An SDR implementation of WiFi receiver for mitigating multiple co-channel ZigBee interferers
Kumar et al. EURASIP Journal on Wireless Communications and
(2019) 2019:224
Networking
https://doi.org/10.1186/s13638-019-1512-3
R ES EA R CH
Open Access
An SDR implementation of WiFi receiver
for mitigating multiple co-channel ZigBee
interferers
Sumit Kumar1*
, Florian Kaltenberger1
, Alejandro Ramirez2 and Bernhard Kloiber2
Abstract
Machine-to-machine (M2M) communication is one of the vertical sectors that will benefit from 5G communication
systems, but today, these systems are still dominated by technologies such as ZigBee and WiFi. An M2M scenario will
experience dense deployment of ZigBee and WiFi nodes in order to route the data from one end to the other. In the
2.4 GHz industrial, scientific, and medical (ISM) band, both of the technologies perform co-channel overlapped
operation and hence face severe cross technology co-channel interference (CCI). In contrast to cellular systems, which
solve the CCI by centralized coordination through the base station, addressing CCI in the ISM band is non-trivial due
to heterogeneous wireless technologies and the lack of centralized coordination. In this work, we first present
interference mitigating receiver architectures for OFDM-based WiFi using single and multiple antennas. Our single
antenna work is based on the localized estimation of excess noise caused by single and multiple co-channel
narrowband interferers and scaling the log-likelihood ratios (LLRs) of the affected WiFi subcarriers. The simulation
shows our method achieves a significant gain in SNR compared to the conventional method for a given packet error
rate (PER) criterion. Next, we discuss maximal ratio combiner with LLR scaling (MLSC), which is a multi-antenna
extension to our previous work. The simulation shows MLSC achieves diversity gain apart from the gain in SNR.
Further, we propose soft-bit maximal ratio combiner with LLR scaling (SB-MLSC). SB-MLSC is an easy to implement
version of MLSC. However, diversity combining in SB-MLSC is performed by combining the LLRs. Nonetheless,
simulations show equivalence in performance by SB-MLSC and MLSC. Finally, as a significant part of this work, we
implemented all our methods using a software-defined radio (SDR) and performed over-the-air (OTA) testing in the
2.4-GHz ISM band using standard WiFi and ZigBee frames. Results of OTA tests fall in complete agreement with our
simulations indicating the practical applicability of our methods. Our methods apply to all the standards and related
radio transmission techniques which are based on OFDM and face narrowband co-channel interference. Additionally,
since our work focuses only on receiver side modifications, they can be integrated with the existing infrastructure with
minimal modifications.
Keywords: Co-channel interference, WiFi-ZigBee, Interference mitigation, Software-defined radio
1 Introduction
The rapid increase in low-cost heterogeneous wireless
devices and scarcity of radio-frequency (RF) spectrum
is causing cross-technology co-channel interference (CTCCI). Effects of CT-CCI are prevalent in the unlicensed industrial, scientific, and medical (ISM) bands
which lack centralized control over devices operating on
*Correspondence:
Communication Systems, Eurecom, Sophia Antipolis, Biot, France
Full list of author information is available at the end of the article
heterogeneous standards. This is in contrast to the cellular
standards operating in licensed frequency bands where
CCI1 is caused due to homogeneous wireless standards
and effectively mitigated by a centralized control of transmit time and transmit power. However, in the ISM bands
where heterogeneous wireless standards operate on overlapped frequency bands, application of methods used in
cellular communication to mitigate CCI is not trivial.
The reason being is the lack of centralized control and
1
1 In cellular networks, as the standards are homogeneous, there is only CCI
and not CT-CCI
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
Kumar et al. EURASIP Journal on Wireless Communications and Networking
(2019) 2019:224
Page 2 of 21
Fig. 1 WiFi-ZigBee frequency allocation in 2.4-GHz ISM band (top) and overlap between a single WiFi and single ZigBee channel (bottom)
1.1 WiFi ZigBee co-channel interference in frequency
domain
802.11g as our candidate OFDM system but the methods
developed by us are generally applicable to other OFDM
system such as IEEE 802.11n as well. IEEE 802.11g is
20 MHz wide and divided into 64 orthogonal subcarriers, each 312.5 kHz wide. In contrast, ZigBee operating
in 2.4 GHz is a narrowband system with a bandwidth
of 2 MHz and uses O-QPSK (offset quadrature phaseshift keying) and DSSS (direct-sequence spread spectrum) in its physical layer. Figure 1 shows that within
every orthogonal channel (20 MHz each) of WiFi, i.e.,
2.412, 2.437, 2.462 GHz, four ZigBee channels (2 MHz
each) completely overlap. As discussed previously, both
WiFi and ZigBee apply CSMA/CA as collision avoidance
mechanism, but still, the collision happens due to the
hidden and blind terminals and differences in channel
sensing/response time [6].
Most of the past studies indicate that WiFi is the culprit
for interference and ZigBee as the victim, which is true
in the majority of the situations [6–8]. The reason being
is the higher transmit power of WiFi compared to ZigBee. However, in the event of a collision, the packet error
rate(PER) of WiFi significantly increases [9, 10], especially
when there is a WiFi receiver in the immediate proximity of a ZigBee transmitter. To verify the PER degradation
of WiFi, we simulated a scenario of interference between
a single-antenna Wi-Fi receiver and a single-antenna ZigBee transmitter in the absence of CSMA/CA2 . Plots of
simulation, as shown in Fig. 2, indicate severe degradation
of Wi-Fi PER for all the modulation and coding scheme
(MCS) which agree with the previous works.
Recognizing that WiFi can also be a victim of CCI
caused by ZigBee, in this work, we address the issue of
IEEE 802.11g (WiFi) operating in a 2.4-GHz band is an
OFDM-based wideband system. We have chosen IEEE
2 Table 1 contains simulation parameters for this figure.
disparity in physical layer implementations of the wireless
standards.
In this work, our application scenarios are smart homes
and modern automated factories where there is dense
deployment of wireless sensors and machine-to-machine
communications play a key role in routing the sensory
data to the processing centers. These wireless sensors
predominantly use wireless local area networks (WLAN;
based on IEEE 802.11) such as IEEE 802.11 a/b/g/n/ah,
and wi (...truncated)
