No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Residential microwave oven interference on Bluetooth data performance
Abstract
With both Bluetooth and microwave ovens operating in the same frequency band, fears have arisen about the effects of microwave oven interference on Bluetooth networks. While Bluetooth devices use frequency hopping spread spectrum (FHSS), the high power output of microwave ovens may still pose a threat to Bluetooth networks. We therefore endeavored to characterize microwave oven behavior and understand its effect upon Bluetooth networks. Our experimental results show that Bluetooth devices will tolerate a high level of interference. With two Bluetooth devices forming a piconet placed within 1 m of an oven, the Bluetooth throughput was significantly greater than half of the maximum throughput rate. Moving to a distance around 10 m from the oven showed very little degradation to the throughput due to interference. The effects of microwave oven interference, while noticeable, are by no means fatal. The results also showed no gain from the forward error correction (FEC) used on some Bluetooth packets.
... Bluetooth is a low cost and low power wireless interface for ubiquitous connectivity in the area of Personal Area Networks (PAN) covering distances of 10 meters or less. The technology operates in the unlicensed 2.402 GHz to 2.480 GHz Industrial Scientific Medical (ISM) band and utilizes frequency hopping with terminals cycling through 79 channels at 1600 hops per second [15] [16] ...
... stipulates that the wireless devices must not give interference and must take any interference received [16]. ...
... There is no intelligence in the FHSS to avoid hopping onto certain channels. Even with the pseudorandom FHSS sequence, interference from other devices may still produce significant packet errors and reduce throughput [16]. ...
Cardiovascular diseases are the leading cause of death in the United States. Advances in wireless technology have introduced telecardiology, the remote monitoring of a patient's electrocardiograph (ECG) sensors via cellular telephony. Some of these telecardiology systems use a Bluetooth component to send the ECG signal between the bio sensors and the cellular phone. Several previous studies have suggested that stray wireless transmissions in the ISM band cause interference resulting in packet loss in Bluetooth piconets. While the Bluetooth devices in a telecardiology system are usually less than half a meter apart, patients using these systems are exposed to wireless signals from various sources, including other Bluetooth devices, Wi-Fi networks, and even microwave ovens. This study investigates the impact that wireless transmissions from residential microwave ovens may have on the Bluetooth component of the telecardiology systems.
... All microwave ovens use magnetrons, which typically produce 700 to1000 watts RF power centered on 2.45 GHz. GHz), it has been shown to be very accurate and the results produced were similar to those produced by a real-time spectrum analyzer [Mar02]. ...
... The receiver configuration details are listed in Table 5.9. The values for the resolution and video bandwidth were based on experimental testing results by [Mar02]. As the distance of separation between the piconet and microwave oven increases, the throughput increases and Bluetooth achieves maximum rates at a distance of 10 meters. ...
... Also ageing effects and usage could alter radiation from the oven. Other researches have also shown that different microwave ovens have different spectral characteristics [Mar02]. higher number of channels affected by interference will have a catastrophic effect on the data packets, making it difficult for the correction code used in DM packets to significantly recover data errors. ...
... (2) Power: The Effective Isotropic Radiated Power (EIRP) of residential MWO's can reach a maximum level of 16 to 33 dBm, with an average EIRP of 5 dBm [7]. The radiation pattern of these MWO's is roughly isotropic, while the strongest leakage is usually detected in front of the oven [7,8]. ...
... In reality, MWO leakage is related to many factors, such as type of the oven (see Table I), load of oven, age of the oven, make of the oven, etc. As a result, the MWOL spectrogram is unique for each MWO, differing even among MWO's of similar make and manufacturer [8]. This presents an exploitable feature for MWO-specific recognition (as discussed in Section V). ...
... The existing AM-FM MWOL model employs a fixed RF carrier that undergoes Frequency Modulation (FM) and Amplitude Modulation (AM) sequentially [3]. However, spectrogram measurements show that MWO emissions exhibit frequency wander attributed to fluctuations in the MWO's magnetron tube or effects of the MWO's mechanical stirrer, causing the MWOL center frequency to drift over time [8]. ...
In this paper, an extended AM-FM MWOL model in the context of WLAN interference management is discussed. The MWOL model incorporates the frequency wander effect, which has not been addressed in the existing MWO models. The simulation result provided by this model match real measurements quite well. The MWOL envelope may change considerably when received at different WLAN channels. The results from this work can be used to develop algorithms for WLAN network-based MWOL interference detection, classification, and recognition
... The energy leakage from the residential MWOs usually affects the whole 2.4-GHz band. However, as depicted by various studies [29,35], the RF emissions from MWOs peak at about a 2.45-GHz frequency, while the number and center frequencies of peaks may vary slightly according to the specific model, as shown in [36]. As a result, the IEEE 802.15.4 Channels 20 and 21 have a high probability of being strongly affected by the MWO operation. ...
... In particular, the eight channels 16-23 seem to offer the best chance for microwave detection, while Channel 21 shows the maximum classification accuracy. This is because, as reported in [36] and the references therein, the residential MWOs have an emission peak frequency around 2.45 GHz, which corresponds to Channel 20 in the IEEE 802.15.4 mapping. In this case, we are likely to be experiencing an MWO with center emission frequency at 2.455 GHz, which consequently triggers a very high detection rate on Channel 21. ...
In recent years, the adoption of industrial wireless sensor and actuator networks (IWSANs) has greatly increased. However, the time-critical performance of IWSANs is considerably affected by external sources of interference. In particular, when an IEEE 802.11 network is coexisting in the same environment, a significant drop in communication reliability is observed. This, in turn, represents one of the main challenges for a wide-scale adoption of IWSAN. Interference classification through spectrum sensing is a possible step towards interference mitigation, but the long sampling window required by many of the approaches in the literature undermines their run-time applicability in time-slotted channel hopping (TSCH)-based IWSAN. Aiming at minimizing both the sensing time and the memory footprint of the collected samples, a centralized interference classifier based on support vector machines (SVMs) is introduced in this article. The proposed mechanism, tested with sample traces collected in industrial scenarios, enables the classification of interference from IEEE 802.11 networks and microwave ovens, while ensuring high classification accuracy with a sensing duration below 300 ms. In addition, the obtained results show that the fast classification together with a contained sampling frequency ensure the suitability of the method for TSCH-based IWSAN.
... P.Sebastian et al.proposed a food intake recognition method via investigating acoustics of chewing different kinds of food[12]. Actually, the research on the power leakage of the microwave oven has been conducted on energy harvesting[3]and WLAN network communication quality[13]. In this paper, we explore the usage of microwave oven leakage for food recognition. ...
... As for the case utilizing 184 features, we show the five most important features with different recognition distances and down sampling frequencies inTable 9. The feature number corresponds to the number inTable 3. The feature number with the suffix[0][1][2][3][4][5][6][7][8][9][10][11][12]stands for the feature extracted from the first raw data frame while the suffix[12][13][14][15][16][17][18][19][20][21][22][23][24]and[24][25][26][27][28][29][30][31][32][33][34][35][36]stand for the features of the second and third frames respectively. The feature number with no suffix stands for the feature of all-time-length raw data. ...
In this paper, we demonstrate a food recognition method by monitoring power leakage from a domestic microwave oven. Universal Software Radio Peripheral (USRP) is applied as a low-cost spectrum analyzer to measure the microwave oven leakage as received signal strength indication (RSSI). We aim to recognize 18 categories of food that are commonly cooked in a microwave oven. By analyzing 180 features that contain the information of heating-time difference, we attain an average recognition accuracy of 82.3%. Using 138 features excluding the heating-time difference information, the average recognition accuracy is 56.2%. The recognition accuracy under different conditions is also investigated, for instance, utilizing different microwave ovens, different distances between the microwave oven and the USRP as well as different data down-sampling rates. Finally, a food recognition application is implemented to demonstrate our method.
... A microwave oven can cause electromagnetic interference to a Bluetooth piconet [4]. However, when a microwave oven is compared to a Wi-Fi network in terms of frequency, space, and time, the Wi-Fi network will have a higher probability to cause interference to a Bluetooth piconet than a microwave oven. ...
... The EIRP of microwave ovens can range from 16 dBm to 33 dBm [6]. The higher power of the microwave oven increases the separation distance that a Bluetooth piconet must maintain to avoid ©2014 IEEE Electromagnetic Compatibility Magazine – Volume 3 – Quarter 3 interference; however, if the Bluetooth piconet is farther than 5m from the microwave, the Bluetooth performance does not degrade [4]. In terms of time, a microwave oven has a maximum duty cycle of 45% [7] compared to Wi-Fi having a maximum duty cycle of 80-90%, resulting in Wi-Fi having a higher probability of interfering with a Bluetooth network. ...
M edical device manufacturers are integrating wireless communication into medical devices at an increasing rate, specifically in the 2.4 GHz industrial, scientific, and medical (ISM) band [1]. The increased use of the 2.4 GHz ISM band is fostered by the economic benefits of inexpensive wireless chipsets and the capability to communicate with other devices exploiting standard wireless technology. From a sample of 326 wireless medical devices cleared by the Food and Drug Administration (FDA), more than half of the wire-less medical devices incorporate Bluetooth (26%) or Wi-Fi 2 (31%), both of which use the 2.4 GHz ISM band, and data suggests that those percentages will increase over time. With increased usage of the unlicensed 2.4 GHz ISM band, the probability of wireless interference increases. Additionally, the Association for the Advancement of Medical Instrumentation (AAMI) wireless work-shop group in October 2012 [2] targeted wireless communication interference as a significant potential problem in healthcare. A challenge of incorporating wireless communication into a medi-cal device is ensuring reasonable medical device effectiveness and patient safety. Presently, there is no test standard to evaluate wireless medical device communication coexistence. Electromag-netic compatibility (EMC) test houses have started to offer wire-less coexistence testing to medical device manufacturers, but without a consensus standard, test methods and reports vary from one EMC test house to another. To remedy this, the American National Standards Institute (ANSI) and AAMI have each formed working groups with the FDA to create complimentary documents addressing wireless coexistence. However, a standard is likely years from completion. The rapidly increasing use of Bluetooth in medical devices calls for more immediate development of a coex-istence test methodology. Therefore, we have developed a method to evaluate a Bluetooth wireless medical device operating in the 2.4 GHz ISM band that is easily adoptable by test engineers from EMC test houses and medical device manufacturers. The wireless coexistence test method is applicable for Bluetooth 1.0, 2.0, 3.0, and 4.0 (Bluetooth Low Energy). The general process can also serve as a foundation for coexistence testing of other wireless technologies. The test method presented in this paper will allow medical device manufacturers to incorporate coexistence testing during the design phase, ultimately decreasing the likelihood of wireless interference, ensuring increased patient safety, and
... The interference and coexistence problems between Bluetooth and WLAN devices were studied [4], [5], [6], [7], [8]. The interference to Bluetooth devices from other communication devices operating in 2.4 GHz ISM band was measured in [9]. Moreover, the interference to WLAN devices from other communication devices operating in the 2.4 GHz ISM band was measured in [10]. ...
... Ideally, the magnetron generates continuous waves centered at 2.45GHz, exactly in the middle of the ISM band. In practice, the power spectrum of the microwave oven varies in frequency (frequency wander) and can show side-bands (or multiple interfering tones) at other frequencies in the ISM band [9]. Hence, the microwave oven operates mainly in the 2.45 GHz, but the operation band varies with time.Fig. ...
As a ubiquitous network era is approaching, the demand for ubiquitous wearable computer terminals is higher to support diverse services. Many types of communication devices, such as WLAN, Zigbee, CDMA, and WiBro are expected to be integrated in a single wearable computer terminal. However, both wireless local area network (WLAN) and wireless personal area network (WPAN) devices may coexist in the 2.4 GHz ISM band. Even other devices like a microwave oven may interfere with WLAN and WPAN devices. Since there is no central control coordinator among them, they can interfere with each other. Therefore, the effect of interference and coexistence problems among them become very important and urgent issues. In this paper, we investigate the effect of mutual interference among Zigbee devices, WLAN devices, and a microwave oven operating in the 2.4 GHz ISM band. We focus on the effect of mutual interference from WLAN devices and a microwave oven on Zigbee devices and measure the performance of Zigbee devices in terms of frame error rate (FER). Experimental results show that the mutual interference degrades the FER performance of Zigbee. To overcome this interference, we propose a coexistence algorithm for Zigbee devices. The performance of the proposed coexistence algorithm is better than for the system without it. Therefore, it can be applied as a coexistence solution in the 2.4 GHz ISM band where several types of devices interfere with one another.
... An important difference between the WLAN and the microwave interference lies in their respective transmission cycles. While the WLAN devices rely on opportunistically gaining the control of the channel when it is vacant, the microwave oven operates at a fixed, pre-decided duty cycle ranging from 30 − 50 % [6] [7]. Thus, by knowing the type of the interferer, the WSN can choose its transmission channel and reporting frequency so that there is minimum network interference. ...
... Interestingly, unlike the WLAN, the degraded channels are not contiguous. As seen inFigure 2(c), Our findings are consistent with [6] on the effect of microwave devices on Bluetooth, which has a similar channel structure as defined in the IEEE 802.15.4 standard. We next propose an algorithm for identifying the presence of these interferers based on their power spectral signatures. ...
Wireless sensor networks (WSNs) are being increasingly deployed in office blocks or residential areas for commercial applications, such as home automation, meter reading, surveillance, among others. At these locations, the WSNs experience interference in the 2.4 GHz unlicensed band due to wireless LANs (WLANs) and commercial microwave devices, leading up to 92% packet losses. In this paper, an algorithmic framework is proposed, that allows the sensor nodes to identify the type of the interferer and its operational channel, so that the former may adapt their own transmission to reduce packet losses in the network. Our proposed interference classification approach comprises of an (i) offline measurement of the spectral characteristics of the WLAN and microwave devices to obtain a reference spectrum shape, and (ii) matching the observed spectral pattern during network operation with the stored reference shape The knowledge of the interferer characteristics is then leveraged by the sensor nodes to decide their transmission channel, packet scheduling times and sleep-awake cycles. Results reveal that our approach incurs up to 50 - 70% energy savings in the WSN, by reducing interference related packet losses.
... • Microwave oven -radiates a spectrum centered at 2.45 GHz, which can act as a severe source of interference in the 2.4 GHz ISM band. The output cycle is tied to the 50 Hz AC input cycle [13] and therefore shows a period of 20 ms. ...
Nowadays Internet-of-Things and Industry 4.0 devices are often connected wirelessly. Current wireless sensor network (WSN) deployments are relying in most cases on the industrial, scientific and medical (ISM) bands without centralized resource scheduling. Thus, each device is a potential source of interference to other devices, both within its own WSN but also to devices in other collocated WSNs. If the transmission behaviour of devices from other WSNs is not random, we are able to find patterns in the time domain in their channel access. This is for example possible for periodic channel access, which is quite common for WSNs with demanding low-power and reliability requirements. The main goal of this work is to detect multiple sources of periodic interference in time slotted signal level measurements and estimate the time windows of future transmissions. This gives a WSN a certain understanding of the radio surrounding and can be used to adapt the transmission behaviour to thus avoid collisions. For this, the Multi Hypothesis Tracking algorithm is adapted and used together with timeslot-based interference measurements on low-cost sensor nodes. The applicability of the algorithm is shown with extensive simulations and the performance is demonstrated with measurements on a time division multiple access based WSN built upon the Bluetooth Low Energy physical layer.
... More importantly, it has been used in home environment and hence its potential applications cannot be over emphasized. The 2.4 GHz frequency band is primarily dedicated for industrial, scientific and medical (ISM) usage [1], [2]. Hence the electromagnetic radiation from other equipment operating in the same frequency band could cause interference and subsequently degrades the performance of the wireless network. ...
The demand for broadband wireless communication in home and office has been increasing exponentially; thus, the need for reliable and effective communication is very crucial. Both theoretical and experimental investigations have clearly shown that electromagnetic radiation from external sources such as microwave oven (MWO) has detrimental impact on the wireless medium and the media content. Therefore, this drastically degrade the signal strength in wireless link and consequently affects the overall throughput due to noise and interference. This experimental study is primarily aimed at critically analyzing and evaluating the impact of electromagnetic radiation on spectrum utilization under different experimental scenarios. The experimental results clearly show that electromagnetic noise radiation from microwave oven can seriously affect the performance of other devices operating in 2.4GHz frequency band, especially, delay sensitive applications and services.
... Those standards are widely adopted by consumer devices for indoor environments and they cause interference for the IEEE 802.15.4-compliant devices. In addition, microwave ovens can cause interference in the same ISM band [4][5][6]. Interference issues can be very severe with the increasing number of devices operating in the 2.4 GHz ISM band since 2.4 GHz is the only global ISM band. Therefore, coexistence arises as a big challenge especially for the IEEE 802.15.4-compliant devices because of their relatively low transmission power, data rate, and buffer capacity. ...
Coexistence is among the most significant challenges for IEEE 802.15.4-compliant devices in indoor environments. Previous works have shown that IEEE 802.11-compliant devices are the major sources of interference in the 2.4 GHz industrial, scientific, and medical band. In order to overcome the coexistence problem, IEEE 802.15.4-compliant devices should monitor the communication channel and access the channel when it is not in use. In this study, the impact of IEEE 802.11 traffic on IEEE 802.15.4 communication is analyzed and a novel predictive channel access scheme, PRESCIENT (PREdictive channel access SCheme for IEee 802.15.4-compliaNT devices), is proposed. The performance evaluation of the proposed scheme is performed using real-world radio frequency signal strength measurements. The results show that the proposed scheme achieves significant performance improvement in terms of channel access under IEEE 802.11 interference.
... At one Fig. 1 e GHP meter used to measure the power intensity, electric and magnetic fields in some House. 2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 meter, there is very little radiation left (Kitamura, de Silva, Yamasaki, & Aizawa, 2010). Fig. 2 show the leak radiation for oven type, here power density was showed with distance, when distance is equal to zero power density is vanish, when increase distance power density increase until higher point reached (500 mw/m 2 ), then later it is decrease with increasing distance because the effect type of oven, at higher point is very less than compared with standard (10 7 mw/m 2 ), results appear that the leak of radiation oven has no harmful for that person who are using this oven (Rondeau, D'Souza, & Sweeney, 2004). Fig. 3 and Table 2 shows that the leak radiation for (Mrphy.Richard) oven type, here power density was showed with distance, when distance is equal to zero power density is vanish, but when increase distance power density is increase until near (600 mw/m 2 ) which represent maximum intensity of radiation produce from oven, then intensity later becomes constant (Kawahara et al., 2013). ...
Background: Microwaves are a form of electromagnetic energy, like light waves or radio
waves, and occupy a part of the electromagnetic spectrum of power, or energy. Microwaves
are very short waves of electromagnetic energy that travel at the speed of light (186,282
miles per second). In our modern technological age, microwaves are used to relay long
distance telephone signals, television programs, and computer information across the
earth or to a satellite in space. But the microwave is most familiar to us as an energy source
for cooking food.
The aim: of this research is to measurement the radiation leak from different types of
electromagnetic oven for some type oven in Erbil city can be measured, that affect to the
human health.
Materials & methods: This study is performed for the first time in some houses in Erbil (the
capital of Iraq Kurdistan region) using an Electromagnetic field strength meter device
measuring electric field, magnetic field and radiation intensity in eight homes in Erbil.
Results & Discussions: The measurements have been done at some houses in Erbil city,
according to the source of background radiation exist before measuring data. Our data
compared with standard safe range of radiation data. Results showed that there is radiation
leak form all type of electromagnetic oven and all at the order of safety compared with
standard value.
Copyright © 2015, The Egyptian Society of Radiation Sciences and Applications. Production
and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
... Yamasaki, & Aizawa, 2010). Fig. 2 show the leak radiation for oven type, here power density was showed with distance, when distance is equal to zero power density is vanish, when increase distance power density increase until higher point reached (500 mw/m 2 ), then later it is decrease with increasing distance because the effect type of oven, at higher point is very less than compared with standard (10 7 mw/m 2 ), results appear that the leak of radiation oven has no harmful for that person who are using this oven (Rondeau, D'Souza, & Sweeney, 2004). Fig. 3 and Table 2 shows that the leak radiation for (Mrphy.Richard) oven type, here power density was showed with distance, when distance is equal to zero power density is vanish, but when increase distance power density is increase until near (600 mw/m 2 ) which represent maximum intensity of radiation produce from oven, then intensity later becomes constant ( Kawahara et al., 2013). ...
Background: Microwaves are a form of electromagnetic energy, like light waves or radio waves, and occupy a part of the electromagnetic spectrum of power, or energy. Microwaves are very short waves of electromagnetic energy that travel at the speed of light (186,282 miles per second). In our modern technological age, microwaves are used to relay long distance telephone signals, television programs, and computer information across the earth or to a satellite in space. But the microwave is most familiar to us as an energy source for cooking food.
The aim: of this research is to measurement the radiation leak from different types of electromagnetic oven for some type oven in Erbil city can be measured, that affect to the human health.
Materials & methods: This study is performed for the first time in some houses in Erbil (the capital of Iraq Kurdistan region) using an Electromagnetic field strength meter device measuring electric field, magnetic field and radiation intensity in eight homes in Erbil.
Results & Discussions: The measurements have been done at some houses in Erbil city, according to the source of background radiation exist before measuring data. Our data compared with standard safe range of radiation data. Results showed that there is radiation leak form all type of electromagnetic oven and all at the order of safety compared with standard value.
... Avoiding the power leakage, which mainly occurs through the door, has been a key issue [25,26], and that is why special attention has been paid to the design of the oven door [27][28][29][30]. Typically, the leakage has been treated as interference for devices like pacemakers [31] and wireless communication systems (Wifi, ZigBee, and Bluetooth), as the microwave oven operates in the ISM (industrial, scientific, and medical) frequency band of 2.4 GHz [32][33][34]. But there are more scenarios where the leakage of the oven has been analyzed, as restaurants, where microwave ovens are more powerful [35], or in highly confined scenarios, such as airplanes [36]. ...
The electromagnetic field leakage levels of nonionizing radiation from a microwave oven have been estimated within a complex indoor scenario. By employing a hybrid simulation technique, based on coupling full wave simulation with an in-house developed deterministic 3D ray launching code, estimations of the observed electric field values can be obtained for the complete indoor scenario. The microwave oven can be modeled as a time-and frequency-dependent radiating source, in which leakage, basically from the microwave oven door, is propagated along the complete indoor scenario interacting with all of the elements present in it. This method can be of aid in order to assess the impact of such devices on expected exposure levels, allowing adequate minimization strategies such as optimal location to be applied.
... In this section, we evaluate the proposed Bluetooth wireless error models using the Markov Chain Monte Carlo (MCMC) method. The Bluetooth Frequency Hopping Selection Kernel [21] in the Matlab environment is used for simulations. Based on the kernel, we implement a packet level burst error channel model and record the state sequence of 20,000 consecutively hopped channels in each simulation run. ...
Data transmission over wireless networks is challenging due to the occurrence of burst errors, and packet loss caused by such
errors seriously limits the maximum achievable throughput of wireless networks. To tailor efficient transmission schemes,
it is essential to develop a wireless error model that can provide insight into the behavior of wireless transmissions. In
this study, we investigate the wireless error model of Bluetooth networks. We study the FHSS feature of Bluetooth using both
ordinary hopping kernels and Adaptive Frequency Hopping (AFH) kernels, and design analytical error models accordingly to capture
the channel behavior of Bluetooth networks. We evaluate the proposed models by comparing the analytical results to the simulation
results obtained by Markov Chain Monte Carlo (MCMC) algorithms. The results show that our analytical models can represent
the channel behavior of Bluetooth networks in all test cases.
KeywordsBluetooth–Error model–Markov Chain Monte Carlo–Gilbert-Elliot model
... In this section, we evaluate the proposed Bluetooth wireless error models using the Markov Chain Monte Carlo (MCMC) method. The Bluetooth Frequency Hopping Selection Kernel [9] in the Matlab environment is used for simulations. Based on the kernel, we implement a packet level burst error channel model and record the binary hopping sequence. ...
Data transmission over wireless networks is challeng- ing due to the occurrence of burst errors, and packet loss caused by such errors seriously limits the maximum achiev- able throughput of wireless networks. To tailor efficient transmission schemes, it is essential to develop a wireless error model that can provide insight into the behavior of wireless transmissions. In this study, we investigate the wireless error model of Bluetooth networks. We study the FHSS feature of Bluetooth using both ordinary hopping ker- nels and Adaptive Frequency Hopping (AFH) kernels, and design analytical error models accordingly to capture the channel behavior of Bluetooth networks. We evaluate the proposed models by comparing the analytical results to the simulation results obtained by Markov Chain Monte Carlo (MCMC) algorithms. The results show that our analytical models can represent the channel behavior of Bluetooth net- works in all test cases.
... Bluetooth short range and low power characteristics enable its interfaces to have a very small footprint and affordable cost, making it perhaps the preferred technology for connecting peripheral devices. However, its limited bandwidth, very short range and unlicensed band (ISM) operation, hence prone to interference [24], makes Bluetooth technology unsuitable for high bandwidth CE applications such as high definition video streaming. Moreover, its voice support does not warrant Bluetooth to transmit high quality audio, a must in most consumer electronics applications. ...
This paper evaluates various networking technologies to satisfy audio/video requirements in the home. It further advocates Ethernet as the backbone network technology in the home, identifying necessary enhancements so as to accommodate consumer electronics applications, in addition to computer devices.
... Our proposed approach goes further in this direction by allowing the sensor node to not only classify the origin of the power source as a ZigBee device or interferer, but also its type, if the latter case is true. While the WLAN devices rely on opportunistically gaining control of the channel when it is vacant, the microwave oven operates at a fixed, pre-decided duty cycle ranging from 30 − 50 % [64][78]. Thus, by knowing the interferer-type, the WSN can choose its transmission channel and reporting frequency so that there is minimum network interference. ...
Cognitive radio (CR) technology allows devices to share the wireless spectrum with other users that have a license for operation in these spectrum bands. This area of research promises to solve the problem of spectrum scarcity in the unlicensed bands, and improve the inefficient spectrum utilization in the bands reserved for the licensed users. However, the opportunistic use of the available spectrum by the CR users must not affect the licensed users. This raises several concerns regarding spectrum sensing, sharing and reliable end-to-end communication in CR networks. This thesis is concerned with the design and implementation of communication protocols for the multi-hop infrastructure-less CR ad-hoc networks (CRAHNs). In addition, it also addresses the critical issue of interference-free spectrum usage in specific ad-hoc architectures, such as, resource-constrained wireless sensor networks and wireless mesh networks that have high traffic volumes. The problems of spectrum management that are unique to CR networks are first identified in this thesis. These issues are then addressed at each layer of the network protocol stack while considering the distributed operation in CRAHNs. At the physical layer an algorithmic suite is proposed that allows the CR devices to detect and adapt to the presence of wireless LANs and commercial microwave ovens. A common control channel is designed that allows sharing of the spectrum information between the CR users, even when the available spectrum varies dynamically. A spectrum sharing scheme for mesh networks is proposed at the link layer that allows cooperative detection of the licensed users and fair utilization of the available spectrum among the mesh devices. The spectrum availability and route formation are then considered jointly at the network layer, so that the licensed users are protected as well as the CRAHN performance is maximized. Finally, we extend the classical TCP at the transport layer to ensure end-to-end reliability in a multi-hop CR environment. Ph.D. Committee Chair: Akyildiz, Ian; Committee Member: Ingram, Mary Ann; Committee Member: Blough, Douglas; Committee Member: Dovrolis, Konstantinos; Committee Member: Li, Ye
... Bluetooth short range and low power characteristics enable its interfaces to have a very small footprint and affordable cost, making it perhaps the preferred technology for connecting peripheral devices. However, its limited bandwidth, very short range and unlicensed band (ISM) operation, hence prone to interference [20], makes Bluetooth technology unsuitable for high bandwidth CE applications such as high definition video streaming. Moreover, its voice support does not warrant Bluetooth to transmit high quality audio, a must in most consumer electronics applications. ...
The rapid proliferation of wireless networks poses a great challenge of effective coexistence management amongst a plethora of wireless communication protocol users that are co-located and contending for the ever scarce spectrum available. For effective spectrum utilization and optimum performance of existing wireless networks and for the realization of new wireless networks, coexistence management of the wireless spectrum is the key to ensure the performance of multiple wireless networks in close proximity. This paper provides a comprehensive review of state-of-the-art coexistence protocols in wireless networks. The paper not only discusses wireless interference detection techniques in detail but also provides various coping mechanisms to counter the interference.
The proliferation of embedded systems, wireless technologies, and Internet protocols have enabled the Internet of Things (IoT) to bridge the gap between the virtual and physical world through enabling the monitoring and actuation of the phys5 ical world controlled by data processing systems. Wireless tech6 nologies, despite their offered convenience, flexibility, low cost, and mobility pose unique challenges such as fading, interference, energy, and security, which must be carefully addressed when using resource-constrained IoT devices. To this end, the efforts of the research community have led to the standardization of several wireless technologies for various types of application domains depending on factors such as reliability, latency, scalability, and energy efficiency. In this paper, we first overview these standard wireless technologies, and we specifically study the MAC and physical layer technologies proposed to address the requirements and challenges of wireless communications. Furthermore, we explain the use of these standards in various application domains, such as smart homes, smart healthcare, industrial automation, and smart cities, and discuss their suitability in satisfying the requirements of these applications. In addition to proposing guidelines to weigh the pros and cons of each standard for an application at hand, we also examine what new strategies can be exploited to overcome existing challenges and support emerging IoT applications.
This paper describes a feature optimization for a novel food recognition system based on the analysis of the power leakage from a microwave oven. Some microwave energy leak from the microwave oven and the leakage pattern changes according to the contents of the microwave oven and also the condition of these meals. Therefore, we collected the received signal strength indicator (RSSI) values during the heating process and analyzed these data by using machine learning method. We also evaluated the importance of each features to clarify which features are useful for food recognition or not. In the results, our study has successfully demonstrated that we can recognize what food is cooked in the microwave oven by monitoring the leakage.
Wireless operators will find this practical, hands-on guide to network deployment invaluable. Based on their own extensive experience, the authors describe an end-to-end network planning process to deliver the guaranteed Quality of Service (QoS) that enables today's wireless IP services such as VoIP, WWW and streaming video. With a focus on practical design, comprehensive examples are provided for • GSM/GPRS/EDGE • UMTS/HSDPA • OFDM • Mesh Wifi • Packet backhaul Topics addressed include: • capacity/peak data rates, • service latency • link budgets • lifecycle costs • network optimisation The trade-off between enhanced user experience and operator cost is explored in the context of an enhanced business model. Suitable for radio and core network planners, designers, optimizers, and business development staff at operators and network equipment manufacturers, the book's extensive references also make it a useful resource for graduate and postgraduate students. © Cambridge University Press 2009 and 2008. All rights reserved.
In this paper, we demonstrate a food recognition method by monitoring power leakage from a domestic microwave oven. Universal Software Radio Peripheral (USRP) is applied as a low-cost spectrum analyzer to measure the microwave oven leakage as received signal strength indication (RSSI). We aim to recognize 18 categories of food that are commonly cooked with a microwave oven. By analyzing 184 features designed after analyzing the features of measured RSSI, we attain an average recognition accuracy of 82.3% with various distances between the microwave oven and the USRP and different data downsampling frequencies for raw data processing.
Cardiovascular diseases are the leading cause of death in the United States. Advances in wireless technology have made possible the remote monitoring of a patient's heart sensors as part of a body area network. Some of these networks use a Bluetooth Low Energy (BLE) component to transmit the signal between the bio sensors and a smart phone. This study investigates the impact that stray wireless transmissions from residential microwave ovens have on the BLE component of the body area network. The results of this study may lead to improvements and widespread use of body area network medical systems, which may lead to better monitoring, more data, and fewer fatalities due to misdiagnosed heart conditions.
In situ exposure of electric fields of 11 microwave ovens is assessed in an occupational environment and in an office. Measurements as a function of distance without load and with a load of 275 ml of tap water were performed at distances of <1 m. The maximal measured field was 55.2 V m(-1) at 5 cm from the oven (without load), which is 2.5 and 1.1 times below the International Commission on Non-Ionizing Radiation Protection reference level for occupational exposure and general public exposure, respectively. For exposure at distances of >1 m, a model of the electric field in a realistic environment is proposed. In an office scenario, switching on a microwave oven increases the median field strength from 91 to 145 mV m(-1) (+91 %) in a traditional Wireless Local Area Network (WLAN) deployment and from 44 to 92 mV m(-1) (+109 %) in an exposure-optimised WLAN deployment.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
In this paper, the noise resistance of two wireless robot cars is analyzed empirically. ZigBee and Bluetooth robot cars are driven remotely under interference conducted by microwave ovens, Bluetooth transmissions, and WLAN (Wireless Local Area Network) traffic. In each interference case, the occupied bandwidth is measured separately. Both robot cars are driven under the interference of all interference sources, and both noise resistance and operation of the robot cars are evaluated.
In this work, the impact of radiofrequency radiation leakage from microwave ovens and its effect on 802.15.4 ZigBee-compliant wireless sensor networks operating in the 2.4 GHz Industrial Scientific Medical (ISM) band is analyzed. By means of a novel radioplanning approach, based on electromagnetic field simulation of a microwave oven and determination of equivalent radiation sources applied to an in-house developed 3D ray launching algorithm, estimation of the microwave oven’s power leakage is obtained for the complete volume of an indoor scenario. The magnitude and the variable nature of the interference is analyzed and the impact in the radio link quality in operating wireless sensors is estimated and compared with radio channel measurements as well as packet measurements. The measurement results reveal the importance of selecting an adequate 802.15.4 channel, as well as the Wireless Sensor Network deployment strategy within this type of environment, in order to optimize energy consumption and increase the overall network performance. The proposed method enables one to estimate potential interference effects in devices operating within the 2.4 GHz band in the complete scenario, prior to wireless sensor network deployment, which can aid in achieving the most optimal network topology.
Number of indoor Wireless Sensor Network (WSN) applications are increasing day by day. However, there are many interferers (like 802.11 × and 802.15.4 devices) effecting 2.4 GHz band. Moreover, co-existence is a bigger challenge for WSNs because of their tiny structure and resource constraints. In this paper, a novel method is proposed to predict the near future channel quality using the statistical channel noise history. By using the prediction method, WSN node channel access can be scheduled when the channel is free in order to increase performance. In this paper, first, noisy channels are analyzed to find a prediction metric. Then, with the help of the prediction algorithm developed, channel access is performed. The results obtained from the test bed show that our approach incurs up to 60% to 90% reduction in noisy channel access which satisfies less packet loss and less interference with non-WSN communications.
The traditional system of radio spectrum allocation has inefficiently restricted wireless services. Alternatively, liberal licenses ceding de facto spectrum ownership rights yield incentives for operators to maximize airwave value. These authorizations have been widely used for mobile services in the U.S. and internationally, leading to the development of highly productive services and waves of innovation in technology, applications and business models. Serious challenges to the efficacy of such a spectrum regime have arisen, however. Seeing the widespread adoption of such devices as cordless phones and wi-fi radios using bands set aside for unlicensed use, some scholars and policy makers posit that spectrum sharing technologies have become cheap and easy to deploy, mitigating airwave scarcity and, therefore, the utility of exclusive rights. This paper evaluates such claims technically and economically. We demonstrate that spectrum scarcity is alive and well. Costly conflicts over airwave use not only continue, but have intensified with scientific advances that dramatically improve the functionality of wireless devices and so increase demand for spectrum access. Exclusive ownership rights help direct spectrum inputs to where they deliver the highest social gains, making exclusive property rules relatively more socially valuable. Liberal licenses efficiently accommodate rival business models (including those commonly associated with unlicensed spectrum allocations) while mitigating the constraints levied on spectrum use by regulators imposing restrictions in traditional licenses or via use rules and technology standards in unlicensed spectrum allocations.
The large number of passive components in mobile electronics devices require a large area. In this study, the passive components on the test chip are processed using a commercial CMOS process. The layout area is reduced by superimposing the on-wafer passive components of the basic inductor-capacitor and inductor-resistor circuits. The resonant frequency of the LC circuit using the stacked components matches well with the calculated value of the reference components. The effect of the parasitic components between the stacked passive components is found negligible in the operating frequency range.
A new radio interface named Bluetooth has been developed to
provide short range connectivity between various consumer devices. The
Bluetooth system operates in the unlicensed 2.45 GHz ISM band and
applies frequency hopping over 79 carriers. This paper presents the
simulation results of the radio network performance of a large number of
co-located Bluetooth units. For a capacity-demanding WWW data traffic
model, the interference caused by (on average) 100 concurrent sessions
in a single room of size 10 m×20 m results only in a 5%
degradation of the aggregate throughput. In general, it is advisable to
use long uncoded packet types for data transmission since they have the
largest ideal throughput and therefore generate the least interference
power. For real-time speech links, frame erasures represent the dominant
reason for transmission quality degradation, more than residual payload
bit errors. It is thus advisable to use the provided uncoded packet type
in order to allow for the largest capacity; a system load of about 30
Erlang yields an average frame erasure rate of 1%
An interesting scheme that can be pursued to improve the bit-error performance of indoor wireless networks (such as Bluetooth™) in close proximity to other ISM devices (such as microwave ovens) is a technique of imposing a random, orthogonal polarization on each hopped-frequency packet transmitted. Furthermore, a polarization-control alert on the operating Bluetooth units can be adopted whenever the microwave oven specified electromagnetic interference (EMI) occurs. In response to this alert, the Bluetooth units can transmit and receive in predominantly horizontal polarization mode, until the oven is off (this will enable a diversity against the predominantly vertical polarization of EM emissions from the ovens). This article proposes a relevant strategy for a coexisting scenario of Bluetooth transmissions and nearby leakage from a microwave oven.
Much discussion has taken place over the last several years about the tremendous growth potential for low power microwave chip devices for low power, unlicensed communications within the 2450 MHz band. Techniques for wireless communication consist of frequency hopping spread spectrum (FHSS) and direct sequence spread spectrum (DSSS). The generic name Bluetooth has recently been utilized to encompass all these types of devices even though it strictly applies only to FHSS. While the economic potential for such technology is undisputed, there is reason to believe that the wireless industry is not aware of the problems that are looming on the horizon in the form of interference from consumer and commercial microwave ovens and industrial microwave equipment installations. These types of non-communications equipment are operating legally in the industrial, scientific, and medical (ISM) bands and present spectra that are quite variable, and in many cases have quite high amplitudes. This article outlines the background and problems that exist and enjoins the two industries to work together to resolve the compatibility issues.
Commercial microwave ovens as applied in restaurants have two
magnetron tubes and compared to domestic kitchen counterparts they
spread the higher RF power and radiated heating energy more evenly. The
domestic kitchen or residential microwave ovens have only one magnetron
tube. The interference from the commercial type of microwave ovens is
more difficult to characterise than the interference from the
residential ones. The commercial type of microwave ovens radiate a
CW-like interference that sweeps over tens of MHz during the two bursts
per mains power cycle. The residential ones give a CW-like interference
that has a more or less stable frequency near 2.45 GHz occurring once
per mains power cycle. The impact of the interference from the
commercial type of microwave ovens on wireless LANs conforming the IEEE
802.11 standard for both DSSS (direct sequence spread spectrum) and FHSS
(frequency hopping spread spectrum) has been evaluated
We focus on key issues associated with ensuring the reliability of
spread-spectrum communication systems in the 2.4 GHz ISM band. To this
end, we present a characterization of the emissions from microwave ovens
which are the most ubiquitous interference sources in this segment of
the spectrum. Clarifying the nature of these interferers facilitates the
development of deployment planning tools that take location specific
interference levels into account in determining radio link feasibility
and reliability. An understanding of the detailed structure in such
interference also leads to optimism about the possibility of using
interference cancellation techniques to mitigate their impact on
wideband spread-spectrum communication systems operating in this ISM
band
This paper presents a probabilistic treatment of the performance of a Bluetooth piconet under cochannel interference from other Bluetooth piconets. An upper bound on the packet error rate of a link is given, as well as a lower bound on the aggregated throughput of n collocated piconets.
Radio spectrum measurements of individual microwave ovens
- P E Gawthrop
- F H Sanders
- K B Nebba
- J J Sell
P.E.Gawthrop, F.H. Sanders, K.B. Nebba, and J.J. Sell, "Radio
spectrum measurements of individual microwave ovens," NTIA Report
94-303-2.
Block and Convolutional Channel Codes
- J G Proakis
J.G. Proakis, "Block and Convolutional Channel Codes," in Digital
Communications, 4th ed., New York: McGraw-Hill, 2001, pp. 416-547.