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Cognitive radio requires that a secondary user (SU) stops its transmission as soon as possible upon the arrival of a primary user (PU). In this paper, we propose a novel approach to quickly detect PUs while an SU transmission is in progress. The proposed method requires an SU transmitter to use OFDM to insert periodic zero-energy intervals in a selected subcarrier and to detect energy during each interval for PU detection. The length and periodicity of these intervals determine the performance of PU detection. We also discuss how to determine the energy detection threshold.

IEEE 802.11 specifies four different medium access control (MAC) protocols to coordinate multiple access in a wireless local area network (WLAN). Since several tens of stations can operate in a WLAN, the performance of MAC protocols is important for overall network efficiency. It has been observed that the IEEE 802.11 MAC protocols can be improved by knowing which station has a non-empty queue, i.e., queue status. The point coordination function (PCF) can use this information to avoid polling a station that has no pending data. The HCF controlled channel access can adapt polling parameters based on queue status information, especially when scheduling a bursty and variable bit-rate traffic. Previously suggested methods are rather limited in terms of accuracy and efficiency. In this paper, we propose a novel method to investigate the queue status of multiple stations by exploiting orthogonal signaling. With synchronous transmission of orthogonal codes and symbol level signal processing, the method allows all of the associated stations to report their queue status at the same time. Challenges that can arise in the implementation of the proposed method are identified, and their solutions are suggested. The feasibility of detecting orthogonal signals is thoroughly tested on a realistic channel model. To demonstrate the performance improvement of a MAC protocol, we applied the proposed method to PCF. Both analysis and simulation show that the modified PCF significantly outperforms not only the original PCF but also other previously suggested PCF enhancements.

Cognitive radio (CR) features opportunistic access to spectrum when licensed users (LU) are not operating. To avoid interference to LU, cognitive users (CU) need to perform spectrum sensing. Because of local shadowing, fading, or limited sensing capability, it is suggested that multiple CUs cooperate to detect LU. In cooperative spectrum sensing, CUs should exchange their sensing data with minimum bandwidth and delay. In this paper, we introduce a novel method to efficiently report sensing data to the central node in an infrastructured OFDM-based CR network. All CUs simultaneously report their sensing data over unique and orthogonal signals on locally available subcarriers. By detecting the signals, the central node can determine subcarrier availability for each CU. Implementation challenges are identified and then their solutions are suggested. The proposed method is evaluated through simulation on a realistic channel model. The results show that the proposed method is feasible and efficient.

In-network data aggregation is a cross-layer routing technique which is essential for wireless sensor networks with a large number of nodes. Although the technique enhances energy efficiency by reducing packet transmissions, it may require routing-layer waiting time which introduces additional delays in packet delivery. This implies that there exists an energy-delay tradeoff which can be controlled depending on the delay level an application can tolerate. In this work, we first perform an in-depth analysis of the data aggregation process and validate the strong relationship between the amount of currently accumulated data in a node and the data aggregation timeout to achieve energy efficiency with little delay overhead. Then, we propose a novel timeout control scheme which dynamically changes timeout according to the amount of currently accumulated data in a node. Our scheme is based on local information without involving control messages so that it is not only robust but also light-weight. Evaluation results based on an implementation of the wireless sensor network show that our scheme facilitates efficient tradeoff between energy and delay. Thus, high energy efficiency can be achieved with little overhead in delay, and vice versa.

Several routing structures have been proposed for data gathering in a wireless sensor network. They are considered to be near-optimal with respect to energy efficiency or delivery delay, but they overlook the construction cost of a routing tree which may make trouble in implementation. Our primary goal in this work is to construct a routing tree with negligible cost, which performs as well as those near-optimal schemes. First, we propose a distributed and localized framework for tree construction called Local Parent Designation (LPD), where the node status information is exchanged locally and decision based on the local information leads us to construct a routing tree. Secondly, we extend LPD to so called LPD-Local Fix (LPD-LF) to reduce further the construction cost with less local information exchange. Simulation results validate that our goal is achieved.

Cognitive radio is one of the most promising solutions to spectrum-scarcity problem. In cognitive radio networks, the most important requirement is to avoid interference between the primary and secondary users. However, different primary users require different levels of protection. Moreover, the extent of interference that a primary user can tolerate may change over time. Therefore, a secondary should adapt its operating parameters according to a primary user's changing requirements. In this paper, we propose a method that determines the optimal length of the sensing period and the data-transmission period. Given the primary user's requirements, our method uses a stochastic model to derive two parameters that maximizes the secondary user's throughput. By simulation, we show that our method is valid and optimal.

The point coordination function (PCF) of the IEEE 802.11 WLAN facilitates deterministic frame transfer by a polling mechanism. This enables to support quality of service. Despite this benefit the PCF could be inefficient at low-to-medium traffic loads because it always polls all stations regardless of their actual demand. To overcome this drawback, we introduce a novel polling scheme where all stations simultaneously report their status by sending orthogonal signals, and a BS identifies and polls only those stations having data to send. The feasibility of orthogonal signalling is evaluated in a realistic channel model where multipath fading and additive white Gaussian noise are applied. Moreover, channel utilization of the proposed scheme is investigated analytically, and compared with other schemes through simulation. The evaluation results show that the proposed scheme considerably outperforms other schemes at low-to-medium traffic loads.

In-network data aggregation is one of the key technologies in wireless sensor networks. Because data aggregation inherently incurs a tradeoff between energy efficiency and delivery delay, several solutions have been proposed to control the waiting time before transmission of an aggregated data (i.e. data aggregation timeout). In this work we consider the case when one packet can carry multiple sensing data elements and this aggregation is limited to a finite number due to the limitation of packet size. Based on the idea that the timeout may be determined by the current number of waiting data elements, we propose a scheme for varying timeout, analyze its performance using a stochastic model, and show how to customize the varying timeout in the proposed scheme for energy efficiency or low delay. Experiment results show that our analytical model accords well with the real world implementation and our scheme facilitates efficient tradeoff between energy and delay, that is, high energy efficiency can be achieved with little overhead in delay, and vice versa.

We focus on the coverage problem in the mobile sensor network, where each node is capable of movement. Most of the prior schemes pursue coverage by uniformizing the node density or internodal distance over the area of interest. In this paper, we first argue that the uniformizing schemes are inefficient to achieve the multi-level coverage due to the phenomenon we call geometric anomaly, and that the anomaly can be solved by layering. Then, we design a distributed layering scheme, where the layers are built by nodes' local decision and the imbalance of the layer size is minimized by regrouping. Simulation results show that our scheme achieves the required multilevel coverage with a significantly reduced number of nodes.