Reliable people counting is crucial to many urban applications. However, most existing people counting systems are sensor-based and can only work in some fixed gateways or checkpoints where sensors have been installed. This high dependence on the exact locations of sensors leads to low accuracy. To overcome these limitations, in this paper, we propose a smartphone-based people counting system, Wi-Counter, by leveraging the pervasive Wi-Fi infrastructure. To collect comprehensive Wi-Fi signals and people count information based on crowdsource, Wi-Counter first adopts a preprocessor to overcome the noisy, discrepant, and fragile data based on the Wiener filter and Newton interpolation. It then makes use of the designated five-layer neural network to learn the relation model between the Wi-Fi signals and the number of people. By analyzing the received Wi-Fi signals, Wi-Counter can estimate the number of people based on the resulting model. We have conducted experiments by implementing a prototype of Wi-counter based on smartphones and evaluated the system in terms of accuracy and power consumption in an indoor testbed covering an area of 96 m $^2$. Wi-Counter achieved a counting accuracy of up to 93% and exhibited reliable and robust performance resisting temporal environmental changes with negligible power usage.

Newly popular indoor location-based services (ILBS), when integrated with commerce and public safety, offer a promising land for wireless indoor localization technologies. WLAN is suggested to be one of the most potential candidates owing to its prevalent infrastructure (i.e., access points (APs)) and low cost. However, the overall performance can be greatly degraded by the spatial localizability variance problem, i.e., the localization accuracy across various locations may have significant differences given any fixed AP deployment. As a result, it brings in user experience inconsistency which is unfavorable for ILBS. In this paper, we propose NomLoc - an indoor localization system using nomadic APs to address the performance variance problem. The key insight of NomLoc is to leverage the mobility of nomadic APs to dynamically adjust the WLAN network topology. A space partition (SP)-based localization algorithm is tailored for NomLoc to perform calibration-free positioning. Moreover, fine-grained channel state information (CSI) is employed to mitigate the performance degradation of the SP-based method due to multipath and none-line-of-sight (NLOS) effects. We have implemented the NomLoc system with off-the-shelf devices and evaluated the performance in two typical indoor environments. The results show that NomLoc can greatly mitigate spatial localizability variance and improve localization accuracy with the assistance of nomadic APs as compared with the corresponding static AP deployment. Moreover, it is robust to the position error of nomadic APs.

Improving channel utilization is a well-known issue in wireless networks. In traditional point-to-point wireless communication, significant efforts had been made by the existing studies on enhancing the utilization of the channel access time. However, in the emerging wireless network using MU-MIMO, considering only the time domain in channel utilization is not sufficient. As multiple transmitters are allowed to transmit packets simultaneously to the same AP, allowing more antennas at AP would lead to higher channel utilization. Thus, the channel utilization in MU-MIMO should consider both time and spatial domains, i.e., the channel access time and the antenna usage, which have not been considered in the existing methods. In this paper, we point out that the fundamental problem is lacking of the antenna information of contention nodes in channel contention. To address this issue, we propose a new MAC-PHY architecture design, CUTS, to allow distributed nodes effectively contend for the channel and utilize the channel in both domains. Particularly, CUTS adopts interference nulling to attach the antenna information in channel contention. Meanwhile, techniques such as channel contention in frequency domain and ACK in frequency domain using self-jamming are adopted. Through the software defined radio-based real experiments and extensive simulations, we demonstrate the feasibility of our design and illustrate that CUTS provides better channel utilization with the gain over IEEE 802.11 reaching up to 470 percent.

Improving channel utilization is a well-known issue in wireless networks. In traditional point-to-point wireless communication, significant efforts had been made by the existing study on enhancing the utilization of the channel access time. However, in the emerging wireless network using MU-MIMO, considering only the time domain in channel utilization is not sufficient. As multiple transmitters are allowed to transmit packets simultaneously to the same AP, allowing more antennas at AP would lead to higher channel utilization. Thus the channel utilization in MU-MIMO should consider both time and spatial domains, i.e., the channel access time and the antenna usage, which has not been considered in the existing methods. In this paper, we point out that the fundamental problem is lacking of the antenna information of contention nodes in channel contention. To address this issue, we propose a new MAC-PHY architecture design, CUTS, to utilize the channel in both domains. Particularly, CUTS adopts interference nulling to attach the antenna information in channel contention. Meanwhile, techniques such as channel contention in frequency domain and ACK in frequency domain using self-jamming are adopted. Through the software defined radio based real experiments and extensive simulations, we demonstrate the feasibility of our design and illustrate that CUTS provides better channel utilization with the gain over IEEE 802.11 reaching up to 470%.

Effective coordination can dramatically reduce radio interference and avoid packet collisions for multistation wireless local area networks (WLANs). Coordination itself needs consume communication resource and thus competes with data transmission for the limited wireless radio resources. In traditional approaches, control frames and data packets are transmitted in an alternate manner, which brings a great deal of coordination overhead. In this paper, we propose a new communication model where the control frames can be "attachedâ to the data transmission. Thus, control messages and data traffic can be transmitted simultaneously and consequently the channel utilization can be improved significantly. We implement the idea in OFDM-based WLANs called hJam, which fully explores the physical layer features of the OFDM modulation method and allows one data packet and a number of control messages to be transmitted together. hJam is implemented on the GNU Radio testbed consisting of eight USRP2 nodes. We also conduct comprehensive simulations and the experimental results show that hJam can improve the WLANs efficiency by up to 200 percent compared with the existing 802.11 family protocols.

Effective coordination can dramatically reduce radio interference and avoid packet collisions for multi-station wireless local area networks (WLANs). Coordination itself needs consume communication resource and thus competes with data transmission for the limited wireless radio resources. In traditional approaches, control frames and data packets are transmitted in an alternate manner, which brings a great deal of coordination overhead. In this paper we propose a new communication model where the control frames can be “attached” to the data transmission. Thus, control messages and data traffic can be transmitted simultaneously and consequently the channel utilization can be improved significantly. We implement the idea in OFDM-based WLANs called hJam, which fully explores the physical layer features of the OFDM modulation method and allows one data packet and a number of control messages to be transmitted together. hJam is implemented on the GNU Radio testbed consisting of eight USRP2 nodes. We also conduct comprehensive simulations and the experimental results show that hJam can improve the WLANs efficiency by up to 72% compared with the existing 802.11 family protocols.

In peer-to-peer (P2P) on-demand streaming applications, multimedia content is divided into segments and peers can seek any segments for viewing at anytime. Since different segments may be of different popularity, random segment caching would lead to a segment popularity-supply mismatch, and hence an uneven workload distribution among peers. Some popular segments may be far from peers, leading to inefficient search and streaming. In this paper, we study optimal segment caching for P2P on-demand streaming. We first state the segment caching optimization problem, and propose a centralized heuristic to solve it, which serves as a benchmark for other algorithms. We then propose a distributed caching algorithm termed POPCA (POPularitybased Caching Algorithm), in which each peer adaptively and independently replaces segments to minimize the popularitysupply discrepancy and the segment distance from peers. Through simulations, we show that POPCA achieves nearoptimal performance, and lower peer workload and segment distance as compared with other schemes.