This article develops a system for through-wall counting of people walking in a room, based purely on passive reception of the WiFi signals that are generated by devices in that room. We use WiFi compressed beamforming reports, collected using a sniffer node located outside the room. We propose a 2-D discrete Fourier transform (2D DFT) approach for feature extraction. As such, we formulate the counting problem as a multiclass image classification problem. Our proposed system achieves accuracies of 100%, 97.8%, 78.3%, and 93.9% in field trials with zero, one, two, and three people walking inside a room, respectively, even for rooms that were not part of the training set.

This article considers the problem of passive tracking of a noncooperating target indoors. We develop a novel system to localize a moving target using asynchronous self-localizing sniffer nodes, which passively listen to WiFi signals transmitted by the target. The proposed system uses only the time-difference-of-arrival between multipath components (multipath TDoA) at each receiver. This does not require phase synchronization. We develop two novel localization algorithms; one uses batch processing and the other is online. We also design a novel multipath association algorithm. A custom-designed hardware platform is developed to prototype the proposed system. The accuracy of the proposed system is verified experimentally. For signal-to-noise ratio of 10 dB, both proposed algorithms achieve target localization accuracies better than 40 cm with probability 0.95 without needing any knowledge of target or sniffer locations. If the location of one sniffer node is known, the accuracy improves to 15 cm.

This paper considers the problem of stand-off detection of human presence and movement in indoor environments. We develop a novel approach using IEEE 802.11ac compressed beamforming reports (CBRs). In the proposed system, a sniffer device collects CBRs communicated between devices inside an indoor environment by listening to the IEEE 802.11ac channels. We translate the problem into a multi-class image classification problem. We develop a discrete Fourier transform (DFT) based feature extraction technique to generate input features which vary significantly across different classes of the classification problem. The pattern of these interclass variations of extracted features remains consistent across different indoor environments. The proposed system was trained and tested using measurements from offices, meeting rooms and lecture theatres. It achieved an accuracy higher than 90% even for rooms that were not included as part of the training set.

This paper considers target localization from ambient radio frequency (RF) signals transmitted by the target. We consider a new practical scenario with an array of asynchronous receivers deployed at arbitrary locations, and present an algorithm that jointly locates the target and self-locates the receivers. The approach exploits time-difference-of-arrival (TDoA) between multipath components (multipath TDoA) at each receiver. We derive lower bounds for the localization errors of all the target and receiver locations. The performance is verified numerically and demonstrated experimentally with a hardware implementation that was tested in an anechoic chamber using passive IEEE 802.11ac receivers. We have shown that sub-meter level accuracy can be achieved using 6 static receivers.

This paper presents a novel passive tracking system to localize a moving target using asynchronous self-locating receivers, which passively listen to the IEEE 802.11 signals transmitted by the target. We have developed passive single-antenna IEEE 802.11ac receivers that estimate time-difference-of-arrival (TDoA) between multipath components at each receiver, and as such, they do not depend on synchronization between the target and the receivers. We have developed a new localization algorithm based on particle filtering (PF), which completes its execution in real-time within 1 s for each target location to be estimated. The performance is demonstrated experimentally and shown to have a target localization error below 30 cm for all the target locations.

We propose a beamforming technique for the multicell downlink of a multicarrier code division multiple access (MC-CDMA) system with sparse signatures. We propose a distributed beamforming algorithm using the sum-product algorithm. The distributed beamforming algorithm converges very quickly to the centralized beamforming solution, minimizing the delay associated with computation of the transmit vector. The complexity of distributed beamforming depends on the number of base stations (BSs) that are in range of each user, not on the size of the entire network.

The performance of optimum combining (OC) in decode-and forward (DF) relaying in the presence of a Poisson field of interferers is analyzed. An approximation for the outage probability of the OC receiver is derived by considering the temporal correlation of the interference. Despite the randomness of the number and the locations of the interferers, the OC receiver suppresses the interference at the destination node and diversity gains are achieved, provided that the relay nodes are noise limited. For single-antenna relay nodes, the end-to-end performance is vulnerable to interference at the relay nodes which is not canceled, resulting in zero diversity gains.

Spatial point processes are commonly used to model the placement and the number of interferers in modern wireless networks, where the ad hoc deployment of transmitters is common. The homogeneous Poisson point process (PPP) is the most popular spatial point process used to model co-channel interference. Optimum combining (OC) is the diversity combining technique that maximizes the signal-to-interference-plus-noise ratio at the receiver. The performance of OC in cooperative relaying in an interferer field modeled by a homogeneous PPP is analyzed. Both decode-and-forward (DF) and amplify-and-forward (AF) relay protocols are studied. Multirelay transmission and relay selection techniques are considered. Accurate approximations for the outage probability are derived for DF and AF relaying when the destination is able to estimate the noise-plus-interference correlation matrix (NICM) perfectly. An approximation for the outage probability of DF relaying is obtained when the destination only estimates the channel state information of the closest interferer. Relay selection outperforms multirelay transmission in both DF and AF relaying protocols. The interference correlation at the relays significantly degrades the outage performance. Limited estimation of the NICM results in better performance than conventional maximal-ratio combining, although it fails to achieve diversity gains.

The performance of optimum combining (OC) in amplify-and-forward (AF) relaying systems in the presence of co-channel interference (CCI) is analyzed using a tight approximation for the signal-to-interference-plus-noise ratio (SINR) at the destination. Two types of relaying protocols are studied, all-relay transmission with OC and best-relay transmission with OC. When CCI is present only at the destination, both relaying protocols achieve diversity gains up to M when interferer powers are scaled with the source and the relay powers, where M is the number of relays. Best-relay transmission with OC maximizes the spectral efficiency as each communication consumes only two time slots.

The performance of optimum combining (OC) with joint relay and antenna selection is analyzed for decode-and-forward relaying when co-channel interference is present at the relays and the destination. The combination of OC with joint relay and antenna selection results in positive diversity gains if at least one relay has Ti > Ni, where Ti is the number of relay antennas and Ni is the number of interferers at the relay, when the interferer powers are scaled with the source and the relay powers.

The diversity gains of cooperative relay networks are degraded in the presence of co-channel interference (CCI), which is the principal limiting factor in a properly planned cellular network. Optimum combining (OC) can be used to mitigate the adverse effects of CCI, which enables achieving diversity gains when CCI is present. The performance of OC in a channel state information (CSI) assisted amplify-and-forward (AF) relay network is analyzed when the destination node is affected by CCI, with the aid of a tight approximation for the signal-to-interference-plus-noise-ratio (SINR) at the destination node. Closed-form expressions are derived for the outage probability and the moment generating function for the approximated SINR. It is proved that OC results in a diversity gain of M, where M is the number of relay nodes. OC shows significant performance improvements over maximal-ratio combining (MRC), which reaches error floors at low-to-medium power levels.

The performance of optimum combining (OC) used in a decode-and-forward relay network over Nakagami-m fading channels in the presence of co-channel interference at the relay nodes and at the destination is analyzed. A closed-form expression is derived for the exact outage probability. It is found that OC cannot be used to achieve end-to-end diversity gain when interference is present at single-antenna relays, but the outage probability floor at the destination receiver is lowered by the OC. If the interference is present only at the destination, diversity gains can be achieved using OC. The performance of OC is compared with maximal-ratio combining (MRC) and OC achieves diversity gain if interference is present only at the destination node, whereas MRC does not.

Cooperative relay networks with multiple antennas at each node enable achieving both macro diversity and micro diversity in a wireless fading channel. Using beamforming along with space-time (ST) coding at the source and the relay of a cooperative relay network allows achieving both diversity gain and array gain. In this paper we propose novel distributed beamforming techniques for a space-time (ST) coded dual-hop cooperative multiple-input multiple-output (MIMO) decode-and-forward (DF) relay network to minimize the pair-wise error probability (PEP), while maintaining the SNR at the relay node above a given threshold. Beamforming techniques for the availability of full-instantaneous channel state information at the transmitter (CSIT) as well as statistical CSIT are proposed. The source and the relay compute their own beamforming matrices based only its own CSIT subject to individual power constraints at each node. The simulation results show that the proposed beamforming techniques offer a significant performance enhancement over the performance of a relay network using ST coding only. Furthermore, the proposed beamforming techniques maintain their performance improvement throughout the possible spatial correlation factor range for the channel.

In highly spatially correlated channels the diversity gain achieved by space-frequency (SF) coding is significantly low. Nevertheless, when full or partial channel state information is available at the transmitter, improved performance can be obtained by combining transmit beamforming with SF coding. In this paper we propose two novel transmit beamforming techniques based on the minimum pair-wise error probability (PEP) criterion for SF-coded MIMO-OFDM systems in frequency-selective Ricean fading channels. The proposed beamforming techniques (referred to as Technique 1 and Technique 2) require only the channel mean and spatial correlation statistics. Technique 1 optimally distributes the total transmit power among all the eigenmodes of the channel, whereas Technique 2 allocates the total transmit power only to the strongest eigenmodes of the channel. The simulation results demonstrate that Technique 1 and 2 offers considerable performance improvements over a system using only SF coding in low and highly spatially correlated channels, respectively. When compared with Technique 1, Technique 2 is more appealing due to the facts that it has less computational complexity, and that it offers better performance in highly correlated channels for all values of the Ricean-K factor.

In a very high noise environment, conventional communication means suffer from significant degradation due to the external noise which can drown out the desired speech signal. Environments such as industrial complexes, manufacturing plants, battle fields are examples of extremely noisy environments. Mobility is also crucial requirement for communication in such environments frequently. The paper describes the design and implementation of a mobile wireless communication system which can operate in such an environment using effective noise cancellation techniques.