBALT response window	5/1 ms
K0	Period of Tx and pausing (PRACH/COBALT)	3 ms
tpr	Processing time before Msg3 Tx/	5/3 ms
	COBALT Ack decoding and processing
ttx	Time of Msg3 Tx, waiting, Msg4 Rx	6 ms
T0	PUCCH procedure duration	8 ms
T	PUCCH SR periodicity	10 ms

Our MTC device energy model is based on four different power states (see Figures 3, 4, and 6) with the power consumption values of a possible future MTC device taken from [14]. We differentiate between (i) the idle state (P0 = 0.01 mW) when the traffic buffer is empty and there is no data to transmit, (ii) the fine clock state (P1 = 10 mW) when the traffic has arrived, but the device does transmit it currently (e.g., backoff time), (iii) the reception (Rx) state (P2 = 100 mW) when the device is listening for the eNodeB transmissions and processing the acknowledgments, and (iv) the transmission (Tx) state (P3 = 300 mW) when the device is transmitting preambles/data.

Note that the current split between the inactive and the idle states is due to the fact that the device needs to use the finer clock when it is waiting for a transmission opportunity. Importantly, the actual power consumption figures in every state may depend on specific implementation and we consider this model only to give a comprehensive example. To indicate potential for improving real-world device implementations, below we consider the optimal power consumption in the sense that a device can immediately fall back to the fine clock state, i.e., it does not have to listen to the downlink activity in every subframe. In other words, we ideally assume that the device is aware of when the feedback is coming from the eNodeB and may adjust its power level immediately.

Below we continue by studying the primary performance metrics, with analysis and then by simulation. We focus on the consumption of RBs (including the number of RBs allocated by the system for either data access mechanism and the number of actually used RBs), the MTC device power consumption, and the data access delay values (defined as the time between the data arrival and its successful UL transmission).

IV. ANALYTICAL BENCHMARKING

A. General remarks

The below analysis of the three considered data access schemes has been conducted with three different approaches. Whereas the evaluation of the PUCCH-based mechanism is close to trivial, the analysis of the contention-based schemes

(PRACH and COBALT) is much more challenging. This is due to the inherent memory of the contention process, and addressing it straightforwardly has not been successful before even for much simpler ALOHA protocols. As such, we had to adopt the equivalent memoryless models for the both schemes.

Due 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 number of collisions during the COBALT-based access is higher due to higher resource utilization. Hence, in order to give a better solution, we consider all possible transitions between the system states and analyze the steady-state distribution.

B. Analysis of PUCCH-based data access

The PUCCH-based transmission is not susceptible to collisions and does not include backoff periods. The packet transmission time is assumed to take 1 subframe. We thus

calculate the mean packet delay as follows:
E[τ] = T/2 + T0 + 1,	(2)

where T0 is the eNodeB response time, T is the system polling cycle, and 1 stands for the transmission time.

To estimate the power consumption, we obtain the time

fraction that a	device spends in every state:
q1 = (T/2	+ 3) · λ, qT X = 2 · λ, q2 = (T0 − 3) · λ. (3)

The total amount of energy spent by the device may thus be derived from the expressions above as follows:

=P2q2 +P3q3 +P1q1 +P0(t−q2 −q3 −q1). (4)

C. Analysis of PRACH-based data access

We describe the PRACH system in terms of assumptions given in our previous work [8] considering contention-based transmission of s preambles and data from M MTC devices activating according to the arrival process described above.

The overall delay in the system can be decomposed into

two separate parts:

(5)

E[τ] = E[τ(1)] + E[τ(2)].

Here, E[τ(1)] is the approximate mean time before Msg3

processing and can be obtained as:

M

M−1 ρj−1

(1

−

ρ)M−j

E[τ(1)]=

j−1

w¯

, (6)

=1(1

λt0)+ a (K +K

+w¯)+ b K

−

1

−

e−

j

0

−2

−

Xj

where w¯ = c2(c2 + 1) + (c2 + b + bc3)(W − bc3 − c2) + bc3c2,

c1 1.42, c2 =b d(K +K0)/be−K−K0, c3 = b(W − c2)/bc

=

and other parameters are given below.

Variables pj , aj, and the approximate traffic source load ρ

have to be calculated as follows:

p = 1

−

s−1

(K +K +w¯)−1 j−1

1 (1

−

e−λt0 )s−1 M−j,

j

0 L1

1

n−−1

1

(7)

aj = pj n=1 n

1 − en

(1 − pj (1 − ei )),

(8)

X

Y

i=1

ρ = (1	−	e−λt0 )(c (K + K		+ w¯) +	b − K	−	w¯), (9)
		1	0	2

where M, L1, and s are the primary PRACH parameters as per Table I.

The mean service time of Msg3 and Msg4 Tx E[τ(2)] is given by:

E[τ(2)] = tpr + ttx 1 − (1 − ptx)L3 (1 + L3ptx) . (10)

ptx

Regarding device power consumption in PRACH, the PUCCH-specific approach may be modified accordingly without any significant difficulty.

D. Analysis of COBALT-based data access

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 ramping procedure.

We assume a collision when two or more MTC devices detect the same COBALT grant and transmit their data over PUSCH. All the collided data transmissions are considered failed. If a transmission fails, the MTC device uniformly selects a backoff counter in [0, W−1]. If the device transmits successfully, it flushes its packet buffer.

Firstly, we obtain an approximation of the mean network entry delay. In order to establish an estimate for the delay in the system with memory due to deterministic constants in service, we adopt the following simplified equivalent model. We assume that every backlogged device attempts its transmis-

1
sion in every subframe with the probability p=		,
	K0+K+(W+1)/2

while the probability of receiving at least one packet equals σ =1−p0 and p0 is given by (1).

Let N(t) be a random process representing the total number of backlogged users in the system at t. In our case, N(t) is

the Markovian process with the state space

{

0, 1, .., M

}

. The

M

elements of transition matrix Π = {πij}i,j=0 for the discussed

Markov chain is given in the Table II.

TABLE II

TRANSITION PROBABILITIES πij

= Pr{N(t) = j|N(t − 1) = i}

j

Value

i z

0

−

21 (1 − σ)M−i

i

p2(1−p)i−2,

i−2

2

i 1

1

(M

i)σ(1

M−i−1

ip(1

p)

i−1

+

2

−

−

σ)

−

i

−

M−i

i

k

i−k

+(1 − σ)

− p)

i−1

k

(1 − p)

[ip(1

+

k=3

2k−1

k p

]

i

M−i

σ

2

(1

σ)

M−i−2

(1 p)

i

M i)σ(1

σ)M−i−1[(1 p)i+

2

−

+(P

−

−

−

−

+

i

k+1 i pk(1

p)i−k]+(1

σ)M−i[ i

p2(1

p)i−2+

k=2

2

k

k

−

−

2

−

i

i

2

2

i

i

k

i k

1

i

k

+(1Pp) + 2

2

p (1

−

p)

−

+

k=3(1

) k

p

(1

−

p)− ]

2k

1

−

−

−

i+1

M−i σ2(1 σ)M−i−2 i

k+2

i

pk(1 p)i−k]+

k+1

2

=1

k

−

2

−

(M i)σ(1 σ)M−i−1[

1 ip(1 p)i−1+

i =2(1 k+1k )

i

pk(1 p)i−k]

2

P

k

2

k

−

−

−

−

−

i+2

M−i

σ2(1 σ)M−i−2[ 1

(1

−

p)i+

ik=1(1

−

k+2

)

i

pk

(1

−

p)i−k]

2

−

2

P

2k+1

k

i+z

M−i

σ(1 σ)M−i−z i

(1

k+z

)

i

pk(1 p)i−k]

k+z

1

k

z

k=0

P

−

P

−

2

−

−

The expected channel throughput in the state i, Sout(i), is calculated as the probability to transmit exactly one packet plus doubled probability to transmit two packets:

Sout(i) = (1−p)i(M−i)σ(1−σ)M−i−1 +ip(1−p)i−1(1−σ)M−i+

i	M−i	k+z		i			i
+ z=0 k=min(0,3 z)				z pz(1−p)i−z z σz(1					−σ)i−z+
		2k+z−1
X	X −							i
(M−i)σ(1−σ)M−i−1ip(1−p)i−1+(1−σ)M−i 2 p2(1−p)i−2+
	+ M − i		σ2(1			σ)M−i−2(1		p)i.	(11)
		2			−		−

Using the steady-state distribution Ω = {ωi}Mi=0 of the process we find the mean number of backlogged users and

the steady-state throughput rate as:

M M

X	X
Sout = Sout(i)ωi, n¯ =	iωi.	(12)
i=0	i=0
The average delay in the system is then given by:
E[τ] = tpr + K0 + K + n/S¯	out + 1/2.	(13)

The power consumption can again be obtained modifying the expressions for PUCCH.

V. COMPARISON 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. For example, for a 5 MHz bandwidth, the RB numbers needed to support 5K or 10K users are higher than what is available in a subframe.

TABLE III

COMPARISON OF RB CONSUMPTION

RB usage per subframe		1K		5K	10K
[allocated : used]
PUCCH	12 :	0.0036	56	: 0.018	112 : 0.036
PRACH	2.4	: 0.50	2.4 : 1.66		2.4 : 2.18
COBALT	4 : 0.07		4	: 0.34	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 and thus may jeopardize H2H users which might then suffer from excessive network entry delay unless preventive mechanisms 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.

mW	0.14			PUCCH
				PRACH
consumption,	0.12			COBALT
				Theory
	0.1
	0.08
power	0.06
	0.04
Individual
	0.02
	0	1000	5000	10000
		Number of MTC devices

Fig. 7. Power consumption for different access schemes.

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 mechanism, especially at lower loads. More interestingly, the COBALT energy performance is even slightly better than that of the PUCCH-based scheme 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 load 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.

		1
	Probability	0.8
		0.6
		0.4

0.2				COBALT
				PRACH
00				PUCCH
	20	40	60	80	100
		Delay, ms

Fig. 8. Data access delay CDF.

Finally, we also investigate the data 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 PUCCH latency for around 85% of the cases.

TABLE IV

COMPARISON OF MEAN ACCESS DELAY

Mean access delay, ms	1K		5K		10K
[simulation : analysis]
PUCCH	14.00	: 14.00	14.00	: 14.00	14.00	: 14.00
PRACH	29.08	: 29.13	29.48	: 29.26	29.95	: 29.50
COBALT	7.72	: 7.74	8.81	: 8.81	10.51	: 10.38

VI. CONCLUSION

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.

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