Path Selection under Budget Constraints in Multihop Cognitive Radio Networks

Abstract

Cognitive radio (CR) technology opens the licensed spectrum bands for opportunistic usage and initiates spectrum trading to improve the spectrum utilization. In this paper, we investigate the path selection problem in multihop cognitive radio networks (CRNs) under constraints on flow routing, link scheduling and CR source's budget. We extend the per-user-based spectrum trading in prior work to CR session-based spectrum trading, and effectively develop the spectrum trading mechanisms based on the cross-layer optimization in multihop CRNs. We introduce a new service provider, called secondary service provider (SSP), to help CR sessions to select the paths for packet delivery. Considering the price of bands and the potential returning of primary services at different CR links, the SSP purchases the licensed spectrum and jointly conducts flow routing and link scheduling under the budget constraints. We also propose a 4D conflict graph to characterize the conflict relationship among CR links and mathematically formulate the path selection problem under multiple constraints into an optimization problem with the objective of maximizing the end-to-end throughput. Due to the NP-hardness of the problem, we have also developed a heuristic algorithm to find the approximate solution.

Stackelberg-Game-Based Dynamic Spectrum Access in Heterogeneous Wireless Systems

“…When we consider k = 1 for (37), we get w n,k 1 + γ n, 1 − λ 1 c 1 + λ 2 = 0 (38) and for k = 2, we get w n,k 1 + γ n, 2 − λ 1 c 2 + λ 3 = 0.…”

“…, N} is the set of players that are the active SUs; 2) Strategies: Actions taken by the players to maximize their payoffs; 3) Payoff: Outcome in (4) of a player based on chosen strategies. We assume that c k is the unit price 4 set by the service provider k, and B n denotes the budget of SU n (which is similar to the payment/budget for a data/voice plan that wireless users pay to their cellular service providers), and mathematically, B n = f ( ∀k p n,k /σ 2 n , P ay) that depends on transmit power of SU n and its payment P ay for the wireless service (e.g., [38] and [39]). Based on a given set of prices {c 1 , c 2 , .…”

Cross-Layer Aided Energy-Efficient Routing Design for Ad Hoc Networks

“…They might be designed for reducing the energy consumption [38,48,52], the end-to-end delay [47], for improving the network's throughput [39,49,54], for striking a flexible tradeoff between any two of them [26,42,45,46,50,51], and even for multiple-constraint optimization [36,41,43,44].…”

“…Heinzelman [52] 2012 Syue et al [53] Proposed a relay-aware cooperative routing protocol relying on cross-layer design. 2013 Pan et al [54] Investigated the path selection problem based on the cross-layer optimization in on flow routing, multihop Cognitive Radio Networks(CRNs) under constraints link scheduling and CR source's budget. 2014 Uddin et al [26] Studied cross-layer design in random-access-based fixed wireless multihop networks under a physical interference model.…”

Pricing-based routing in cognitive radio networks

“…Through an iterative price adaptation algorithm, spectrum is allocated for the route selected. A session-based spectrum trading mechanism based on the crosslayer optimization is proposed in [10]. A secondary service provider (SSP) selects the paths considering various parame-ters including the price of bands, primary activity, flow routing, and link scheduling.…”