Communications and Network, 2013, 5, 69-73
http://dx.doi.org/10.4236/cn.2013.53B2014 Published Online September 2013 (http://www.scirp.org/journal/cn)
Cross-layer Resource Allocation on Broadband Power
Line Based on Novel QoS-priority Scheduling Function
in MAC Layer
Huang Qian, Lu Jun, Xiong Chen, Duan Ruichao
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Email: hq050176@163.com, lujun@ncepu.edu.cn, xiongchen2007@163.com, duanrc501@163.com
Received May, 2013
ABSTRACT
Traditional resource allocation algorithms use the hierarchical system, which does not apply to the bad channel envi-
ronment in broadband power line communication system. Introducing the idea of cross-layer can improve the utilizatio n
of resources and ensure the QoS of services. This paper proposes a cross-layer resource allocation on broadband power
line based on QoS priority schedu ling function on MAC layer. Firstly, the algorithm considers both of real-time users’
requirements for delay and non-real-time users’ requirements for queue length. And then user priority function is pro-
posed. Then each user’s scheduled packets number is calculated according to its priority function. The scheduling se-
quences are based on the utility function. In physical layer, according to the scheduled packets, the algorithm allocates
physical resources for packets. The simulation results show that the proposed algorithm give consideration to both la-
tency and throughput of the system with improving users’ QoS.
Keywords: Broadband Power Line Communication; OFDM; Cross-layer; Resource Allocation; Scheduling
1. Introduction
With the construction of strong and smart grid and the
rapid development of communication technology, broad-
band power line communications gradually develop into
the high-speed. Traditional wired network
The wired networks adopt traditional hierarchical sys-
tem: Open Systems Interconnection (OSI) model, which,
from top to bottom, is divided into the application layer,
presentation layer, session layer, transport layer, network
layer, data link layer, and physical layer. Each layer is
independent designed, and the interface between the lay-
ers is static. In broadband power line systems, due to the
large differences of sub-channels, great changes of noise,
multipath fading, dispersion and other unfavorable fac-
tors, the traditional hierarchical system cannot be flexible
to adapt to fast-changing channel environment. Apply the
cross-layer design into the OFDM system, and let the
upper layer’s dynamic business be in close contact with
the physical layer’s channel conditions, which could re-
alize the dynamic allocation of resources and further im-
prove the utilization of resources. In reference [1], an
algorithm based on the satisfaction of packet exchange
and resource allocation is proposed. The algorithm opti-
mally defines the various satisfactory degree evaluation
functions. Then, based on such functions, the algorithm
calculates scheduling utility function, achieving user’s
scheduling. In this algorithm, the differentiation between
emergency services and non-emergency services is not
obvious, which may lead to packet loss of real-time
business. In reference [2], a scheduling algorithm based
on the satisfactory factor is proposed. The algorithm de-
fines satisfactory factor of quality of serv ice, and gets the
new utility function through improving the traditional
index scheduling algorithm (EXP). The algorithm does
not consider the queue’s conditions, which could make
packet loss rate increase for non-real-time services.
This paper introduces a cros s-layer resource allocation
algorithm on broadband power line based on a novel
scheduling function in MAC layer. For real-time busi-
ness, the algorithm considers the packets delay; for
non-real-time business, it considers the queue length.
Combining with the user channel conditions and factors
above, users are divided into different priorities. And
MAC layer utility function is proposed . In physical layer,
we use equal power resource allocation method. The al-
gorithm closely contacts the MAC layer with the physi-
cal layer, and processes packet scheduling and resource
allocation reasonably, which improves the throughput of
the system.
2. Model of Cross-layer Resource Allocation
Through information exchanging between layers, and
C
opyright © 2013 SciRes. CN
H. QIAN ET AL.
70
according to the system’s overall conditions, the cross-
layer resource allocation algorithm meets uses’ needs
better in each layer. Therefore, cross-layer allocation algo-
rithm provides more information to adaptive resource
allocation. However, because of the increase of informa-
tion, computational complexity of the algorithm will in-
crease [3].
The model of cross-layer resource allocation is shown
below:
According to the information interaction between lay-
ers and relevant scheduling rules, the scheduler reasona-
bly allocates system resources, as is shown in Figure 1.
The information between layers mainly includes channel
estimation, feedback, resources of physical layer, queue
status and the QoS requirements, etc. In broadband power
line system, MAC-PHY cross-layer scheduler works as
follows: data from the upper layer, which is assigned to
different buffer queues, combines with physical channel
conditions as the basis of the MAC layer scheduler.
In the broadband power line system, the operations of
the upper layer are varied, and the QoS requirements are
also different. In addition, the arrival of some business
flows is sudden and random, and the power line channel
is time-varying. To make full use of link resources, and
ensure the validity and reliability, the scheduler must
take real-time channel status into consideration. Thus, the
scheduler could select the MAC-PHY cross-layer sched-
uling mode above.
3. Cross-layer Scheduling and Resource
Allocation Algorithm
3.1. User Scheduling on MAC
The scheduling is implemented in the MAC layer. The
utility function may be provided on the joint of the delay,
queue length, packet loss rate and other information on
the MAC layer and channel information on the physical
layer. The utility function determines the scheduling or-
der of business, and completes scheduling [4].
For the sake of simplicity, it is assumed that, at the same
moment, a user has only one service, and corresponds to
only one queue. Each data packet scheduling is for each
queue scheduling. Corresponds to the real-time and non-
real-time user, the queue is divided into real-time queue
and non-real-time one.
First, according to the urgency degree of every queue,
packets are divided into two categories: high priority
packets and ordinary packets.
The priority of queue of real-time business is deter-
mined by delay. Let maximum delay which can be toler-
ated by real-time business of user k is and assume
waiting time of packets of real-time business queue of
user k is , the priority of packets of real-time
business queue of user k is divided according to equation
(1).
max
k
D
current
k
D
max
current
k
RT
kk
D
D
(1)
Packet loss of non-real-time business queue is mainly
caused by the overflow of packets, so its priority is de-
termined by the length of queue [5]. Set the maximum
number of buffered packets of buffered queue is .
In the slot t, the prioritization function of non-real-time
business queue of user k is:
max
Q
max
k
NRT
k
Q
Q
(2)
where
is the coordination factor, which is a positive
number less than 1.
The emergency degree of data packets in each queue is
determined as follows:
c
c
1high priority
ordinary
k
kk



(3)
where k
shows the emergency function of real-time or
non-real-time services, c
is the threshold of emergency
function.
When the priority of the head packet of each queue is
judged, scheduling sequences of different priority is
judged by the scheduling function of high priority and
ordinary packets. Scheduling function is expressed as
follows:
[] []high priority
[] [] [ ]ordinary
[]
kk
K
c
kkk
a
k
PD ii
PD
Ui Ri i
Ri
(4)
where represents the packet loss rate of the
queue k before the i-th frame, and
[]
k
PD i
K
PD
[]
c
k
Ri represents the
maximum packet loss rate. And represents the
maximum supported rate of the queue k’s i-th frame, that
is, when all of time-frequency blocks of the i-th frame
distribute to the queue, the transmission rate can reach
the maximum [6]. And represents the weighted
average rate of the queue k before the i-th frame. The
iterative formula describes as follows:
[]
a
k
Ri
11
[] (1)[1][1]
aa
kkk
cc
RiRiRi
tt
 (5)
where [1]
k
Ri
shows the actual rate of the i-1 frame of
queue k, and tc is the length of the sliding time window.
Based on the scheduling functi on abo ve, pack ets of each
queue are scheduled. The scheduling principle is that,
dispatch high priority packets firstly, and then, schedule
ordinary packets. The packets of same priority are sched-
uled according to the descending order of scheduling
function.
Average sending rate of each user is indicated as a
Copyright © 2013 SciRes. CN
H. QIAN ET AL. 71
vector: 12
[, ,,]
K
Packet RateRRR. According to the
priority function, the number of current scheduling pack-
ets of each user is determined as follows.
(1 )
queue
kk
NR

k
(6)
where k
is the normalized priority.
1
k
kK
k
k
(7)
3.2. Physical Resource Allocation
The method of equal power allocation is applied on
physical layer. Suppose the total power of the system is P,
the number of subcarriers is N, the number of bits which
can be transmitted for user k on the su bcarrier n is:
,
,2
(/ )
log (1)
kn
kn k
PNg
Rb 



(8)
In accordance with the number of scheduling packets
identified on the MAC layer, the sub-carrier which is the
optimal matching is assigned to each user. When the re-
source allocation on physical layer is complete, the cur-
rent round of resource allocation is end. If the rate of
users reaches the scheduling requirement and the system
also has the remaining resources, the remaining resources
are needed to be allocated.
3.3. Remaining Resource Allocation
If all users have reached the fixed rate and the unused
available sub-carriers are still present in the system, the
algorithm allocates the remaining resources. Remaining
resource allocate principle is as follows.
Export the highest priority packet according to the
MAC layer scheduling algorithm.
The optimal sub-carrier is assigned to correspond-
ing packet until bits allocation of the packet is com-
pleted.
Figure 1. Cross-layer resource allocation system diagram.
Figure 2. The flowchart of cross-layer resource allocation.
If the system does not have enough sub-carriers to
transmit bits of th e packets, th ey are not sen t in this OFDM
symbol, and the allocation algorithm of the present
OFDM symbol finishes. If the allocation can be finished
and the system still has sub-carriers to be used, return to
the first step.
The flowchart of cross-layer resource allocation on
broadband power line communication is shown in Figure
2.
4. Simulation and Analysis
4.1. Traffic Source Model
With the development of broadband power line commu-
nication, services hosted on it become diverse increas-
ingly. In order to facilitate the analysis, service wh ich has
high time delay requirements belongs to real-time service,
and others are non-real-time service. Two types of ser-
vices are modeled.
Packets of real-time service queue arrive obey the two-
state Markov distribution, as is shown in Figure 3. ON
indicates the activation period. OFF indicates the quiet
period.
and
indicate the corresponding transition
probability.
Copyright © 2013 SciRes. CN
H. QIAN ET AL.
72
1( /)
OFF
TT
 (9)
1exp( /)
ON
TT
  (10)
In which T is the length of one OFDM symbol, OFF
is the average of quiet period, is the average of
activation pe riod.
T
ON
T
Packets of non-real-time service queue arrive obey the
Poisson distribution. ()
() !
tn
et
PN nn
 (11)
In which
is the average packets arrival rate of non-
real-time service.
In order to ensure the stability o f the system, the aver-
age capacity of services should not exceed the system’s
total transmit capacity. Service source models created
using above distributions are shown in Figure 4 and
Figure 5.
Figure 3. The real-time service Markov model.
0100 200 300400 500 600700 800 9001000
0
0. 5
1
1. 5
Time
unitary data
Two-state Markov
Figure 4. The real-time service model.
0100 200300 400 500600 700 800900 1000
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Time
unit ary dat a
Poisson
Figure 5. The non-real-time service model.
4.2. Simulation and Analysis of System
Performance
The algorithm simulates in typical power line environ-
ment. The following parameters are set as follows: The
frequency range is 0-20 MHZ, power spectrum upper is
-50-0.8 f (dBm/Hz) and f is in MHz. The number of
sub-carriers is 128. Real-time business is corresponding
to user 1 and 2 and the maximum delay is 10 ms. Its max-
imum packet loss rate is 10-3. Non-real-time business is
corresponding to user 3 and 4 and its maximum queue
length is 600. Its maximum packet loss rate is 10-3. =
0.7. Four users’ average packets arrival rates are: 60 kbps,
60 kbps, 40 kbps and 30 kbps.
This article selects maximum throughpu t algorithm [7]
(MAX/MIN) as the comparison. And the proposed algo-
rithm compares and analyses the following factors, such
as system throughput, delay and packet loss rate.
Throughput per forma nce comparis o n
Figure 6 depicts that the MAX / MIN has an uneven
distribution. User one has high throughput, but other us-
ers throughput is low. This paper algorithm’s throughput
matches users’ average packets arrival rates and has high
throughput.
Delay performance comparison
Figure 6. Throughput perfor manc e .
Figure 7. Average queue length.
Copyright © 2013 SciRes. CN
H. QIAN ET AL.
Copyright © 2013 SciRes. CN
73
Figure 7 shows the average queue length of each user.
The MAX\MIN has long queue length. It shows that us-
ers have higher delay. This paper algorithm has short
queue length, which means the delay of packets is short.
Performance comparison of packet loss rate.
Statistics show that the packet loss rate of MAX / I is
0.0015. The packet loss rate of this paper algorithm is
zero. The algorithm proposed takes the users’ average
packets arrival rate into account, improving the packets’
transmission rate. And, the algorithm possessed gets
lower packet loss rate and ensures the user's QoS.
5. Conclusions
This paper discusses cross-layer resource allocation on
broadband power line communication system and puts for-
ward a MAC layer scheduling algorithm based on users’
priority. The algorithm creates different scheduling func-
tion between the real-time and non-real-time users in
MAC layer, and applies the priority function to divide
users into two priorities. Then users are scheduled based
on the priority and utility function. In the physical layer,
equal power allocation method is used. The simulation
results show that the proposed algorithm can take the
latency and throughput into account and improve user's
QoS.
6. Acknowledgements
This work was supported by National Natural Science
Foundation of China (No.51007021) and National Sci-
ence and Technology Major Project of the Ministry of
Science and Technology of China (No.2010ZX03006-
005-01).
REFERENCES
[1] J. Huang, G. S. Vijay and A. Rajeev, et al., “Joint Sched-
uling and Resource Allocation in Uplink OFDM Systems
for Broadband Wireless Access Networks,” IEEE J. Se-
lect. Areas Commun. Vol. 27, No. 2, 2009, pp. 226-234.
doi:10.1109/JSAC.2009.090213
[2] C. Fan, L. Zhang and W. J. Lian, “A Scheduling Algo-
rithm for Guarantying QoS of Streaming Traffic over
Mixed Services,” Journal of Bijing University of Posts
and Telecommunications, Vol. 30, No. 3, 2007, pp.
75-78.
[3] W. W. L. Ho and Y. C. Liang, “Optimal Resource Allo-
cation for Multiuser MIMO-OFDM Systems with User
Rate Constraints,” IEEE Trans. Veh. Technol., Vol. 58,
No. 3, 2009, pp. 1190-1203.
doi:10.1109/TVT.2008.927721
[4] K. Deb, A. Pratap and S. Agarwal, “A Fast and Elitist
Multiobjective Genetic Algorithm: NSGA-,”IEEE
Transactions on Evolutionary Computation, Vol. 6, No. 2,
2002, pp. 182-197.
[5] S. Y. Lin and J. S. Huang, “Adaptive Subcarrier Assign-
ment and Bit Allocation for Multiuser OFDM System
Using Ordinal Optimization Approach,” IEEE Trans. Veh.
Technol., Vol. 57, No. 5, 2008, pp. 2907-2919.
[6] H. Hou, W. Zhou, S. Zhou, et al., “Cross-layer Resource
Allocation for Heterogeneous Traffics in Multiuser
OFDM based on a New QoS Fairness Criterion,” in Proc.
VTC, Baltimore, MD, USA, Sept. 2007, pp. 1593-1597.
[7] B. Sanghamitra, S. Sriparna and U. Maulik, “A Si-
mulated Annealing-based Multiobjective Optimiza-
tion Algorithm: AMOSA,” IEEE Transactions on
Evolutionary Computation, Vol. 12, No. 3, 20 08 , pp.
269-283.doi:10.1109/TEVC.2007.900837