〈一般研究課題〉 走行中自動車群のソフト一体化を実現する
ポジティブ対応型通信に関する研究
助 成 研 究 者

愛知県立大学田

学軍

走行中自動車群のソフト一体化を実現する
ポジティブ対応型通信に関する研究
田 学軍（愛知県立大学）

Improving Wireless Networks to Realize Positive
Communication for Transport Systems
Xuejun Tian
(Aichi Prefectural University)

Abstract
The MAC protocol is important in LAN, especially in wireless LAN because of limited bandwidth. A
great deal of research has been carried out and some of proposed schemes are effective. Specifically,
considerable effort has been devoted to improving the IEEE 802.11 standard which is utilized widelyand it seems that we cannot expect to enhance the throughput dramatically than improved proposals
ether for DCF or PCF. In the meantime, besides throughput, there are some other issues for DCF
such as fairness and QoS support. However, except for several hybrid protocols, most proposals were
either based on contention mode or schedule mode and neither of the two modes has possessed thegood characters of the other.
In this paper, we propose a new hybrid MAC scheme used for distributed system (with no controlnode) that dynamically adapts to traffic changes without degradation of delay in the case of low trafficload and achieves high throughput which is close to transmission capacity in saturated case. We
carried out simulations focusing on throughput and delay. Through an analysis of simulation results,
we show that our scheme can greatly improve the throughput with low delay.

Keywords WLAN, MAC protocol, Throughput, Random Access, Channel Reservation.

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Ⅰ. INTRODUCTION
The MAC protocol is important in LAN, especially in wireless LAN because of limited bandwidth.
IEEE 802.11 standard [1], [2], [3] specifies a common medium access control (MAC) layer, which
provides two functions, Distributed Coordination Function (DCF) and an optional Point Coordination
Function (PCF). The basic 802.11 MAC layer uses DCF to share the medium between multiple
stations. DCF will suffer collisions, which will lower the available bandwidth in the case of high traffic.
In contrast to the DCF, the polling mechanism causes significant overhead and unnecessary delay forstations under low traffic.
Since DCF and PCF have different performances, research on MAC protocols based on the two
methods were carried out respectively for the different situations. Due to inherent simplicity andflexibility, the DCF mode is preferred and has attracted most research attention [4], [5], [6], [9], [10],[11], [12]. Cali et al. pointed out in [7] that depending on the network configuration, IEEE 802.11 DCF
may deliver a much lower throughput compared to the theoretical throughput limit after analysis and ascheme was given for achieving a throughput close to the theoretical upper bound in saturated case. It
seems that we cannot expect to enhance the throughput much more for DCF in a usual way. Hybrid
Coordination Function (HCF)[13],[14] of IEEE 802.11e is defined for overcoming the QoS problem byIEEE 802.11 task group. The HCF uses a superframe consisting of contention period (CP) andcontention free period (CFP), which seems like a hybrid method of contention-based and schedulebased scheme. However, the CF-Schedule needs a control node as a coordinator and may waste
channel capacity. A scheduled node may not fully utilize the allocated TXOP (Transmission
Opportunity) when there are not enough pending data to be transmitted. On the other hand, thelifetime of each scheduled TXOP is different, so the scheduled TXOPs that are still alive may sparsely
distribute over the channel space after a certain time period. It becomes an overhead for the PC torearrange the scheduled TXOPs. HCF is a complex coordination function and EDCA appears to begaining more early acceptance than HCF but, as indicated, cannot provide efficient channel utilizationand the aggregate throughput degrades when network situation changes in the number of active
nodes, traffic load and proportions among traffic of different priorities [18][19]. In this paper, we
propose a novel MAC protocol for WLANs, focusing on the aggregate throughput and potential QoS
support. The novelMAC scheme dynamically works in the two modes, i.e., schedule or contentionmode, which is named as Scheduled Random Access Protocol (SRAP). Compared to the 802.11 MAC
protocol and previous enhancement approaches, this scheme has the following distinguishing features:・It allows WLANs to work with low delay as in the contention-based mode and achieve a highthroughput as in the schedule-based mode without complicated on-line estimation as required inprevious schemes[15],[16],[17].
・Unlike usual hybrid methods, SRAP dynamically works in the schedule and contention modes
without the burden of complicated computing for shifting in two modes.
・SRAP suitably adapts to traffic changes, which leads to high throughput in saturated case without
degradation in delay even in the unsaturated case.

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・Unlike HCF, SRAP is simple and can be easily adapted to support QoS as a distributed function,
which can be expected to be used for improving other protocols such as EDCA.
The remainder of this paper is organized as follows. In Section 2, we present in detail our proposed
SRAP scheme. Then we analyze SRAP approximately. In Section 3, we give the simulation results anddiscussions. Finally, concluding remarks are given in Section 4.

Ⅱ. SCHEDULED RANDOM ACCESS PROTOCOLTo better understand our scheme, in this section we first briefly introduce the DCF of original
version of the IEEE 802.11 utilized broadly in WLANs, a distributed contention based medium access
control protocol. Then, we give our proposal SRAP.
A. Operations of the IEEE 802.11 MAC
The IEEE 802.11 DCF is based on a mechanism called carrier sense multiple access with collision
avoidance (CSMA/CA). In DCF mode, a node with a packet to transmit initializes a backoff timer
with a random value selected uniformly from the range [0, CW − 1], where CW is the contention
window in terms of time slots. After a node senses that the channel is idle for an interval called DIFS
(DCF interframe space), it begins to decrease the backoff timer by one for each idle time slot. Whenthe channel becomes busy due to other nodes' transmissions, the node freezes its backoff timer until
the channel is sensed idle for another DIFS. When the backoff timer reaches zero, the node begins
to transmit. If the transmission is successful, the receiver sends back an acknowledgment (ACK)after an interval called SIFS (short inter-frame space). Then, the transmitter resets its CW toCWmin. In case of collisions, the transmitter fails to receive the ACK from its intended receiver
within a specified period, it doubles its CW subject to a maximum value CWmax, chooses a new
backoff timer, and start the above process again. When the transmission of a packet fails for a
maximum number of times, the packet is dropped.
To improve channel efficiency for long packet transmissions, the IEEE 802.11 protocol can also
use a short Request To Send (RTS) control frame and a short Clear To Send (CTS) frame to reserve
access to the channel. RTS/CTS is valid to relieve the interference from collisions. Hereafter,
RTS/CTS is used only in contention period of our protocol SRAP stated afterwards.
B. SRAPAs shown in Fig. 1 (a), SRAP allows channel access in terms of superframes consisting of twoparts, schedule period and contention period. Nodes either transmit in schedule period without
collision or contend for the channel to transmit in contention period but are not allowed to transmit
in both of two periods in one superframe. At the beginning, a node contends for a channel incontention period and after successful transmission, it is allowed to transmit in scheduled period if
its queue is not empty or it has a sending request coming in time, or the queue length exceeds acertain threshold. Here, firstly we give the procedure for nodes to reserve channels in schedule
period and to escape from schedule period when the queue become empty in the normal case shownas Fig. 1. And then we give the procedure of initialization when there is no schedule period.

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Successful Transmission (ST)SIFS
Node 5, Node 6 join into the schedule period
and Node 4 finishes its transmission

DIFS

PacketTransmission

ACK

ST of
Node 5

ST of
Node 6

Schedued period
ST of Node 1

HeadBeacon

ST of
Node 4ST of
ST of Node 3
Node 2Collision checkif collision occurs, after the collision
the header uses an interval shorter than
DIFS

(a)

ST of
ST of Node 3
Node 2Collision check
Head Beacon

ST of
Node 6

ST of
Node 5End Beacon

Idle slot
for Node 4(b)Contension period (CPIS)

Schedued period
ST of Node 1

Collision check
Head Beacon

Contension period (CPIS)

No collision

Schedued period
ST of Node 1

Contension period (CPIS)

End Beacon

ST of
ST of Node 3
Node 2

ST of
Node 6First End Beacon

ST of
Node 5

Second End Beacon(c)Contension period (CPIS)

Schedued period
ST of Node 1

ST of
ST of Node 3
Node 2

ST of
Node 6

ST of
Node 5Collision check
End Beacon

Head Beacon(d)Fig. 1 Procedure of forming a scheduled queue in SRAPIn Figure 1 (a), the node ordered as the first sender in schedule period takes charge as the leader
which sends the head beacon at the beginning of superframe. In the meantime, the node ordered as
the last sender in schedule period takes charge as the tail which sends the end beacon at the end of
superframe. The leader begins to count idle slots after the end beacon. If a certain number called ascontention window in term of idle slots (CPIS) has been reached, the leader then sends the headbeacon. For an active node, it also counts the idle slots and knows the end of contention period, so
collision with the head beacon can be avoided. But for a new comer, it may begin to transmit
immediately if the channel is idle. To deal with this case, the leader waits for one more slot after
sending a head beacon and it uses SIFS to retry if there is the collision. Meanwhile, the tail sends an− 46 −

end beacon after its transmission. The tail can know if it is a tail, which will be explained below.
A node with a request before confirming the channel situation (schedule or contention period) iscalled as a new comer and it can contends for the channel just according to DCF mode. A new comercan understand the channel situation by listening to the channel for some events such as continuoustransmissions with a short interval, head or end beacons when it is in backoff. In general, a newcomer has no chance to find an idle slot in schedule period except that a node with a reservation inschedule period has no frame to transmit and leaves an idle slot after escaping. If unexpectedcollision in schedule period occurs because of a new comer, the new comer will back off and thenode with reservation will retry again with a short SIFS.
Figure 1 shows how nodes (node 5, 6) access the channel, get reservations in schedule period andescape from schedule period (nodes 4). As shown in Fig. 1 (a), there are two nodes, node 5 and 6
succeeding in sending a frame in contention period, which are candidates to have a reservation inschedule period of the next superframe. Since, after successful transmission in contention period, anode can know the following successful transmissions till to the head beacon of the next superframe,
in reverse order, nodes transmits in schedule period after the first end beacon of the next
superframes as shown in Fig. 1 (b).
If a node has no frame to transmit and escape from schedule period, it need not to do anything andan idle slot appears in this position, or certainly, sends a signal of one slot to keep the reservation if
necessary. Counting the idle slot as a frame transmission, the other nodes judge their transmission
turns. After the transmission of the last candidate, the tail sends the second end beacon whichmakes the last candidate to become the tail instead from the next superframe. The useless idle slots
distributing in schedule period are compressed in the next superframe as shown in Fig. 1 (c) and(d).
Since the channel is busy in schedule period, a node contending in contention period just needs to
set backoff according to the situation of contention period without caring the schedule period. The
contention period CPIS in term of time slot is just like an entrance to the schedule period and thelonger it is the faster a node can access the channel; however, a long CPIS wastes bandwidth when
the network becomes saturated. So CPIS is an important parameter for SRAP.
As for the initialization, we give the procedure as follows. We assume that a node withouttransmission request is not active and does not listen to the channel, so when a request arrives at anode it begins to contend for the channel with no information related to neighbor nodes and channel
situations. The node contends for the channel just as DCF mode. If the node encounters no collisionand detects no event related to schedule period, it can continue transmitting. A node in backoff,upon detecting no head beacon after CPIS, knows that the channel is unscheduled. Then the node
just needs to send a head beacon and end beacon to announce itself as the leader and tail.

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Superframe

Contention period(CPIS slots)
Schedule period
ST ofNode 2ST of Node 1

ST of Node n
Idle Slots

Collision check
End Beacon

Head
BeaconFig. 2 Channel of SRAP in saturated case

From above, we can see that the number of nodes in schedule period increases as traffic loadrises. On the other hand, SRAP behaves like pure DCF when traffic load becomes extremely low.
C. Approximately Analysis and Discussion
In this section, we evaluate the performance of our SRAP approximately through comparing withusual protocols. After showing that SRAP achieves a higher throughput for the saturated traffic load,
we discuss the performance besides throughput in the unsaturated case and then we give potential
option to support QoS. In fact, we can apply any improved DCF protocols such as [7],[8] in thecontention period of SRAP and a higher throughput can be expected. However, for the convenience,
we suppose our SRAP use IEEE 802.11 DCF in contention period.
1. Throughput in saturated case.
The saturated traffic load means every node always has a frame to send. In other words, every
nodes' queue is never empty. In this case, we can understand the throughput of SRAP reaches the
maximum and the wireless channel are utilized effectively as shown in Fig. 2
If we ignore the overhead in schedule period such as head beacon, we can express the throughput
as follows:
ρ=

n

n

（Σ i=1 Ti）/(Σ i=1 Ti +CPIS ・ Tslot )（1）

where Ti is the transmission time of the frame sent from node i, n is the number of active nodes.
As shown above, we can enhance aggregate throughput by decreasing CPIS. And we canunderstand that SRAP with a small CPIS can achieve a higher throughput than original andimproved IEEE 802.11 DCF schemes whose throughput is close to the theoretical upper boundindicated in [7]. For the saturated case, SRAP has a higher throughput close to that achieved byschedule-based scheme and also dynamically adapts to the changes in traffic load and the numberof nodes in WLANs.
2. Mean waiting time in unsaturated case.
Like most research on IEEE 802.11 focusing on improving throughput for the saturated case,we showed every node of SRAP transmits frames in a way of reservation with a higher throughput
in the saturated case. In the following, we approximately discuss performance related to theaverage queue length and mean waiting time for unsaturated case.
Generally, any scheme based on DCF can be used in the contention period of SRAP, such as
IEEE 802.11+ proposed in [7] that claimed to achieve a throughput close to theoretical upper− 48 −

bound in the saturated case. We assume SRAP uses the same protocol in contention period whencompared with a reference DCF protocol.
Obviously, if each node does not enter schedule mode when traffic load is extremely low, SRAP
becomes a pure DCF scheme used in contention period and certainly its waiting time and queue
length are same as those of the DCF scheme. On the other hand, pure DCF scheme will reachsaturation as arrival rate increases, for example at λ th. Assume SRAP with the same number ofnodes in network reaches saturation at λths, we have λths r λth if we set CPIS small enough. In
this case, when the arrival rate is near or greater than λth , SRAP will have a shorter average
waiting time and average queue length than pure DCF scheme. So, at least, we can find a value,λ0(e λth ) from which SRAP behaves with a shorter average waiting time and queue length thanpure DCF scheme. To achieve better performances of average waiting time and queue length aswell as a higher throughput, we can simply keep nodes not to enter schedule mode until theirarrival rates increase beyond the λ0 . Thinking of practical applications, we have a very simple
index, queue length, which is suitable for a node to decide whether to enter into schedule mode.
When the queue length of a node exceeds a threshold value, it means the traffic load of the node
is beyond capability of DCF scheme or many frames are accumulated occasionally, both of which
result in a long waiting time. In this case, it is very natural for a node to enter into schedule mode
to transmit accumulated frames more quickly. By this way, a node announces if it will not enter tokeep a reservation in schedule period after successful transmission in contention period otherwise
it enters into schedule period. In fact, according to the simulation without no limitation for a node
to enter schedule period, shown in the next section, we find that SRAP has no obvious droparound the point at which the throughput of SRAP exceeds that of IEEE 802.11 DCF.
3. Potential options for supporting QoS
The latest version of wireless protocol, EDCA, is developed to provide QoS in the MAC layer. In
EDCA, fixed CWmin[AC] and CWmax[AC] can guarantee the differentiation among different
priority classes, but it cannot provide an efficient channel utilization and the throughput degrades
when network situation changes in the number of active nodes, traf- fic load and the proportions
among traffic of different priorities. In contrast, SRAP has several possible options to support QoS
without degradation in throughput when the network situation changes. For example, SRAP cantransmit high priority frames in schedule period, which means that a node can enter into schedule
period to transmit high priority frames no matter how long its queue length is. In this way, a nodeof SRAP can realize if the QoS of high priority frame is satisfied through the schedule periodinterval and if necessary, a node can halt the transmission of low priority frames. Furthermore, if
necessary, SRAP can use EDCA in contention period, so a node with a high priority frame canaccess the channel faster and then send the other high priority frames in schedule period. With
this method, SRAP can support QoS and achieve a high throughput no matter how networkchanges in the total traffic load or the proportion of high and low priority traffic loads.

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Ⅲ. SIMULATIONIn this section, we focus on evaluating the performance of our SRAP including throughput and delay,
through simulations carried out on ns2. For comparison purpose, we also present the simulation
results for the IEEE 802.11 DCF. Though some improved protocols [8] of higher throughputs havebeen proposed, we use IEEE 802.11 DCF as the access protocol in contention period of SRAP and we
can understand straightly that the SRAP should have a much higher throughput if using improved
IEEE 802.11 from analysis as shown in the above section. Here, we just give the simulation results ofIEEE 802.11 which is a well known protocol. In contention period of SRAP, the RTS/CTS mechanism
is used, which is not necessary in schedule period. The DCF-related parameters are shown as follows:
MinCW: 31, MaxCW :1023, SIFS: 10μ sec, DIFS: 50 μ sec ,Slot Length: 20 μ sec, Basic Bit rate: 1
Mbps , Bit rate: 11 Mbps
We carry out simulations with the model shown in Fig. 3. There is a sink node which only acts as areceiver. There are also 8 source nodes and 24 source nodes respectively for the two cases simulated.
All source nodes generate Poisson traffic with the same arrival rate, which is a disadvantageous casefor SRAP which allows a node with burst traffic to transmit in a reservation mode. Thinking a WLAN
used indoors, we set nodes at the intersection points of grid with 5-10m interval.
Figure 4 shows the throughput results of 8 source nodes. The horizontal axis expresses the nodetraffic which is set as the same value on each node, while the vertical axis expresses obtained total
throughput of network whose datarate is 11Mbps. As shown in Fig. 4, the throughputs of SRAP
increase with arrival rate (Mbps/per node) till reaching saturation either in the case of packet size
500byte or 1000 byte. Around saturated points of IEEE 802.11, the throughputs of two protocols almost
have no difference and when traffic continues increasing, the throughputs of the SRAP increase. On
the contrary, the throughputs of IEEE 802.11 get a little down because of increasing collisions. In

5m

5m
Sink node

5m

5m

5m
5m
5m
5m
Simulation model of WLAN:
8 source nodes (black circle) with 1 sink node
24 source nodes (all circle) with 1 sink nodeFig. 3 Simulation models of 8 nodes and 24 nodes− 50 −

comparison to IEEE 802.11, SRAP gives significantly better performance, the throughputs are
improved 57% and %71 respectively for the case of 1000byte and 500byte, which means the SRAP ismore effective in avoiding collisions.
Figure 5 shows the throughput results of 24 source nodes. As shown in Fig. 5, we can find the samecharacters shown in the case of 8 source nodes. The saturated points are not so clear as the case of 8
nodes. Since all source nodes are set with the same Poisson arrival rate under the condition of samedata rate 11Mbps, when the total traffic rises close to saturation, the traffic per node is lower than thatof 8 source nodes, so the probability that a node sends a packet in reservation mode for SRAP is lower
than the case of 8 source nodes. Then, the throughputs of 24 nodes increase for a period before
reaching saturation. In practice, many cases are such that some nodes have heavy traffic and theothers have comparatively light traffic, in which SRAP is advantageous. From the simulation results,
we find the throughput of SRAP could not reach the throughput evaluated in the previous section
because of overhead and transmission error.
Figure 6 shows delay results of 24 source nodes. Here, the delay is defined as the average time for apacket from joining into queue to being received. In Fig. 6, the horizontal axis expresses traffic load oneach node and the corresponding total traffic load becomes 8 times since there are 8 nodes in network.
As well Known, under the condition of a constant data rate, the higher the throughput is, the lower the
average delay, which can be found from Fig. 4 and 6. As shown in Fig. 6, when total traffic in network
is under 1.6Mbps with constant packet size 500 bytes, the delay of SRAP is lower or almost same asthat of IEEE 802.11. When the total traffic exceeds 1.6Mbps, the delay of SRAP becomes obviously
lower than that of IEEE 802.11. As increasing of traffic, the delay reaches a constant value since thethroughput stop increasing because of packet abandonment. Comparing the case of 500bytes with
1000bytes, we can find that the delay of 1000bytes is lower than 500byte at low traffic either for SRAP

Fig. 4 Throughput of SRAP with 8 nodes− 51 −

or IEEE 802.11 but becomes higher in the case of saturation because the delay includes thetransmission time which of 1000byte is longer than that of 500byte.
In Fig. 7, we can find same characters shown in the case of 8 nodes in Fig. 6. In Figure 7, the delay of
packet in SRAP is decreased dramatically and lower than that of IEEE 802.11 when traffic exceeds acertain value and the difference of delay between srap and IEEE 802.11 becomes more bigger because
SRAP can avoid collisions which getting worse in the case of more node members.

Fig. 5 Throughput of SRAP with 24 nodes

Fig. 6 Delay of SRAP and 802.11 with 9 nodes− 52 −

Fig. 7 Delay of SRAP and 802.11 with 24 nodes

Ⅳ. CONCLUSIONSIn this paper, we proposed a novel MAC protocol called SRAP, which achieves high throughput insaturated case without degradation in delay before saturation. SRAP is a distributed protocol whereby
a central control node is not necessary. SRAP utilizes schedule period as well as contention period toachieve a throughput higher than the upper bound of pure DCF protocol given in the prior research.
Meanwhile, SRAP does not need complicated configuration parameters. A node of SRAP just adjusts
itself to enter into schedule period according to its own queue length. Thinking practical applicationsof nodes in network with unbalanced traffic, it is a good character using index of queue length andwaiting time which are easily obtained. Besides high throughput, SRAP can reach a low packet delay
shown as simulation results. SRAP also can be expected to achieve a low jitter and need to be evaluatedin future works.

ACKNOWLEDGMENT : This research was partially supported by the Hibi Research Grant, 2006.

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