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Uncertainty appears naturally in most systems and is one of their design considerations. Improperly managed uncertainty could lead to catastrophic consequences. Wireless communication systems are no exceptions. Channel conditions and multi-user access environments are well-known examples affecting the system design and performance. Various approaches and methodologies have been proposed to mitigate their adverse impacts to the systems. Majority of them unavoidably introduce additional and redundant resources to overcome uncertainty which ultimately improve the overall performance from system perspective. Nevertheless, such designs usually suffer degradation from the standpoint of resource utilization. We argue that resource utilization could be optimized by introducing secondary usage or recycling useless resources for useful purposes. In this thesis, we presented uncertainty management and resource usage patterns with emphasis on wireless communication systems. Through an extensive analysis of existing mechanisms, we identified the root causes of inefficiency and proposed innovative approaches to acquire useful information from previously neglected data and situations. We illustrated this idea through three application scenarios in RFID systems and wireless channel condition inference. This revolutionary methodology would not only improve resource utilization but also allow it to be analyzed and measured in a new dimension.

IEEE 802.15.4 standard specifies physical layer (PHY) and medium access control (MAC) sublayer protocols for low-rate and low-power communication applications. In this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. The 32 chips as a whole is also called a pseudonoise code (PN-Code). Due to complex channel conditions such as attenuation and interference, the transmitted PN-Code will often be received with some PN-Code chips corrupted. In this paper, we conduct a systematic analysis on these errors occurring at chip level. We find that there are notable error patterns corresponding to different cases. We then show that recognizing these patterns enables us to identify the channel condition in great details. We believe that understanding what happened to the transmission in our way can potentially bring benefit to channel coding, routing, and error correction protocol design. Finally, we propose Simple Rule, a simple yet effective method based on the chip error patterns to infer the link condition with an accuracy of over 96 percent in our evaluations.

IEEE 802.15.4 standard specifies physical layer (PHY) and medium access control (MAC) sublayer protocols for low-rate and low-power communication applications. In this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. The 32 chips as a whole is also called a pseudonoise code (PN-Code). Due to complex channel conditions such as attenuation and interference, the transmitted PN-Code will often be received with some PN-Code chips corrupted. In this paper, we conduct a systematic analysis on these errors occurring at chip level. We find that there are notable error patterns corresponding to different cases. We then show that recognizing these patterns enables us to identify the channel condition in great details. We believe that understanding what happened to the transmission in our way can potentially bring benefit to channel coding, routing, and error correction protocol design. Finally, we propose Simple Rule, a simple yet effective method based on the chip error patterns to infer the link condition with an accuracy of over 96 percent in our evaluations.

Counting the number of RFID tags (cardinality) is a fundamental problem for large-scale RFID systems. Not only does it satisfy some real application requirements, it also acts as an important aid for RFID identification. Due to the extremely long processing time, slotted ALOHA-based or tree-based arbitration protocols are often impractical for many applications, because tags are usually attached to moving objects and they may have left the readers interrogation region before being counted. Recently, estimation schemes have been proposed to count the approximate number of tags. Most of them, however, suffer from two scalability problems: time inefficiency and multiple-reading. Without resolving these problems, large-scale RFID systems cannot easily apply the estimation scheme as well as the corresponding identification. In this paper, we present the Lottery Frame (LoF) estimation scheme, which can achieve high accuracy, low latency, and scalability. LoF estimates the tag numbers by utilizing the collision information. We show the significant advantages, e. g., high accuracy, short processing time, and low overhead, of the proposed LoF scheme through analysis and simulations.

Recent years have seen an increasing need of wireless networks in a mobile environment serving for more complex tasks and applications. Mobility becomes an indispensable factor of the system design and has been widely recognized as a general cause of packet loss. Though many works have been done on mobility study, to the best of our knowledge, they are mainly based on simulations or analytical studies that assume idealized link conditions. In this work, we experimentally investigate the nature of the error characteristics of mobility-induced packet losses at "chip-level" in IEEE 802.15.4. We believe this more understanding of mobility-induced packet losses can bring great potential benefits for further study on channel coding, routing and protocol design. Toward this end, we design and implement an efficient algorithm to distinguish mobility-induced packet losses from other packet losses of static environments such as attenuation. Our algorithm is greatly advantaged as it needs no training data even when environment changes. Collecting three corrupted packets is sufficient to obtain a satisfactory performance. This feature makes our design in particular suitable for dynamic and mobile environments, allowing real-time mobilityinduced loss detection in an online manner. Experiments based on GNU Radio testbed show that our algorithm can provide an accuracy of up to 96%. ©2010 IEEE.

IEEE 802.15.4 standard specifies physical layer (PHY) and medium access control (MAC) sublayer protocols for low-rate and low-power communication applications. In this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. The 32 chips as a whole is also called a pseudo-noise code (PN-Code). Due to complex channel conditions such as attenuation and interference, the transmitted PN-Code will often be received with some PN-Code chips corrupted. In this paper, we conduct a systematic analysis on these errors occurring at chip-level. We find that there are notable error patterns corresponding to different cases. Recognizing these patterns will enable us to identify the channel condition in great details. We believe that understanding what happened to the transmission in our setup can potentially bring benefit to channel coding, routing and error correction protocol design.

The growing importance of operations such as identification, location sensing and object tracking has led to increasing interests in contactless Radio Frequency Identification (RFID) systems. Enjoying the low cost of RFID tags, modern RFID systems tend to be deployed for large-scale mobile objects. Both the theoretical and experimental results suggest that when tags are mobile and with large numbers, two classical MAC layer collision-arbitration protocols, slotted ALOHA and Tree-traversal, do not satisfy the scalability and time-efficiency requirements of many applications. To address this problem, we propose Adaptively Splitting-based Arbitration Protocol (ASAP), a scheme that provides low-latency RFID identification and has stable performance for massive RFID networks. Theoretical analysis and experimental evaluation show that ASAP outperforms most existing collision-arbitration solutions. ASAP is efficient for both small and large deployment of RFID tags, in terms of time and energy cost. Hence it can benefit dynamic and large-scale RFID systems.

Recent years have seen an increasing need of wireless networks in a mobile environment serving for more complex tasks and applications. Mobility becomes an indispensable factor of the system design and has been widely recognized as a general cause of packet loss. Though many works have been done on mobility study, to the best of our knowledge, they are mainly based on simulations or analytical studies that assume idealized link conditions. In this work, we experimentally investigate the nature of the error characteristics of mobility-induced packet losses at "chip-level" in IEEE 802.15.4. We believe this more understanding of mobility-induced packet losses can bring great potential benefits for further study on channel coding, routing and protocol design. Toward this end, we design and implement an efficient algorithm to distinguish mobility-induced packet losses from other packet losses of static environments such as attenuation. Our algorithm is greatly advantaged as it needs no training data even when environment changes. Collecting three corrupted packets is sufficient to obtain a satisfactory performance. This feature makes our design in particular suitable for dynamic and mobile environments, allowing real-time mobilityinduced loss detection in an online manner. Experiments based on GNU Radio testbed show that our algorithm can provide an accuracy of up to 96%. ©2010 IEEE.

IEEE 802.15.4 standard specifies physical layer (PHY) and medium access control (MAC) sublayer protocols for low-rate and low-power communication applications. In this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. The 32 chips as a whole is also called a pseudo-noise code (PN-Code). Due to complex channel conditions such as attenuation and interference, the transmitted PN-Code will often be received with some PN-Code chips corrupted. In this paper, we conduct a systematic analysis on these errors occurring at chip-level. We find that there are notable error patterns corresponding to different cases. Recognizing these patterns will enable us to identify the channel condition in great details. We believe that understanding what happened to the transmission in our setup can potentially bring benefit to channel coding, routing and error correction protocol design.

Sensor networks have attracted intensive interests due to its extendable capability. In this paper, we attempt to answer a fundamental but practical question:" how should we deploy these nodes?" In most current designs, sensors are randomly or uniformly distributed because of their simplicity. However, the node deployment has a great impact to the wireless systems. It in essential highlights an open issue that, instead of maintaining the coverage for some snapshots of the network, how we can provide a continuous coverage in the whole lifecycle of the wireless sensor networks. We will exhibit the weakness of the uniform distribution by disclosing the fatal Sink routing-hole problem. To address this problem, we propose a non-uniform, power-aware distribution scheme. Our analysis and simulation results show that the Power-aware deployment scheme can significantly improve the long-termed network connectivity and service quality. © 2006 IEEE.

Wireless Sensor Networks (WSNs) have provided a new model for building intelligent applications with better computer-human/environment interaction. WSNs are built using massive tiny and resources-constrained sensor nodes. With the limited power supply for the sensor nodes, energy consumption is one of the major concerns of the usefulness of the application. It is widely accepted that sleeping is the most effective way to reduce the energy consumption and thus prolong the network lifetime. Many sleeping algorithms have been proposed which aim to identify the redundant sensor nodes and turn them into the sleeping mode. In diffusion stimulus (DS) monitoring, the application will result in degraded performance when traditional sleeping algorithms are in use. It is due to the fact that detection delay is as important as energy consumption. We propose our Stimulus-based Adaptive Sleeping (SAS) which incorporate these application-specific requirements into the sleeping algorithm. This decentralized design provides a balanced performance on both the energy consumption and detection delay with the understanding and utilization of the DS behaviors.

Wireless sensor networks have been widely deployed for monitoring environments of interest. The diffusion stimulus (DS) is a very common and important one in real environments, which is characterized by originating at a source spot and continuously spreading outward. DS-based applications are usually time-sensitive and require high accuracy. It is very challenging, however, for sensor networks to monitor a DS when those sensors could usually monitor one point (the sensing range is zero) only. No existing algorithm is effective and energy-efficient for DS monitoring. In this paper, we propose stimulus-based adaptive sleeping (SAS), to tackle this unique challenge. With SAS, each node independently determines its sleep duration based on its local observations on the stimulus. SAS enables sensors near the stimulus boundary to stay alert to accurately capture the stimulus arrival, and those far away from the stimulus to safely sleep longer for energy efficiency. © 2005 IEEE.