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## Energy-Infeasibility Tradeoff in Cognitive Radio Networks: Price-Driven Spectrum Access Algorithms (2014)

Citations: | 1 - 1 self |

### Citations

7417 | Convex Optimization
- Boyd, Vandenberghe
- 2004
(Show Context)
Citation Context ...nd admission control algorithms with low implementation complexity. In particular, we first propose an algorithm based on the sum-of-infeasibilities convex relaxation heuristic in optimization theory =-=[28]-=-. Using optimization duality, we refine our algorithm based on the tradeoff analysis between the total energy consumption and the system capacity to compute a (suboptimal) feasible set of users that c... |

648 | framework for uplink power control in cellular radio systems
- Yates, BA
- 1995
(Show Context)
Citation Context ...on power control algorithms for energy minimization subject to SINR constraints, it has been extended to consider power constraints, e.g., the constrained Distributed Power Control (DPC) algorithm in =-=[6]-=-, when there is an individual power constraint for each user. In [7], the authors proposed joint power control and channel access algorithms for robustness against outage. In [8], [9], the authors pro... |

507 |
Non-Negative Matrices and Markov Chains
- Seneta
- 1981
(Show Context)
Citation Context ...e el denotes the lth unit coordinate vector. Let Hl = diag ( γ̄ 1+q )( F+ 1p̄lve l ) for all l. Note thatHl is a nonnegative matrix that is irreducible whenever F is for all l. Using Theorem 1.6 in =-=[31]-=- (Subinvariance Theorem), we deduce that: Suppose thatHl is an irreducible nonnegative matrix and there is a vector p ≥ 0 with p = 0 satisfying Hlp ≤ p (implying that (3) is feasible), then p > 0 and... |

475 | simple distributed autonomous power control algorithm and its convergence
- Foschini, Miljanic, et al.
- 1993
(Show Context)
Citation Context ...radio network is the dynamic access of TV white space spectrum, which consists of unused TV broadcast frequency bands. constraints of all the users. Since the seminal work by Foschini and Miljanic in =-=[5]-=- on power control algorithms for energy minimization subject to SINR constraints, it has been extended to consider power constraints, e.g., the constrained Distributed Power Control (DPC) algorithm in... |

383 |
Nonnegative Matrices in the Mathematical Sciences
- Berman, Plemmons
- 1994
(Show Context)
Citation Context ...s |Dij |. Thus, from (49) and after taking the absolute value on both sides, we have, elementwise: D̂ ≤ [ diag (p ◦ x)−1 F̄ 0 0 0 ] +E diag ([p ◦ x;p ◦ x])−2 . (51) Using Lemma 1 and Corollary 1.5 in =-=[32]-=- which states that ρ(A) ≤ ρ(B) for nonnegative matrices A and B satisfying A ≤ B, we get the inequalities: ρ ( diag (p ◦ x)−1 F̄ ) ≤ ρ ( diag ( γ̄ 1+q ) F ) < ρ ( diag ( γ̄ 1+q )( F+ 1p̄lve l )) ≤ 1... |

300 | Spectrum sharing for unlicensed bands - Etkin, Parekh, et al. - 2007 |

283 | Joint Scheduling and Power Control for Wireless Ad-Hoc Networks,”
- Elbatt, Ephremides
- 2002
(Show Context)
Citation Context ...hose interference can overwhelm the (licensed band) primary users [10]–[14]. Thus, joint power and admission control is necessary to resolve the infeasibility issue in the energy minimization problem =-=[15]-=-. 0733-8716/14/$31.00 c© 2014 IEEE ZHAI et al.: ENERGY-INFEASIBILITY TRADEOFF IN COGNITIVE RADIO NETWORKS: PRICE-DRIVEN SPECTRUM ACCESS ALGORITHMS 529 To simultaneously maximize the number of secondar... |

220 |
A Mathematical Introduction to Robotic Manipulation. Boca Raton
- Murray, Li, et al.
- 1994
(Show Context)
Citation Context ...Theorem 2: Let us define a locally asymptotically stable solution in the Lyapunov sense to be one such that all solutions starting near the stable solution remain near it and tend towards it as k → ∞ =-=[29]-=-. Algorithm 1 converges to a locally asymptotically stable solution that is feasible in (3). Remark 3: The computation of (22) and (26) can be made distributed by message passing. We may have more tha... |

132 | A survey on spectrum management in cognitive radio networks - Akyildiz, Lee, et al. - 2008 |

122 |
Log-det heuristic for matrix rank minimization with applications to hankel and euclidean distance matrices
- Fazel, Hindi, et al.
- 2003
(Show Context)
Citation Context ...ivalent to removing the secondary user that satisfies argmax j∈A νj where A is the set of secondary users. Besides the sum-of-infeasibilities heuristic, there are also other methodologies, e.g., see =-=[30]-=-, that can be used to approximately solve the vector-cardinality problem. We present another parametric problem formulation that leverages Lagrange duality to study the tradeoff between minimizing the... |

120 | BChannel access algorithms with active link protection for wireless communication networks with power control
- Bambos, Chen, et al.
- 2000
(Show Context)
Citation Context ...constraints, it has been extended to consider power constraints, e.g., the constrained Distributed Power Control (DPC) algorithm in [6], when there is an individual power constraint for each user. In =-=[7]-=-, the authors proposed joint power control and channel access algorithms for robustness against outage. In [8], [9], the authors proposed an energy-robustness tradeoff optimization to balance energy e... |

105 | Advances in cognitive radio networks: a survey
- Wang, Liu
- 2011
(Show Context)
Citation Context ...er and admission control. I. INTRODUCTION ENERGY efficiency in wireless communication is a grow-ing focus as energy consumption by wireless devices increasingly becomes a global environmental concern =-=[1]-=-–[3]. In wireless networks, power control is an important medium access control mechanism used to minimize the total energy consumption [4]. The requirement therein is to ensure that the signal is str... |

64 |
Power Control in Wireless Cellular Networks.
- Chiang, Hande, et al.
- 2008
(Show Context)
Citation Context ... devices increasingly becomes a global environmental concern [1]–[3]. In wireless networks, power control is an important medium access control mechanism used to minimize the total energy consumption =-=[4]-=-. The requirement therein is to ensure that the signal is strong enough for the desired receiver to satisfy the Signal-to-Interference-plus-Noise Ratio (SINR) requirements for reliable reception and y... |

60 | Understanding Dynamic Spectrum Access: Models, Taxonomy and Challenges."
- Buddhikot
- 2007
(Show Context)
Citation Context ...ibility problem is more severe in a cognitive radio network due to the unplanned deployment of the (unlicensed band) secondary users whose interference can overwhelm the (licensed band) primary users =-=[10]-=-–[14]. Thus, joint power and admission control is necessary to resolve the infeasibility issue in the energy minimization problem [15]. 0733-8716/14/$31.00 c© 2014 IEEE ZHAI et al.: ENERGY-INFEASIBILI... |

39 | Power control in cognitive radio networks: how to cross a multi-lane highway,”
- Ren, Zhao, et al.
- 2009
(Show Context)
Citation Context ...ally, it is equivalent to computing the maximum feasible set given an infeasible set of linear constraints [16]. In practice, admission control is needed to find the maximum feasible set of users. In =-=[17]-=-–[19], the authors studied the optimal power and admission control for fading channels under stochastic uncertainty. In [20], Mahdavi-Doost et al. proposed an algorithm that removes users based on max... |

28 | Convex approximation techniques for joint multiuser downlink beamforming and admission control
- Matskani, Sidiropoulos, et al.
- 2008
(Show Context)
Citation Context ...sed on maximizing the minimum achievable SINR. In [21], Rasti et al. proposed a distributed algorithm to remove secondary users once their instantaneous power exceed certain threshold. The authors in =-=[22]-=-–[24] proposed linear programming relaxation to obtain approximate solution to the system capacity. The authors in [25] proposed a robust distributed uplink power allocation algorithm in a cognitive r... |

27 | Spectrum management in multiuser cognitive wireless networks: Optimality and algorithm - Tan, Friedland, et al. - 2011 |

24 | Fast heuristics for the maximum feasible subsystem problem,”
- Chinneck
- 2001
(Show Context)
Citation Context ...ary users and to minimize the total energy consumption is generally hard to solve. Mathematically, it is equivalent to computing the maximum feasible set given an infeasible set of linear constraints =-=[16]-=-. In practice, admission control is needed to find the maximum feasible set of users. In [17]–[19], the authors studied the optimal power and admission control for fading channels under stochastic unc... |

17 |
Energy-efficient design of sequential channel sensing in cognitive radio networks: Optimal sensing strategy, power allocation, and sensing order
- Pei, Liang, et al.
- 2011
(Show Context)
Citation Context ...nd admission control. I. INTRODUCTION ENERGY efficiency in wireless communication is a grow-ing focus as energy consumption by wireless devices increasingly becomes a global environmental concern [1]–=-=[3]-=-. In wireless networks, power control is an important medium access control mechanism used to minimize the total energy consumption [4]. The requirement therein is to ensure that the signal is strong ... |

17 | Technical challenges for cognitive radio in the tv white space spectrum, - Shellhammer, Sadek, et al. - 2009 |

16 | Decentralized cognitive radio control based on inference from primary link control information
- Huang, Liu, et al.
- 2011
(Show Context)
Citation Context ...y. The authors in [25] proposed a robust distributed uplink power allocation algorithm in a cognitive radio network to maximize the social utility of secondary users that are admitted. The authors in =-=[26]-=- proposed a power control algorithm to maximize the throughput of the secondary users while protecting the primary users. Phunchongharn et al. proposed power control algorithms for transmission under ... |

13 | Optimal power control in rayleigh-fading heterogeneous networks,” in
- Tan
- 2011
(Show Context)
Citation Context ... it is equivalent to computing the maximum feasible set given an infeasible set of linear constraints [16]. In practice, admission control is needed to find the maximum feasible set of users. In [17]–=-=[19]-=-, the authors studied the optimal power and admission control for fading channels under stochastic uncertainty. In [20], Mahdavi-Doost et al. proposed an algorithm that removes users based on maximizi... |

12 | Joint power and admission control via linear programming deflation - Liu, Dai, et al. - 2013 |

11 | Joint power and admission control for ad-hoc and cognitive underlay networks: Convex approximation and distributed implementation,”
- Mitliagkas, Sidiropoulos, et al.
- 2011
(Show Context)
Citation Context ...n maximizing the minimum achievable SINR. In [21], Rasti et al. proposed a distributed algorithm to remove secondary users once their instantaneous power exceed certain threshold. The authors in [22]–=-=[24]-=- proposed linear programming relaxation to obtain approximate solution to the system capacity. The authors in [25] proposed a robust distributed uplink power allocation algorithm in a cognitive radio ... |

10 | BRobustness-energy tradeoff in cellular network power control
- Tan, Palomar, et al.
- 2007
(Show Context)
Citation Context ...ol (DPC) algorithm in [6], when there is an individual power constraint for each user. In [7], the authors proposed joint power control and channel access algorithms for robustness against outage. In =-=[8]-=-, [9], the authors proposed an energy-robustness tradeoff optimization to balance energy expenditure and robustness in wireless cellular networks. In a cognitive radio network, secondary users activel... |

10 | Characterization of SINR region for interfering links with constrained power,”
- Mahdavi-Doost, Ebrahimi, et al.
- 2010
(Show Context)
Citation Context ..., admission control is needed to find the maximum feasible set of users. In [17]–[19], the authors studied the optimal power and admission control for fading channels under stochastic uncertainty. In =-=[20]-=-, Mahdavi-Doost et al. proposed an algorithm that removes users based on maximizing the minimum achievable SINR. In [21], Rasti et al. proposed a distributed algorithm to remove secondary users once t... |

7 | Power control for cognitive radio networks: Axioms, algorithms,
- Sorooshyari, Tan, et al.
- 2012
(Show Context)
Citation Context ...ty problem is more severe in a cognitive radio network due to the unplanned deployment of the (unlicensed band) secondary users whose interference can overwhelm the (licensed band) primary users [10]–=-=[14]-=-. Thus, joint power and admission control is necessary to resolve the infeasibility issue in the energy minimization problem [15]. 0733-8716/14/$31.00 c© 2014 IEEE ZHAI et al.: ENERGY-INFEASIBILITY TR... |

6 | Pareto and energy-efficient distributed power control with feasibility check in wireless networks,” - Rasti, Sharafat, et al. - 2011 |

6 |
Robust distributed power control in cognitive radio networks,”
- Parsaeefard, Sharafat
- 2013
(Show Context)
Citation Context ...ry users once their instantaneous power exceed certain threshold. The authors in [22]–[24] proposed linear programming relaxation to obtain approximate solution to the system capacity. The authors in =-=[25]-=- proposed a robust distributed uplink power allocation algorithm in a cognitive radio network to maximize the social utility of secondary users that are admitted. The authors in [26] proposed a power ... |

4 |
Distributed robust scheduling and power control for cognitive spatial-reuse TDMA networks,”
- Phunchongharn, Hossain
- 1934
(Show Context)
Citation Context ...ol algorithm to maximize the throughput of the secondary users while protecting the primary users. Phunchongharn et al. proposed power control algorithms for transmission under channel uncertainty in =-=[27]-=-. The system capacity is in fact intriguingly related to the amount of energy consumption in the network. Aggressive admission control unduly removes secondary users that leads to the network being un... |

2 | Slow admission and power control for small cell networks via distributed optimization - Nai, Quek, et al. - 2013 |