Robust Distributed Power Control in Cognitive Radio Networks

Abstract-We investigate the secondary users (SUs) power allocation in adhoc cognitive radio networks, considering an underlay paradigm where SUs can access the licensed spectrum owned by the primary users (PUs), if the total power to SUs and the interference power threshold from PUs and the signal-tointerference-noise-ratio (SINR) requirements of SUs are guaranteed. While prevalent works about distributed resources allocation algorithms are mainly focused on power allocation under the consideration of many practical limitations, which may not be the case in practice. We assume that SUs also are needed to satisfy heterogenous constraints with different positions by taking the fairness of SUs into account. Moreover, we develop a weighted robust distributed power allocation scheme to guarantees the fairness of SUs. Techniques from robust optimization theory are used to study an objective formulation with infinite numbers of constraints. The optimal solution is obtained by using Lagrange dual method, and the Lagrange multiplier is solved by the sub-gradient update algorithm. The feasibility and availability of our proposed power allocation scheme is confirmed by numerical results.

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“…! is generated by random function; (18) and (19), respectively; 3. Update the SU strategy simultaneously: …”

Section: Weighted Robust Distributed Algorithmmentioning

confidence: 99%

“…Thus, we can confirm that the PWRS is efficient compared with the PWNRS. In Fig.5, we compare the total power, the capacity, the interference performance and the SINR experienced by SUs of different schemes: PWRS and traditional robust scheme (TRS) [19]- [21] under the same parameter perturbation (! !…”

Section: Performance Analysismentioning

confidence: 99%

A Robust Power Allocation Scheme in Ad-Hoc Cognitive Radio Networks

2017

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“…Therefore, in fact, static spectrum allocationalgorithm without considering nondeterministic parameters may result in frequent spectrum collision and poor performance. Recently, dynamic resource allocation with non-deterministic parameters in CRNs has received considerable interest from academia, which mainly focus on non-deterministic channel gain and mutual interference [10]- [12]. [10] studies the resource allocation for CRNs under non-deterministic signal-to-interference-plusnoise ratio (SINR) and propose a power control scheme by using water filling algorithm and stochastic programming.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, [11] studies the distributed resourceallocation problem in CRNs by considering the nondeterministic channel gainand the authors propose arobustdistributedpowercontrol algorithm by applying secondorder cone programming (SOCP). [12] proposes a robust distributed uplink power allocation algorithm by using worst case robust optimization method, which consider channel gains from SUs to PUs' base station, and interferencecaused by PUs to the SUs' base station are nondeterministic. Inaddition,most existing works mainly focus on non-deterministic channel gain and mutual interference.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Assignment with Non-Deterministic Bandwidth of Spectrum Holein Cognitive Radio Networks

Huang

Zeng

et al. 2016

MATEC Web of Conferences

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Abstract.The spectrum allocation for cognitive radio networks (CRNs) has received considerable studies under the assumption that the bandwidth of spectrum holes is static. However, in practice, the bandwidth of spectrum holes is timevaried due to primary user/secondary user (PU/SU) activity and mobility, which result in non-determinacy. This paper studies the spectrum allocation for CRNs with non-deterministic bandwidth of spectrum holes. We present a novel probability density function (PDF) model through order statistic to describe the non-deterministic bandwidth of spectrum holes and provide a bound to approximate it. After that, a statistical spectrum allocation model based on stochastic multiple knapsack problem (MKP) is established for spectrum allocation with non-deterministic bandwidth of spectrum holes. To reduce the computational complexity, we transform this stochastic programming probleminto a constant MKP though exploiting the properties of cumulative distribution function (CDF), which can be solved via MTHG algorithm by using auxiliary variable. Simulation results illustrate that the proposed statistical spectrum allocation algorithm can achieve better performances compared to the existing algorithms when the bandwidth of spectrum holes istime-varied.

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“…The proposed scheme, with the consideration of both cooperative feedback from PUs and local feedback from SUs to the secondary base station (SBS), is robust to the channel uncertainties. Robust distributed power allocation algorithm for underlay CR networks was proposed in [10],which maximizes the sum utility of SUs when channel gains from SUs to primary base station (PBS) and interference introduced by PUs to the SBS are uncertain. In [11], the authors studied the problem of joint beamforming and power allocation in a cognitive MIMO system using game theory, where the imperfect CSI was taken into account by the robust interference constraint and the optimization problem in the formulated robust game is converted into a SOCP problem.…”

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confidence: 99%