Long Term Evolution-Advanced (LTE-A) is the latest 4G technology with 3GPP specifications, which will provide anytime and anywhere internet access to the ever increasing number of smart phone users. In LTE-A, scheduling plays a fundamental role in allocating radio resources to the wireless network. An efficient radio resource allocation mechanism is imperative for any wireless network to ascertain the performance of the network taking into account the channel conditions and QoS requirements. In this paper we have made an extensive survey of various scheduling algorithms for downlink real time data in LTE-A networks. We essentially focused on scheduling algorithms with reference to the real time traffic classes such as VoIP, Video Streaming etc., with specific emphasis on QoS parameters.
Keywords: Packet Scheduling, LTE-Advanced, Real Time Traffic,QoS, Radio Resource Management.
1. Introduction
In recent times, the demand for high data rates is ever increasing in any wireless network environment. The requirements for 4G systems as specified by 3rd Generation Partnership Project (3GPP), a part of International Mobile Telecommunications-Advanced (IMT-A), is 1 Gbps downlink peak data rate and 500 Mbps uplink peak data rate[1]. Orthogonal Frequency Division Multiple Access(OFDMA),Carrier Aggregation (CA), Multi Input and Multi Output (MIMO), Coordinated Multi-Point transmission (CoMP) techniques, Relaying, and Heterogeneous Networks (HetNets) deployments are some of the key technologies standardized for fulfilling IMT-A targets.[1]
There are three main challenges in wireless communication that need to be met, so as to enable access to information and data sharing anywhere and anytime, by anyone and anything. These are
• Massive growth in the number of connected devices
• Mammoth growth in traffic volume
• An ever increasing range of wide applications with varying requirements and characteristics [2]
For these challenges to be addressed properly, certain technologies have been developed to evolve LTE-Radio Access Technology(RAT) further. A brief introduction to these technologies has been given below.
Since the spectrum is sparsely available and its cost is very high, it is not always possible to get continuous frequency bandwidth. In order to overcome this constraint, a technique called Carrier Aggregation is used. CA facilitates effective use of spectrum by allowing User Equipments(UE) to simultaneously aggregate different frequency fragments(e.g., 20 Mhz) to form a wider transmission bandwidth. These individual fragments are called Component Carriers(CC)[7].These carriers can be configured either within the same band(contiguous) or in different bands (non-contiguous) using different bandwidths.Since we are using these multi carriers in LTE-Advanced, developing a constraint based packet scheduling algorithm has become more challenging when compared to other single carrier systems.
Long Term Evolution-Advanced(LTE-A) Release-10 proposes another technique called MIMO(Multiple Input and Multiple Output) which deploys multiple antennas at the transmitter and at the receiver in order to provide simultaneous transmission of several data streams on a single radio link. In LTE-A terms MU-MIMO(Multi User-MIMO) approach facilitates assigning the same RB(Resource Block) to different users[4].
2.Scheduling in LTE-A networks
The following fig.1 depicts the overall Radio Resource Management(RRM) process that interact with the downlink packet scheduler. The whole process can be divided into a sequence of operations that are repeated, in general, every TTI:
1. The eNB uses the Channel Quality Indicator(CQI) information for the allocation decisions and fills up a RB “allocation mask”. The eNodeB uses both CA and MIMO features to take a scheduling decision based on QoS parameters and buffer status.
2. The AMC module selects the best MCS that should be used for the data transmission by scheduled users.
3. The information about these users, the allocated RBs, and the selected MCS are sent to the UEs on the Physical Downlink Control Channel(PDCCH).
4. Each UE reads the PDCCH payload and, in case it has been scheduled, accesses to the proper PDSCH payload.
5. Each UE decodes the reference signals, computes the CQI, and sends it back to the eNB[3].
Fig. 1 Basic Model of a Packet Scheduler[3]
2.1 Radio Bearer Management and QCI classes
A radio bearer is a logical channel established between an User Equipment(UE) and the evolved-NodeB(base station). It is responsible for managing QoS provision on the E-UTRAN (Evolved-Universal Terestrial Radio Access Network) interface. When an UE joins the network, a default bearer is created for basic connectivity and exchange of control messages. It remains established during the entire lifetime of the connection. Dedicated bearers, instead, are set up every time a new specific service is issued. Depending on QoS requirements, they can be further classified as Guaranteed bit-rate (GBR) or non-guaranteed bit rate (non-GBR) bearers [3]. Each bearer is characterized by a QoS class identifier (QCI). The standard QCI characteristics is summarized in Table 1[3].
In Section-3 details a thorough review of various packet scheduling algorithms for real time traffic in LTE-A and their scheduling metrics.
3. Related Work
In many related works, the scheduling problem has already been proved that it is NP-hard[5],[6],[7]. Because, the assignment
of RB of a CC to a UE during a specific TTI, is largely influenced by the channel conditions with varying time, frequency and UE’s location.
In [8], the authors proposed a new method forradio resource allocation for LTE-A users.
TABLE-1 STANDARDIZED QCI CHARACTERISTICS[3]
QCI Resource Type Priority Packet Delay Budget
(ms) Packet Error Loss Rate Example Services
1 GBR 2 100 10-2 Conversational Voice
2 4 150 10-3 Conversational Video
(Live Streaming)
3 3 50 10-3 Real Time Gaming
4 5 300 10-6 Non-Conversational Video
(Buffered Streaming)
5 Non-
GBR 1 100 10-6 IMS Signalling
6 6 300 10-6 Video (Buffered Streaming) TCP-based(e.g., e-mail,ftp,chat,etc.,)
7 7 100 10-3 Voice,Video(Live Streaming),
Interactive Gaming
8 8 300 10-6 Video(Buffered Streaming) TCP-based(e.g., e-mail,ftp,chat,etc.,)
9 9
In [3],the Key Design Issues and a survey of various scheduling algorithms such as First In First Out(FIFO), Round Robin(RR), Blind Equal Throughput(BET), Resource Preemption(RP), Weighted Fair Queuing(WFQ), Earliest Deadline First(EDF), Modified Largest Weighted Delay First(M-LWDF), Maximum Throughput(MT), Proportional Fair Scheduler(PF) and so on were comprehensively presented.
In the above mentioned scheduling schemes such as FIFO and RR which are QoS unaware, may not be directly deployed in today’s multimedia applications based networks. The age-old Maximum Throughput(MT) algorithm selects the flows experiencing the best instantaneous channel conditions and the Propo
rtional Fair(PF) scheme chooses the flows with least running average throughput at a given TTI.
Hence, for our review we consider the more recent schemes which are QoS aware and suitable for present day real time internet applications. we present their scheduling metrics as follows:
They have stated that since LTE-A uses multiple Component Carriers(CC), two ways of implementing the Proportional Fair (PF) Scheduler.They are,
(a) Independent scheduling per CC
This method is derived from the traditional single carrier scheduling by carrying out resource allocation separately in active configured CCs. Scheduler in each CC is not aware of the scheduling status of users in other CCs. The metric for this method is given as follows :
j = argmax (1)
where Rn,m (i, k) is throughput of nth user in ith scheduling interval at kth resource block(RB) of mth CC. Tn,m(i − 1) is average throughput of this user in the same CC. j is the selected user to be scheduled.
(ii) Joint scheduling across CC
This method takes into account the user’s statistics of all the configured CCs. The joint scheduler which is implemented in both serial and parallel manners, can improve the overall performance of throughput.
In Blind Equal Throughput(BET) the scheduling metric is shown as follows
MBET = 1/(R[N]) (2)
and in Proportional Fair(PF) the scheduling metric is given as
MPF = (D[n]) / (R[n]) (3)
where n is the user index, D[n] is the wideband throughput expected, R[n] is the past average throughput which is updated every TTI[24].
The M-LWDF scheduling algorithm considers the real time traffic service classes such as VoIP and Video Streaming flows for providing QoS. The metric for M-LWDF is given as follows.
In each time slot t, serve the queue j for which
MMLWDF = (4)
is maximal where Wj(t) is the head-of the-line packet delay for queue j.rj(t) is the channel capacity with respect to flow j. is the arbitrary positive constants[25].
In [26], the authors have proposed a Modified Earliest Deadline First algorithm for video and VoIP traffic in LTE-Advanced. In this algorithm, a user whose HoL(Head of Landline) packet is the most close to the headline is chosen according to the equation as in
k=argmax (5)
where
k selected user with the largest metric
packet delay threshold of user i
DHoL,i HoL packet delay of the i th
user at t th TTI. [26]
The authors in [27] proposed an optimized-service aware (OSA) scheduler. In this scheme the resource allocation process has been divided into three separate stages—QoS classes identified classification, time domain, and frequency domain scheduling. The OSA algorithm sorts each GBR bearer according to the head of line (HOL) packet delay in the buffer of the related bearer, while the non-GBR bearer list is ordered according to the following priority metric:
MOSA = (D[n])/(ɵ[n]) WQoS (6)
where ɵ[n] is the normalized average channel condition estimate of bearer n and WQoS is the QoS weight.
In [28], A three level packet scheduler has been proposed for real time traffic. The three layers are super-frame layer,frame layer and TTI layer which represent three distinct time domains at which this algorithm operates.
A novel Packet Prediction Mechanism(PPM) has been proposed in [29] which operates in three different phases. These phases include in the first phase initial scheduling for Physical Resource Blocks(PRBs) in frequency domain for effective bandwidth utilization, then managing queues and calculating expected delays for packets, and finally introducing a cut-in process for meeting delay requirements.
4. SUMMARY AND CONCLUSION
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