Elements of information theory
Elements of information theory
Convex Optimization
Geometric programming for communication systems
Communications and Information Theory
Embracing wireless interference: analog network coding
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Foundations and Trends® in Networking
On power allocation for parallel Gaussian broadcast channels with common information
EURASIP Journal on Wireless Communications and Networking - Special issue on optimization techniques in wireless communications
Power Control By Geometric Programming
IEEE Transactions on Wireless Communications
Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks
IEEE Transactions on Wireless Communications
Comments on broadcast channels
IEEE Transactions on Information Theory
Sum capacity of Gaussian vector broadcast channels
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
A tutorial on decomposition methods for network utility maximization
IEEE Journal on Selected Areas in Communications
A tutorial on cross-layer optimization in wireless networks
IEEE Journal on Selected Areas in Communications
Joint congestion control, routing, and MAC for stability and fairness in wireless networks
IEEE Journal on Selected Areas in Communications
| Hi-index | 35.68 |
A wireless data network with K static nodes is considered. The nodes communicate simultaneously over the same narrowband channel and each node uses superposition coding to broadcast independent messages to individual nodes in the network. The goal herein is to find optimal data routes and power allocations to maximize a weighted sum of the data rates injected and reliably communicated over the network. Two instances of this problem are considered. In the first instance, each node uses a fixed power budget, whereas in the second instance the power used by each node is adjustable. For the latter case, two variants are considered: in the first there is a constraint on the power used by each node and in the second there is constraint on the total power used by all nodes. It will be shown that while the instance in which the power of each node is fixed can be cast in the form of an efficiently solvable geometric program (GP), the second instance in which the node powers are adjustable cannot be readily cast in this form. To circumvent this difficulty, an iterative technique is proposed for approximating the constraints of the original optimization problem by GP-compatible constraints. Numerical simulations suggest that this technique converges to a locally optimal solution within a few iterations.