The slow intelligence system (SIS) technology is a novel technology for the design of a complex information system that is aware of the environment through multiple sensors and capable of improving its performance over time. In this paper we describe a practical slow intelligence system test bed where super-components can be specified to describe interactions among components. These super-components are automatically transformed into time controllers for components so they can be managed by the SIS test bed. We illustrate the application of this methodology to personal healthcare system design.

This work on cognitive radio access ventures beyond the more traditional "listen-before-talk" paradigm that underlies many cognitive radio access proposals. We exploit the bi-directional interaction of most primary communication links. By intelligently controlling their access parameters based on the inference from observed link control signals of primary user (PU) communications, cognitive secondary users (SUs) can achieve higher spectrum efficiency while limiting their interference to the PU network. In one specific implementation, we let the SUs listen to the PU's feedback channel to assess their own interference on the primary receiver, and adjust radio power accordingly to satisfy the PU's interference constraint. We propose a discounted distributed power control algorithm to achieve non-intrusive secondary spectrum access without either a centralized controller or active PU cooperation. We present an analytical study of its convergence property. We show that the link control feedback information inherent in many two-way primary systems can be used as important reference signal among multiple SU pairs to distributively achieve a joint performance assurance for primary receiver's quality of service.

We venture beyond the "listen-before-talk" strategy that is common in many traditional cognitive radio access schemes. We exploit the bi-directional nature of most primary communication systems. By intelligently choosing their transmission parameters based on the observation of primary user (PU) communications, secondary users (SUs) in a cognitive network can achieve higher spectrum usage while limiting their interference to the PU. Specifically, we propose that the SUs listen to the PU's feedback channel to assess their interference on the primary receiver (PU-Rx), and adjust radio power accordingly to satisfy the PU's interference constraint. We investigate both centralized and distributed power control algorithms without active PU cooperation. We show that the PU feedback information inherent in many two-way primary systems can be used as important coordination signal among multiple SUs to distributively achieve a joint performance guarantee on the primary receiver's quality of service.

In cognitive wireless networks where secondary users (SUs) opportunistically access spectral white spaces of primary users (PUs), there exists an inherent tradeoff between sensing and transmission due to the competing goals of PU protection and SU access maximization. This paper studies means of sensing-transmission for SUs to better manage the competing goals by defining utility function to reward the SU for successful packet transmissions and to penalize it for colliding with PU. To maximize the SU utility, we present a threshold-based sensing-transmission structure that is optimal under a technical constraint. Both perfect sensing and imperfect sensing are considered, with or without SU acknowledgement of reception. This SU access scheme optimizes SU access efficiency while protecting PU performance. It sets a benchmark and provides insight for the design of sensing-transmission control in cognitive networks such as IEEE 802.22.

Cognitive radio offers a promising technology to mitigate spectrum shortage in wireless communications. It enables secondary users (SUs) to opportunistically access low-occupancy primary spectral bands as long as their negative effect on the primary user (PU) access is constrained. This PU protection requirement is particularly challenging for multiple SUs over a wide geographical area. In this paper, we study the fundamental performance limit on the throughput of cognitive radio networks under the PU packet collision constraint. With perfect sensing, we develop an optimum spectrum access strategy under generic PU traffic patterns. Without perfect sensing, we quantify the impact of missed detection and false alarm, and propose a modified threshold-based spectrum access strategy that achieves close-to-optimal performance. Moreover, we develop and evaluate a distributed access scheme that enables multiple SUs to collectively protect the PU while adapting to behavioral changes in PU usage patterns. Our results provide useful insight on the trade-off between the protection of the primary user and the throughput performance of cognitive radios.

Driven by regulatory initiatives and radio technology advances, opportunistic spectrum access has the potential to mitigate spectrum scarcity and meet the increasing demand for spectrum. In this paper, we consider a scenario where secondary users can opportunistically access unused spectrum vacated by idle primaries. We introduce two metrics to protect primary performance, namely collision probability and overlapping time. We present three spectrum access schemes using different sensing, back-off, and transmission mechanisms. We show that they achieve indistinguishable secondary performance under given primary constraints. We provide closed form analysis on secondary user performance, present a tight capacity upper bound, and reveal the impact of various design options, such as sensing, packet length distribution, back-off time, packet overhead, and grouping. Our work sheds light on the fundamental properties and design criteria on opportunistic spectrum access.

Cognitive radio has recently been identified as a potential relief to spectrum scarcity by improving temporal spectral efficiency. We investigate a flexible non-intrusive cognitive radio network based on smart antenna technologies. The proposed scheme exploits transmit beamforming to enable better spectral sharing between primary users and cognitive (secondary) users. As proposed, the cognitive transmitter equipped with antenna array forms transmit beamforming to keep the interference to primary receiver below a given threshold. By also adopting smart antennas at primary transmitters, we can significantly boost the successful transmission probability of cognitive users; thereby improving the spectrum utilization efficiency of the wireless communication networks.

In this paper, we propose a new receiver-aided beamforming scheme to exploit the multiuser diversity in a multiantenna broadcast channel. By introducing an appropriately designed beamforming codebook that consists of the beam matrices, we can further exploit multiuser diversity by performing beam matrix selection operation and improve system throughput. The beam matrix selection could be implemented by the aid of receivers in practical system. Beamforming codebook is generated offline and stored at the base station (BS) and every user's receiver. Each user calculates the achievable signal to interference plus noise ratio (SINK) using the available channel state information at the receiver (CSIR), all beamforming matrices in the codebook and all beam vectors in the selected beam matrix, and then forms feedback information including the maximum sink and the corresponding best beam matrix index and beam vector index. Based on the feedback information, the BS runs scheduling algorithm to maximize throughput. Numerical results show that this scheme can considerably improve throughput of existed random beamforming scheme with only a few more bits feedback overhead.