914 IEEE TRANSACTIONS ONELECTROMAGNETIC COMPATIBILITY, VOL. 49, NO. 4, NOVEMBER 2007
Channel Clustering and Probabilistic Channel
Visiting Techniques for WLAN Interference
Mitigation in Bluetooth Devices
Qixiang Pang and Victor C. M. Leung, Fellow, IEEE
Abstract—Since Bluetooth and wireless local area network
(WLAN) technologies both operate at the 2.4-GHz industrial, sci-
entific, and medical (ISM) band, the two types of devices may
suffer from mutual interference and performance degradations.
In this paper, we propose two new techniques, channel cluster-
ing and probabilistic channel visiting, to effectively improve the
existing coexistence and interference mitigation mechanisms. The
channel clustering technique employs statistical pattern recogni-
tion to classify the status of Bluetooth channels more accurately.
The probabilistic channel visiting is used to more equitably allo-
cate the channel resources between Bluetooth and WLAN devices.
The effectiveness of these techniques is quantified by simulations.
Results show that both techniques are beneficial in improving the
performance of the existing mechanisms.
Index Terms—Bluetooth, coexistence, interference mitigation,
wireless local area network (WLAN).
I. INTRODUCTION
I
EEE 802.11 wireless local area networks (WLANs) [1] and
IEEE 802.15.1 Bluetooth (BT) wireless personal area net-
works (WPANs) [2] have been widely deployed. Because both
systems operate in the 2.4-GHz industrial, scientific, and med-
ical (ISM) frequency band, mutual interference between them
may result in severe performance degradations [3], and coexis-
tence of these systems over a shared electromagnetic spectrum
becomes an important issue.
Recently, the interference issue has attracted many research
and standardization activities [3]–[8]. For example, the IEEE
802.15.2 standard [3] includes eight coexistence and interfer-
ence mitigation mechanisms that can be classified into two cat-
egories: collaborative and noncollaborative. The collaborative
mechanisms can be used when the WLAN and BT devices are
integrated within the same physical unit and exchanging infor-
mation between them is feasible. The noncollaborative mech-
anisms are designed for application in BT devices when they
are not collocated with the interfering WLAN devices within
the same physical units. In practice, since many WLAN and
BT devices are independently implemented and installed, the
Manuscript received October 3, 2006; revised February 27, 2007 and May 24,
2007. This work was supported in part by the Canadian Natural Sciences and
Engineering Research Council under Grant STPGP 257684-02 and in part by
the OPNET University program. This paper was presented in part at the IEEE
VTC-Spring, May 2006.
The authors are with the Department of Electrical and Computer Engineering,
The University of British Columbia, Vancouver, BC V6T 1Z4, Canada (e-mail:
qixiangp@ece.ubc.ca; vleung@ece.ubc.ca).
Digital Object Identifier 10.1109/TEMC.2007.908262
noncollaborative mechanisms are more practical. In the follow-
ing discussions, we shall concentrate on the noncollaborative
mechanisms.
The existing noncollaborative mechanisms all use similar
techniques to detect the presence of WLANs in the ISM band
and classify the BT channels as “bad” if they are subject to
WLAN interference, or “good” otherwise. For example, each
BT device can estimate the packet-error rate (PER) or received
signal strength indication (RSSI) for each channel, and a chan-
nel is marked “bad” if the PER or RSSI value exceeds a prede-
fined threshold [3]–[5]. The device then modifies its frequency-
hopping pattern to avoid the “bad” channels, or chooses not
to transmit when hopping onto a “bad” channel. The existing
channel classification methods are simple, but they are effec-
tive only when a single BT piconet exists in the area of inter-
est. When there are multiple piconets within radio range, these
methods can be misled as a high PER or RSSI can result when
more than one piconet hops onto the same channel. To address
this issue, sensing of actual WLAN carriers could be an effec-
tive option, which is, however, quite complex and possibly too
costly to implement in low-cost BT devices due to physical layer
differences.
Besides channel classification, a related problem is how of-
ten a BT piconet should visit the channels after they have been
classified. In the existing mechanisms, once a channel is marked
as “bad,” it will not be visited at all. However, channel condi-
tions are subject to changes and the channel classification can
be misled by the presence of other BT piconets, as discussed
earlier. When multiple WLANs and/or BT piconets coexist, the
number of “good” channels can be very low and the BT de-
vices may be starved of radio resources due to their excessive
courtesy.
Therefore, the existing coexistence mechanisms may not
work effectively in some practical situations. This paper con-
tributes novel solutions to the respective problems discussed ear-
lier by proposing the channel clustering classification method
and probabilistic channel visiting. The current work substan-
tially improves and extends our preliminary work [9] in the
following aspects: 1) a detailed analysis of the problems in
the existing PER-based and RSSI-based channel classification
methods; 2) a detailed analysis of the problem in the existing
channel visiting methods; 3) a refined channel classification
method compared with [9] and other previous work [3]–[7];
4) an analytical evaluation of the proposed scheduling mecha-
nism; and 5) additional simulation scenarios and more detailed
discussions on the performance results.
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