Vector quantization and signal compression
Vector quantization and signal compression
Energy-efficient packet transmission over a wireless link
IEEE/ACM Transactions on Networking (TON)
Convex Optimization
IEEE Transactions on Information Theory
Capacity and optimal resource allocation for fading broadcast channels .I. Ergodic capacity
IEEE Transactions on Information Theory
Hi-index | 0.00 |
We deal with energy efficient time-division multiple access (TDMA) over fading channels with finite-rate feedback in the power-limited regime. Through finite-rate feedback from the access point, users acquire quantized channel state information. The goal is to map channel quantization states to adaptive modulation and coding (AMC) modes and allocate optimally time slots to users so that transmitpower is minimized. To this end, we develop two joint quantization and resource allocation approaches. In the first one, we rely on the quantization regions associated to each AMC mode and the time allocation policy inherited from the perfect CSI case to optimize the fixed transmit-power across quantization states. In the second approach, we pursue separable optimization and resort to coordinate descent algorithms to solve the following two sub-problems: (a) given a time allocation, we optimize the quantization regions and transmit-powers; and (b) with improved quantization regions, we optimize the time allocation policy. Numerical results are present to evaluate the energy savings and compare the novel approaches.