Price-Based Spectrum Management in Cognitive Radio Networks

Abstract

Cognitive radios (CRs) have a great potential to improve spectrum utilization by enabling users to access the spectrum dynamically without disturbing licensed primary radios (PRs). A key challenge in operating these radios as a network is how to implement an efficient medium access control (MAC) mechanism that can adaptively and efficiently allocate transmission powers and spectrum among CRs according to the surrounding environment. Most existing works address this issue via sub-optimal heuristic approaches or centralized solutions. In this paper, we propose a novel joint power/channel allocation scheme that improves the performance through a distributed pricing approach. In this scheme, the spectrum allocation problem is modeled as a non-cooperative game, with each CR pair acting as a player. A price-based iterative water-filling (PIWF) algorithm is proposed, which enables CR users to reach a good Nash equilibrium (NE). This PIWF algorithm can be implemented distributively with CRs repeatedly negotiating their best transmission powers and spectrum. Simulation results show that the social optimality of the NE solution is dramatically improved through pricing. Depending on the different orders according to which CRs take actions, we study sequential and parallel versions of the PIWF algorithm. We show that the parallel version converges faster than the sequential version. We then propose a corresponding MAC protocol to implement our resource management schemes. The proposed MAC allows multiple CR pairs to be first involved in an admission phase, then iteratively negotiate their transmission powers and spectrum via control-packet exchanges. Following the negotiation phase, CRs proceed concurrently with their data transmissions. Simulations are used to study the performance of our protocol and demonstrate its effectiveness in terms of improving the overall network throughput and reducing the average power consumption.

Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access

“…Pricing and Contract are generally adopted by the futures market, wherein sellers and buyers enter into certain agreements, specifying the price, quality and demand in advance. In particular, Pricing is often used under information symmetry, where sellers and buyers possess the same market information (e.g., utility and quality) or hold the same degree of uncertainty about the market information (see, e.g., Kloeck et al (2005), Wang et al (2008), Niyato & Hossain (2008)). …”

“…Futures Market Pricing: Kloeck et al (2005), Wang et al (2008), Niyato & Hossain (2008). Contract: Gao et al (2010), Duan et al (2011), Kalathil & Jain (2010).…”

Economic Approaches for Cognitive Radio Networks: A Survey

“…For self coexistence among secondary users, while [33] proposes a non-cooperative dynamic channel switching game, [19] considers a cooperative approach for channel allocation. On the other hand, [34] considers a non-cooperative framework and a pricing based cooperative approach for self coexistence of secondary users. Figure 4a shows the classification based on the particular game models described in Sect.…”

“…In terms of resource allocation, while [14,36] consider the coexistence between primary service providers and secondary users, [19,33,34] explore self coexistence among secondary users. Although both [14,36] consider the coexistence between primary and secondary systems, [36] is based on the cooperation between primary and secondary users, while in [14], the framework is non-cooperative.…”

“…In [34], a joint power/channel allocation scheme is proposed using a distributed pricing approach for cognitive radio networks and a frequency dependent power mask constraint is introduced for secondary users in addition to maximum transmission power constraint and minimum SINR constraint.…”