• Corpus ID: 18963179

Power Control for Maximum Throughput in Spectrum Underlay Cognitive Radio Networks

  title={Power Control for Maximum Throughput in Spectrum Underlay Cognitive Radio Networks},
  author={John Tadrous and Ahmed Sultan and Mohammed Nafie and Amr El-Keyi},
We investigate power allocation for users in a spectrum underlay cognitive network. Our objective is to find a power control scheme that allocates transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service (QoS) of the primary users greater than a certain minimum limit. Since an optimum solution to our problem is computationally intractable, as the optimization problem is non-convex, we propose an iterative… 

Figures from this paper

Maximum–Minimum Throughput for MIMO Systems in Cognitive Radio Networks
  • JuiTeng Wang
  • Business
    IEEE Transactions on Vehicular Technology
  • 2014
This work presents a proposition to simplify the optimization of the power assignment for multiple-input-multiple-output (MIMO) systems in cognitive radio (CR) networks and finds that MMTPA outperforms EPA and IPC in the minimal throughput among all SUs.
An achievable rate region for a primary network shared by a secondary link
This work investigates the effect of rate-splitting on the rate region for two cases of a multiple access primary network with N transmitters and determines the optimal rate- Splitting that maximizes the sum throughput of the primary network and the secondary link subject to a constraint on primary rate.
On Rate-Splitting by a Secondary Link in Multiple Access Primary Network
A necessary and sufficient condition to determine which primary signal that the secondary receiver can decode without degrading the range of primary achievable sum rates is provided and it is shown that the probability of having at least one primary user satisfying this condition grows with the primary signal to noise ratio.


Resource allocation for spectrum underlay in cognitive radio networks
  • L. Le, E. Hossain
  • Computer Science
    IEEE Transactions on Wireless Communications
  • 2008
A resource allocation framework is presented for spectrum underlay in cognitive wireless networks and admission control algorithms to be used during high network load conditions so that QoS requirements of all admitted secondary users are satisfied while keeping the interference to primary users below the tolerable limit.
Distributed admission and power control for cognitive radios in spectrum underlay networks
This paper proposes an efficient distributed algorithm with reasonable complexity that provides results close to the optimum solution without requiring neither a large amount of signaling nor a wide range of information about the system parameters.
Joint rate and power allocation for cognitive radios in dynamic spectrum access environment
A complete framework to perform joint admission control and rate/power allocation for secondary users such that both QoS and interference constraints are only violated within desired limits is developed.
Dynamic Spectrum Management: Complexity and Duality
  • Z. Luo, Shuzhong Zhang
  • Computer Science, Mathematics
    IEEE Journal of Selected Topics in Signal Processing
  • 2008
Using the Lyapunov theorem in functional analysis, this work rigorously proves a result first discovered by Yu and Lui (2006) that there is a zero duality gap for the continuous (Lebesgue integral) formulation of the discretized version of this nonconvex problem.
Sequential Geometric Programming for 2 × 2 Interference Channel Power Control
We analyze the performance of sequential geometric programming (SGP) in solving the nonconvex power control problem of maximizing the sum capacity of the interference channel with no multiuser
Technical Note - A General Inner Approximation Algorithm for Nonconvex Mathematical Programs
Inner approximation algorithms have had two major roles in the mathematical programming literature. Their first role was in the construction of algorithms for the decomposition of large-scale
Convex Optimization
A comprehensive introduction to the subject of convex optimization shows in detail how such problems can be solved numerically with great efficiency.
Power Control By Geometric Programming
This work presents a systematic method of distributed algorithms for power control that is geometric-programming-based and shows that in the high Signal-to- interference Ratios (SIR) regime, these nonlinear and apparently difficult, nonconvex optimization problems can be transformed into convex optimized problems in the form of geometric programming.
CVX: Matlab software for disciplined convex programming
  • CVX: Matlab software for disciplined convex programming
  • 2009