1 Age of Information in Downlink Systems Broadcast or Unicast Transmission

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Age of Information in Downlink Systems:

Broadcast or Unicast Transmission?

Zhifeng Tang, Student Member, IEEE, Nan Yang, Senior Member, IEEE,

Parastoo Sadeghi, Senior Member, IEEE, and Xiangyun Zhou, Senior

Member, IEEE

Abstract

We analytically decide whether the broadcast transmission scheme or the unicast transmission

scheme achieves the optimal age of information (AoI) performance of a multiuser system where a base

station (BS) generates and transmits status updates to multiple user equipments (UEs). In the broadcast

transmission scheme, the status update for all UEs is jointly encoded into a packet for transmission,

while in the unicast transmission scheme, the status update for each UE is encoded individually and

transmitted by following the round robin policy. For both transmission schemes, we examine three

packet management strategies, namely the non-preemption strategy, the preemption in buffer strategy,

and the preemption in serving strategy. We ﬁrst derive new closed-form expressions for the average AoI

achieved by two transmission schemes with three packet management strategies. Based on them, we

compare the AoI performance of two transmission schemes in two systems, namely, the remote control

system and the dynamic system. Aided by simulation results, we verify our analysis and investigate the

impact of system parameters on the average AoI. For example, the unicast transmission scheme is more

appropriate for the system with a large number UEs. Otherwise, the broadcast transmission scheme is

more appropriate.

Index Terms

Age of information, multiuser system, short packet communications, packet management.

This work was supported by the Australian Research Council Discovery Project (DP180104062).

Z. Tang, N. Yang, and X. Zhou are with the School of Engineering, Australian National University, Canberra, ACT 2600,

Australia (Email: {zhifeng.tang, nan.yang, xiangyun.zhou}@anu.edu.au).

P. Sadeghi is with the School of Engineering and Information Technology, University of New South Wales, Canberra, ACT

2612, Australia (Email: p.sadeghi@unsw.edu.au).

arXiv:2210.15078v3 [cs.IT] 7 Jul 2023

I. INTRODUCTION

Real-time applications, such as intelligent transport systems and factory automation, have

recently attracted rapidly increasing interests from academia and industry. In these applications,

timely status update plays an indispensable role in accurate monitoring and control [1]–[4].

To reduce transmission latency in real-time applications, short packet communication has been

widely considered as a promising solution, due to its unique beneﬁts in delay reduction [5]–[8].

Moreover, in order to fully characterize the freshness of delivered status information, the concept

of age of information (AoI) has been introduced as a new and effective performance metric [9].

Speciﬁcally, the AoI is deﬁned as the elapsed time since the last successfully received status

update being generated by the transmitter, which is a time metric capturing both latency and

freshness of transmitted status information.

Since being introduced in [9], the concept of AoI has reaped a wide range of attention and

interests. The authors of [10] studied the average AoI in a ﬁrst-come-ﬁrst-served (FCFS) single-

user system. Different from [10], [11] proposed the last-come-ﬁrst-served (LCFS) queuing policy,

which was shown to achieve a lower average AoI than the FCFS queuing policy. Building

upon these efforts on the single-user system, increasing research efforts have been devoted to

investigating the AoI performance of multiuser systems. The authors of [12] extended [10] to

analyze the average AoI under the FCFS queuing policy in a multiuser system. By considering

the effect of unreliable channels on packet loss, [13] introduced a feedback mechanism to

deliver generated packets as timely as possible. Moreover, [14] examined the average AoI for

three different scheduling policies, i.e., round robin (RR), work-conserving non-collision, and

random access. The authors of [14] further pointed out that the RR policy is the optimal arrival-

independent scheduling policy to minimize the average AoI. By considering sporadic packet

generation rates of users, [15] proposed a random access based transmission scheme to improve

the average AoI performance. In addition, [16] designed a Whittle index based scheduling policy

to optimize the AoI performance while considering the effect of unreliable channels.

To improve the AoI performance, multiple packet management strategies were discussed, e.g.,

[17]–[21]. As an early study, [17] introduced two different packet management strategies for the

LCFS system, namely, the preemption strategy and the non-preemption strategy in a single-user

system. In the preemption strategy, when a new packet is generated at the source, it is allowed

to replace the current packet in service. In contrast, for the non-preemption strategy, the newly

generated packet has to wait for the current packet in service to be transmitted. The authors

of [18] extended [17] into a multiuser system and revealed the superiority of the preemption

strategy when the packet generation rate is large. A retransmission strategy was proposed in

[19], where the source keeps transmitting the most recent packet once the transmission is

completed. [19] further pointed out that the retransmission strategy signiﬁcantly reduces the

peak AoI (PAoI) when the transmission error rate is high. In [20], a hybrid automatic repeat

request (HARQ) protocol was employed such that several incremental redundancy bits are sent

when the receiver cannot successfully decode. Very recently, [21] introduced a packet dropping

strategy and demonstrated the beneﬁt of this strategy on decreasing the average AoI.

Motivated by the beneﬁts of short packet communications on latency reduction, the AoI perfor-

mance of short packet communications was analyzed to evaluate the impact of short packets on

the freshness of transmitted information, e.g., [22]–[27]. Speciﬁcally, [22] investigated the impact

of the packet blocklength on the delay and the PAoI in a single-user system. Considering the

same system, [23] extended [22] to analyze the probability of the peak-age violation exceeding

a threshold. Focusing on a decode-and-forward relaying system, [24] estimated the impact of

the packet generation rate, the packet blocklength, and the blocklength allocation factor on the

average AoI. Moreover, [25] studied the optimal packet blocklength of non-preemption and

preemption strategies for minimizing the average AoI, while [26] derived the average AoI and

the AoI violation probability in a downlink system. Considering a feedback mechanism, [27]

derived the average AoI under two protocols, i.e., the traditional protocol and the ARQ protocol,

and presented sub-optimal blocklengths to minimize the average AoI for both protocols.

Although the aforementioned studies have investigated the impact of the packet blocklength

on the AoI performance of short packet communication systems, the impact of different packet

management strategies on the AoI performance of multiuser short packet communication systems

has not been touched. Moreover, the impact of correlation among the information for user

equipments (UEs) on the average AoI has not been studied in the literature. To the best of

our knowledge, this is the ﬁrst work to investigate transmission scheme selection to optimize the

AoI performance based on the correlation among the information for UEs. The main contributions

of this paper are summarized as follows:

•We derive new closed-form expressions for the average AoI of a multiuser system, where

we consider two transmission schemes with three packet management strategies, i.e., the

non-preemption strategy, the preemption in buffer strategy, and the preemption in serving

strategy. Aided by simulations, we demonstrate the accuracy of our analytical results. We

also ﬁnd that the block error rate has a more signiﬁcant impact on the average AoI for the

unicast transmission scheme than the broadcast transmission scheme. We further ﬁnd that

the non-preemption strategy achieves a lower average AoI than the preemption in serving

strategy in the broadcast transmission scheme, and the preemption in buffer strategy achieves

the lowest average AoI compared with the non-preemption and the preemption strategy in

serving strategies in the unicast transmission scheme.

•Considering the information correlation among UEs, we compare the average AoI achieved

by both transmission schemes with non-preemption strategy in a remote control system. In

this system, with the feature of stochastic status update generation, we derive the thresh-

old of the information ratio between the broadcast transmission scheme and the unicast

transmission scheme to decide which transmission scheme is adopted. We then show the

relationship between this threshold and the number of UEs in two special cases. We further

ﬁnd that the unicast transmission scheme achieves a lower average AoI than the broadcast

transmission scheme when the number of UEs is large.

•We then extend the comparative study of the two transmission schemes to a dynamical

system. In this system, we approximate the expected average AoI under the zero-waiting

policy. Based on the approximation result, we determine the approximated threshold of

the ratio between the individual information and the common information to decide which

transmission scheme is adopted. We observe that the increase in this ratio has a more

pronounced impact on the average AoI for the broadcast transmission scheme than the

unicast transmission scheme.

The rest of the paper is organized as follows. In Section II, the system model and two

transmission schemes are described. New closed-form expressions for the average AoI of two

transmission schemes with different packet management strategies are derived in Section III. In

Section IV, the transmission schemes are decided based on the AoI performance in two systems.

The numerical results are discussed in Section V and the paper is concluded in Section VI.

II. SYSTEM MODEL

A. System Description

We consider a multiuser wireless communication system, as depicted in Fig. 1, where a

base station (BS) transmits status update to NUEs. We denote the nth UE by Un, where

Fig. 1. Illustration of our considered multiuser system where the BS transmits status update to NUEs.

n= 1,2,· · · , N. In this system, the BS generates the status update for NUEs according to a

Poisson process with the rate λ. Then, packets are generated by the BS based on the generated

status update, and the packets are transmitted from the BS to UEs. In this system, we consider two

transmission schemes, namely, the broadcast transmission scheme and the unicast transmission

scheme, described as follows:

•In the broadcast transmission scheme, we assume that the status update for NUEs contains

Lbits, where Lis a ﬁxed value. Once the BS generates the status update, it encodes these L

bits into a packet with the blocklength of Mchannel use (c.u.) and transmits this packet to

NUEs. For this transmission, we deﬁne the coding rate, R, as the ratio between the number

of bits in the status update and the blocklength of the transmitted packet, i.e., R=L

•In the unicast transmission scheme, the BS separately transmits the status update to N

UEs by following an RR policy. We denote the length of the status update and the packet

blocklength for Unby Lnand Mn, respectively. For this transmission, we deﬁne the coding

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1AgeofInformationinDownlinkSystems:BroadcastorUnicastTransmission?ZhifengTang,StudentMember,IEEE,NanYang,SeniorMember,IEEE,ParastooSadeghi,SeniorMember,IEEE,andXiangyunZhou,SeniorMember,IEEEAbstractWeanalyticallydecidewhetherthebroadcasttransmissionschemeortheunicasttransmissionschemeachievestheopti...

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