The capacity of average and peak power constrained fading channels with channel side information

Abstract

Abstract-We derive the ergodic capacity of discrete-time fading channel with additive Gaussian noise subject to both peak and average power constraint. The average power can be interpreted as the cost that we incur to achieve a certain rate. On the other hand, the motivation of this analysis comes from the fact that there is also a peak power limitation in practical communication system. It is been shown that the optimal power adaption is no longer water-filling or constant power adaption which is the case where there is no limitation on the peak power. The numerical results show that the importance of peak power constraint become negligible for relatively low available average power, while it is limiting the capacity to be finite even as available average power goes to infinity.

Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity

“…It is also noticed that the power allocation scheme given by (12) has the same structure as that in [16], where the ergodic capacity of fading channels is studied under both peak and average transmit power constraints. The main difference is that the power allocation scheme given by (12) is not only related to SU channel but also related to the channel between SU-Tx and PU-Rx.…”

Power Allocation in Wireless Systems Subject to Long-Term and Short-Term Power Constraints

“…As we can see, there is always a small range in which the second region (case 3) occurs. It gets even smaller if we increase the number of antennas n. optimal,n=10 optimal,n=2 sub−optimal,n=10 sub−optimal,n=2 without CSIT,n=10 without CSIT,n=2 Since the capacity versus average SNR for the singleantenna channel has been plotted in [5], we only show the results for MISO systems. For comparison, we have also plotted the capacity for the case in which there is CSI at receiver only (labeled by "Without CSIT").…”

“…The actual received SNR with power adaption is P (γ)γ/P . The authors in [5] have proved a coding theorem that says the ergodic capacity is the solution to the following optimization problem:…”

“…Case 3, 1 < α ≤ α max : In this case, both power constraints play a role and the optimal power allocation is [5] …”

“…This problem has been partially studied in [5] for the case of single-antenna systems, in which a coding theorem is proved for the capacity of fading channels. However, we study this problem in more detail and extend the results to the case of multiple-input-single-output (MISO) and MIMO channels.…”