Optimal power allocation for OFDM-based cognitive radio with new primary transmission protection criteria

Kang, Xin; Garg, H.K.; Liang, Ying-Chang; Zhang, Rui

doi:10.1109/twc.2010.06.090912

Cited by 159 publications

(111 citation statements)

References 16 publications

Supporting

Mentioning

111

Contrasting

Order By: Relevance

“…Let D be the set specified by the remaining constraints in (14d), (14e), and (14f). Consequently, problem (14) can be given by the subproblems C int , C SIC , and C SC defined over S 2 , S 3 , and S 4 , respectively, as…”

Section: Power Allocation Optimizationmentioning

confidence: 99%

“…The optimal power allocation to achieve ergodic capacity and outage capacity in fading channel was derived in [13]. In [14], the authors maximized the secondary achievable rate under a new criterion referred to as rate-loss constraint. The authors in [15] investigated the problem of random subcarrier allocation in OFDM-based CR networks without any spectrum-sensing information at the SU.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Resource allocation for OFDM-based multiuser cooperative underlay cognitive systems

Chami

Pischella

Ruyet

2017

J Wireless Com Network

View full text Add to dashboard Cite

This paper investigates the resource allocation problem for a multiuser underlay cognitive system where the secondary system is allowed to transmit and cooperate with the primary system. In this scenario, the secondary users are subject to two main constraints in the presence of the primary user: their total power budget and the allowable interference threshold at the primary receiver. Power and subcarrier allocation problems are detailed in order to maximize the system sum rate. In this work, we highlight the benefits of the proposed multiuser adaptive algorithm which encompasses three phases. The first step includes the adaptive selection of the decoding strategy at the secondary receiver which is either treating interference as noise or performing successive interference cancelation or superposition coding. The second step describes the subcarrier allocation among the different users. Finally, the third step details the optimal distribution of the available power budget on the users. The problem is first treated assuming perfect channel state information (CSI). The simulation results show that our proposed scheme achieves higher secondary and sum rates compared to existing approaches with perfect CSI. The robustness of the proposed algorithm when the secondary user has only partial information about channel gains is also derived.

show abstract

Section: Power Allocation Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Resource allocation for OFDM-based multiuser cooperative underlay cognitive systems

Chami

Pischella

Ruyet

2017

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…The orthogonal frequency-division multiplexing (OFDM) can be employed in a cognitive radio network by dividing the primary user's unused bandwidth into a number of sub-bands available for use in the cognitive radio systems [7]. The frequency efficiency of OFDM is very high and attracts cognitive radio users [8,9].…”

Section: Problem Formulationmentioning

confidence: 99%

A Power Allocation Algorithm Based on Variational Inequality Problem for Cognitive Radio Networks

2017

J Inf Process Syst

View full text Add to dashboard Cite

Power allocation is an important factor for cognitive radio networks to achieve higher communication capacity and faster equilibrium. This paper considers power allocation problem to each cognitive user to maximize capacity of the cognitive systems subject to the constraints on the total power of each cognitive user and the interference levels of the primary user. Since this power control problem can be formulated as a mixed-integer nonlinear programming (NP) equivalent to variational inequality (VI) problem in convex polyhedron which can be transformed into complementary problem (CP), we utilize modified projection method to solve this CP problem instead of finding NP solution and give a power control allocation algorithm with a subcarrier allocation scheme. Simulation results show that the proposed algorithm performs well and effectively reduces the system power consumption with almost maximum capacity while achieve Nash equilibrium.

show abstract

“…We model the channel gains as independent, identically distributed Rayleigh random variables and assume that they are known at the CR-BS [13,19,20]. It is further assumed that the instantaneous channel fading gains of all links change so slowly that they can be regarded as constant during each transmission slot.…”

Section: System Modelmentioning

confidence: 99%

Joint optimization of detection threshold and resource allocation in infrastructure-based multi-band cognitive radio networks

Shi

Wang

et al. 2012

J Wireless Com Network

View full text Add to dashboard Cite

Consider an infrastructure-based multi-band cognitive radio network (CRN) where secondary users (SUs) opportunistically access a set of sub-carriers when sensed as idle. The carrier sensing threshold which affects the access opportunities of SUs is conventionally regarded as static and treated independently from the resource allocation in the model. In this article, we study jointly the optimization of detection threshold and resource allocation with the goal of maximizing the total downlink capacity of SUs in such CRNs. The optimization problem is formulated considering three sets of variables, i.e., detection threshold, sub-carrier assignment and power allocation, with constraints on the PUs' rate loss and the power budget of the CR base station. Two schemes, referred to as offline and online algorithms respectively, are proposed to solve the optimization problem. While the offline algorithm finds the global optimal solution with high complexity, the online algorithm provides a close-to-optimal solution with much lower complexity and realtime capability. The performance of the proposed schemes is evaluated by extensive simulations and compared with the conventional static threshold selection algorithm specified in the IEEE 802.22 standard.

show abstract

Optimal power allocation for OFDM-based cognitive radio with new primary transmission protection criteria

Cited by 159 publications

References 16 publications

Resource allocation for OFDM-based multiuser cooperative underlay cognitive systems

Resource allocation for OFDM-based multiuser cooperative underlay cognitive systems

A Power Allocation Algorithm Based on Variational Inequality Problem for Cognitive Radio Networks

Joint optimization of detection threshold and resource allocation in infrastructure-based multi-band cognitive radio networks

Contact Info

Product

Resources

About