Nautilus Cognitive Software-Radio Enabled Fair Spectrum Access in Open Spectrum Systems

Wireless devices are becoming ubiquitous, placing increasing stress on the fixed radio spectrum available to all access technologies. To eliminate interference between different wireless technologies, current policies allocate a fixed spectrum slice to each technology. This static assignment prevents devices from efficiently utilizing allocated spectrum, resulting in spectrum holes (no targeted devices in local area) and very poor utilization (6-10%) in other geographic areas(DARPA source). Studies have shown that reuse of such "wasted" spectrum can provide an order of magnitude improvement in system capacity. These results further motivate the Open Spectrum approach to spectrum access. Enabled by software defined radio (SDR) technology, Open Spectrum allows unlicensed (secondary) users to share spectrum with legacy (primary) spectrum users, thereby "creating" new capacity and commercial value from existing spectrum ranges. Based on agreements and constraints imposed by primary users, secondary users opportunistically utilize unused licensed spectrum on a non-interfering or leasing basis.

The Open Spectrum approach to spectrum access can achieve near-optimal utilization by allowing devices to sense and utilize available spectrum opportunistically. However, a naive distributed spectrum assignment can lead to significant interference between devices. In this series of work, we define a general framework that defines the spectrum access problem for several definitions of overall system utility.

• Graph Coloring Based Collaborative Spectrum Access--- Topology based optimization
  By reducing the allocation problem to a variant of the graph coloring problem, we show that the global optimization problem is NP-hard, and provide a general approximation methodology through vertex labeling. We examine both a centralized strategy, where a central server calculates an allocation assignment based on global knowledge, and a distributed approach, where devices collaborate to negotiate local channel assignments towards global optimization. Our experimental results show that our allocation algorithms can dramatically reduce interference and improve throughput (as much as 800%). Further simulations show that our distributed algorithms generate allocation assignments similar in quality to our centralized algorithms using global knowledge, while incurring substantially less computational complexity in the process. Please refer to our ICC05 and ACM Monet papers for more details.

• Distributed Spectrum Allocation via Local Bargaining -- low complexity distributed collaboration based algorithms that are robust to topology variations.
  Users self-organize into bargaining groups and adapt their spectrum assignment to approximate a new optimal assignment. The number of computations required to adapt to topology changes can be significantly reduced compared to that of the conventional topology-based optimizations that ignore the prior assignment. We propose a Fairness Bargaining with Feed Poverty to improve fairness in spectrum assignment and derive a theoretical lower bound on the minimum assignment each user can get from bargaining for certain network configurations. Such bound can be utilized to guide the bargaining process. We also show that the difference between the proposed bargaining approach and the true optimal approach is upper-bounded. Experimental results demonstrate that the proposed bargaining approach provides similar performance as the topology-based optimization but with more than 50% of reduction in complexity. Please refer to our SECON 2005 paper for more details.

• Rule based Spectrum Management - for devices with constrained communication resources such as sensor and mobile ad hoc networks (without frequent collaboration efforts).
  We propose a device-centric spectrum management scheme with low communication costs, where users observe local interference patterns and act independently according to preset spectrum rules. We propose five rules that tradeoff performance with implementation complexity and communication costs, and derive a lower bound on each user's allocation based on these rules. Experimental results show that our proposed rule-based approach reduces communication costs from efficient collaborative approaches by a factor of 3--4 while providing good performance. Check out the Dyspan 2005 paper for more details.

Collaboration and Fairness in Opportunistic Spectrum Access
Haitao Zheng, Chunyi Peng
IEEE International Conference on Communications(ICC)2005
Korea, May,2005
Also as MSR Technical Report, Feb. 2005 [Abstract , PDF ]

Utilization and Fairness in Spectrum Assignment for Opportunistic Spectrum Access
Chunyi Peng, Haitao Zheng, Ben Y. Zhao
accepted by ACM Monet [Abstract  ]

Distributed Spectrum Allocation via Local Bargaining
Lili Cao, Haitao Zheng
accepted by IEEE SECON 2005 PDF [Abstract]

Device Centric Spectrum Management
Haitao Zheng, Lili Cao
accepted by IEEE Dyspan 2005 PDF [Abstract]

• Haitao Zheng
• Chunyi Peng
• Lili Cao
• Jun Zhao
• Ben Y. Zhao