Effect of pedestrian movement on MIMO-OFDM channel capacity in an indoor environment

The rapid growth of mobile telephone use, satellite services, and now the wireless Internet and WLANs are generating tremendous changes in telecommunication and networking. As indoor wireless communications become more prevalent, modeling indoor radio wave propagation in populated environments is a topic of significant interest. Wireless MIMO communication exploits phenomena such as multipath propagation to increase data throughput and range, or reduce bit error rates, rather than attempting to eliminate effects of multipath propagation as traditional SISO communication systems seek to do. The MIMO approach can yield significant gains for both link and network capacities, with no additional transmitting power or bandwidth consumption when compared to conventional single-array diversity methods. When MIMO and OFDM systems are combined and deployed in a suitable rich scattering environment such as indoors, a significant capacity gain can be observed due to the assurance of multipath propagation. Channel variations can occur as a result of movement of personnel, industrial machinery, vehicles and other equipment moving within the indoor environment. The time-varying effects on the propagation channel in populated indoor environments depend on the different pedestrian traffic conditions and the particular type of environment considered. A systematic measurement campaign to study pedestrian movement effects in indoor MIMO-OFDM channels has not yet been fully undertaken. Measuring channel variations caused by the relative positioning of pedestrians is essential in the study of indoor MIMO-OFDM broadband wireless networks. Theoretically, due to high multipath scattering, an increase in MIMO-OFDM channel capacity is expected when pedestrians are present. However, measurements indicate that some reductions in channel capacity could be observed as the number of pedestrians approaches 10 due to a reduction in multipath conditions as more human bodies absorb the wireless signals. This dissertation presents a systematic characterization of the effects of pedestrians in indoor MIMO-OFDM channels. Measurement results, using the MIMO-OFDM channel sounder developed at the CSIRO ICT Centre, have been validated by a customized Geometric Optics-based ray tracing simulation. Based on measured and simulated MIMO-OFDM channel capacity and MIMO-OFDM capacity dynamic range, an improved deterministic model for MIMO-OFDM channels in indoor populated environments is presented. The model can be used for the design and analysis of future WLAN to be deployed in indoor environments. The results obtained show that, in both Fixed SNR and Fixed Tx for deterministic condition, the channel capacity dynamic range rose with the number of pedestrians as well as with the number of antenna combinations. In random scenarios with 10 pedestrians, an increment in channel capacity of up to 0.89 bits/sec/Hz in Fixed SNR and up to 1.52 bits/sec/Hz in Fixed Tx has been recorded compared to the one pedestrian scenario. In addition, from the results a maximum increase in average channel capacity of 49% has been measured while 4 antenna elements are used, compared with 2 antenna elements. The highest measured average capacity, 11.75 bits/sec/Hz, corresponds to the 4x4 array with 10 pedestrians moving randomly. Moreover, Additionally, the spread between the highest and lowest value of the the dynamic range is larger for Fixed Tx, predicted 5.5 bits/sec/Hz and measured 1.5 bits/sec/Hz, in comparison with Fixed SNR criteria, predicted 1.5 bits/sec/Hz and measured 0.7 bits/sec/Hz. This has been confirmed by both measurements and simulations ranging from 1 to 5, 7 and 10 pedestrians.

Characterisation of indoor air organic pollutants in Brisbane

The occurrence and levels of airborne polycyclic aromatic hydrocarbons and volatile organic compounds in selected non-industrial environments in Brisbane have been investigated as part of an integrated indoor air quality assessment program. The most abundant and most frequently encountered compounds include, nonanal, decanal, texanol, phenol, 2-ethyl-1-hexanol, ethanal, naphthalene, 2,6-tert-butyl-4-methyl-phenol (BHT), salicylaldehyde, toluene, hexanal, benzaldehyde, styrene, ethyl benzene, o-, m- and pxylenes, benzene, n-butanol, 1,2-propandiol, and n-butylacetate. Many of the 64 compounds usually included in the European Collaborative Action method of TVOC analysis were below detection limits in the samples analysed. In order to extract maximum amount of information from the data collected, multivariate data projection methods have been employed. The implications of the information extracted on source identification and exposure control are discussed.

A pilot study on the effect of indoor particle sources on indoor particle concentration in residential houses

Characterization of indoor particle sources from 14 residential houses in Brisbane, Australia, was performed. The approximation of PM2.5 and the submicrometre particle number concentrations were measured simultaneously for more than 48 h in the kitchen of all the houses by using a photometer (DustTrak) and a condensation particle counter (CPC), respectively. From the real time indoor particle concentration data and a diary of indoor activities, the indoor particle sources were identified. The study found that among the indoor activities recorded in this study, frying, grilling, stove use, toasting, cooking pizza, smoking, candle vaporizing eucalyptus oil and fan heater use, could elevate the indoor particle number concentration levels by more than five times. The indoor approximation of PM2.5 concentrations could be close to 90 times, 30 times and three times higher than the background levels during grilling, frying and smoking, respectively.

Indoor exposure to submicrometer particles and PM2.5 in residential houses in Brisbane, Australia

As part of a large study investigating indoor air in residential houses in Brisbane, Australia, the purpose of this work was to quantify indoor exposure to submicrometer particles and PM2.5 for the inhabitants of 14 houses. Particle concentrations were measured simultaneously for more than 48 hours in the kitchens of all the houses by using a condensation particle counter (CPC) and a photometer (DustTrak). The occupants of the houses were asked to fill in a diary, noting the time and duration of any activity occurring throughout the house during measurement, as well as their presence or absence from home. From the time series concentration data and the information about indoor activities, exposure to the inhabitants of the houses was calculated for the entire time they spent at home as well as during indoor activities resulting in particle generation. The results show that the highest median concentration level occurred during cooking periods for both particle number concentration (47.5´103 particles cm-3) and PM2.5 concentration (13.4 mg m-3). The highest residential exposure period was the sleeping period for both particle number exposure (31%) and PM2.5 exposure (45.6%). The percentage of the average residential particle exposure level in total 24h particle exposure level was approximating 70% for both particle number and PM2.5 exposure.

Relationship between indoor/outdoor concentrations of particles : a critical review

The relationship between indoor and outdoor concentration levels of particles in the absence and in the presence of indoor sources has been attracting an increasing level of attention. Understanding of the relationship and the mechanisms driving it, as well as the ability to quantify it, are of importance for assessment of source contribution, assessment of human exposure and for control and management of particles. It became particularly important to address this topic when evidence came from epidemiological studies on the close association between outdoor concentration levels of particles and health effects, yet with many studies showing that indoor concentrations could be significantly higher than those outdoors. This paper presents a summary of an extensive literature review on this topic conducted with an aim to identify general trends in relation to the I/O relationship emerging from studies conducted worldwide. The review considered separately a larger body of papers published on PM10, PM2.5, as well as the smaller database on particle number and number or volume size distribution. A specific focus of this paper is on naturally ventilated houses. The conclusion from the review is that despite the multiplicity of factors that play role in affecting the relationship, there are clear trends emerging in relation to the I/O relationship for particle mass concentration, enabling more general predictions to be made about the relationship. However, more research is still needed on particle number concentration and size distribution.

Pedestrians Effects on Indoor MIMO-OFDM Channel Capacity

Temporal variations caused by pedestrian movement can significantly affect the channel capacity of indoor MIMOOFDM wireless systems. This paper compares systematic measurements of MIMO-OFDM channel capacity in presence of pedestrians with predicted MIMO-OFDM channel capacity values using geometric optics-based ray tracing techniques. Capacity results are presented for a single room environment using 5.2 GHz with 2x2, 3x3 and 4x4 arrays as well as a 2.45 GHz narrowband 8x8 MIMO array. The analysis shows an increase of up to 2 b/s/Hz on instant channel capacity with up to 3 pedestrians. There is an increase of up to 1 b/s/Hz in the average capacity of the 4x4 MIMO-OFDM channel when the number of pedestrians goes from 1 to 3. Additionally, an increment of up to 2.5 b/s/Hz in MIMO-OFDM channel capacity was measured for a 4x4 array compared to a 2x2 array in presence of pedestrians. Channel capacity values derived from this analysis are important in terms of understanding the limitations and possibilities for MIMO-OFDM systems in indoor populated environments.

Effect of Pedestrian Movement on MIMO-OFDM Channel Capacity in an Indoor Environment

Effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity have been investigated using experiment and simulation. The experiment was conducted at 5.2 GHz by a MIMO-OFDM packet transmission demonstrator using four transmitters and four receivers built in-house. Geometric optics based ray tracing technique was used to simulate the experimental scenarios. Changes in the channel capacity dynamic range have been analysed for different number of pedestrian (0-3) and antennas (2-4). Measurement and simulation results show that the dynamic range increases with the number of pedestrian and the number of antennas on the transmitter and receiver array.

Mapping of indoor environments by robots using low-cost vision sensors

For robots to operate in human environments they must be able to make their own maps because it is unrealistic to expect a user to enter a map into the robot’s memory; existing floorplans are often incorrect; and human environments tend to change. Traditionally robots have used sonar, infra-red or laser range finders to perform the mapping task. Digital cameras have become very cheap in recent years and they have opened up new possibilities as a sensor for robot perception. Any robot that must interact with humans can reasonably be expected to have a camera for tasks such as face recognition, so it makes sense to also use the camera for navigation. Cameras have advantages over other sensors such as colour information (not available with any other sensor), better immunity to noise (compared to sonar), and not being restricted to operating in a plane (like laser range finders). However, there are disadvantages too, with the principal one being the effect of perspective. This research investigated ways to use a single colour camera as a range sensor to guide an autonomous robot and allow it to build a map of its environment, a process referred to as Simultaneous Localization and Mapping (SLAM). An experimental system was built using a robot controlled via a wireless network connection. Using the on-board camera as the only sensor, the robot successfully explored and mapped indoor office environments. The quality of the resulting maps is comparable to those that have been reported in the literature for sonar or infra-red sensors. Although the maps are not as accurate as ones created with a laser range finder, the solution using a camera is significantly cheaper and is more appropriate for toys and early domestic robots.