Opportunistic spectral usage: bounds and a multi-band CSMA/CA protocol
IEEE/ACM Transactions on Networking (TON)
Training and limited feedback strategies for fading channels
Training and limited feedback strategies for fading channels
Optimal channel probing and transmission scheduling for opportunistic spectrum access
IEEE/ACM Transactions on Networking (TON)
IEEE Transactions on Information Theory
Capacity and mutual information of wideband multipath fading channels
IEEE Transactions on Information Theory
Bandwidth scaling for fading multipath channels
IEEE Transactions on Information Theory
Fading channels: how perfect need "perfect side information" be?
IEEE Transactions on Information Theory
Spectral efficiency in the wideband regime
IEEE Transactions on Information Theory
How much training is needed in multiple-antenna wireless links?
IEEE Transactions on Information Theory
Channel Coherence in the Low-SNR Regime
IEEE Transactions on Information Theory
Opportunistic Downlink Transmission With Limited Feedback
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Optimal Competitive Algorithms for Opportunistic Spectrum Access
IEEE Journal on Selected Areas in Communications
On training with feedback in wideband channels
IEEE Journal on Selected Areas in Communications
Hi-index | 754.84 |
We consider the capacity of a wideband fading channel with partial feedback, subject to an average power constraint. The channel is modeled as a set of parallel independent block Rayleigh fading subchannels with finite coherence time (L channel uses). The transmitter probes a subset of subchannels during each coherence time by transmitting pilot sequences for channel estimation. For each subchannel probed, one bit of feedback indicates whether or not the channel gain exceeds a threshold allowing transmission. Our problem is to optimize jointly the training (both length and power), number of sub-channels probed (probing bandwidth), and feedback threshold to maximize the achievable rate (lower bound on ergodic capacity) taking into account the subchannel estimation error. Optimizing the probing bandwidth balances diversity against the quality of the subchannel estimate. We show that the achievable rate increases as S log L, where S is the signal-to-noise ratio, and exceeds the capacity with impulsive signaling (given by S) when L exceeds a (positive) threshold value. Moreover, the optimal probing bandwidth scales as S L/log2 L. In contrast, without feedback the optimal probing bandwidth for the probing scheme scales as SL1/3 and the achievable rate converges to S, where the gap diminishes as SL-1/3.