Finite Blocklength Rates over a Fading Channel with CSIT and CSIR

In this work, we obtain lower and upper bounds on the maximal transmission rate at a given codeword length $n$, average probability of error $\epsilon$ and power constraint $\bar{P}$, over a finite valued, block fading additive white Gaussian noise (AWGN) channel with channel state information (CSI) at the transmitter and the receiver. These bounds characterize deviation of the finite blocklength coding rates from the channel capacity which is in turn achieved by the water filling power allocation across time. The bounds obtained also characterize the rate enhancement possible due to the CSI at the transmitter in the finite blocklength regime. The results are further elucidated via numerical examples.Comment: 10 pages, 2 figures, results for finite valued fading states, typos corrected, proofs elaborated, lower bound under short term power constraint improve

Polar Codes over Fading Channels with Power and Delay Constraints

The inherent nature of polar codes being channel specific makes it difficult to use them in a setting where the communication channel changes with time. In particular, to be able to use polar codes in a wireless scenario, varying attenuation due to fading needs to be mitigated. To the best of our knowledge, there has been no comprehensive work in this direction thus far. In this work, a practical scheme involving channel inversion with the knowledge of the channel state at the transmitter, is proposed. An additional practical constraint on the permissible average and peak power is imposed, which in turn makes the channel equivalent to an additive white Gaussian noise (AWGN) channel cascaded with an erasure channel. It is shown that the constructed polar code could be made to achieve the symmetric capacity of this channel. Further, a means to compute the optimal design rate of the polar code for a given power constraint is also discussed.Comment: 6 pages, 6 figure

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Information Rates over Point-to-Point and Multi-user Wireless Channels with Energy and Delay Constraints

In this thesis, we consider communication systems having energy, delay and reliability constraints. We characterize optimal communication rates achievable over these systems. First we consider point-to-point communication setting. In this context, first, we characterize achievable rates for an energy harvesting point-to-point channel with additive Gaussian noise. These rates are shown to be close to the optimal rates under various assumptions on the system architecture. Next, we consider a non-energy harvesting, point-to-point block fading wireless channel with Gaussian noise, subjected to canonical peak and average power constraints. We characterize lower and upper bounds on the maximal channel coding rate with channel state information at the transmitter and the receiver, at a given codeword length and average probability of error. The bounds characterize back-off from the water-filling capacity in the finite block length regime. Subsequently, we extend the finite block length results derived for the non-energy harvesting channel, to the case where the transmitter is energy harvesting. Next, we consider multi-user communication scenario. In this setting, first, we consider a Gaussian multiple access channel with energy harvesting transmitters. We obtain the capacity region of the channel with transmitters having infinite energy buffer. In addition, with transmitters assumed to have finite energy buffers, we characterize achievable rate regions. Next, we obtain inner bounds to the ergodic capacity region of a block fading Gaussian multiple access channel, with finite codeword length, non-vanishing average error probability and peak power constraint on the codewords. Subsequently, we consider a fading Gaussian broadcast channel under the assumption that both the transmitter and the receivers harvests energy and the receivers treat the transmitter as a radio frequency energy source. This corresponds to the paradigm of simultaneous wireless information and power transfer. In this scenario, we characterize the fundamental limits of simultaneous wireless information and power transfer under a minimum-rate constraint. Finally, we consider an energy harvesting, fading Gaussian multiple access channel and the receivers treat transmitter as an radio-frequency energy source. In this setting as well, we characterize the information theoretic limits under a minimum-rate constraint at each user