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Sinan Gezici  One of the best experts on this subject based on the ideXlab platform.

Optimal Detector Randomization for Multiuser Communications Systems
IEEE Transactions on Communications, 2013CoAuthors: Mehmet Emin Tutay, Sinan Gezici, Orhan ArikanAbstract:Optimal detector Randomization is studied for the downlink of a multiuser communications system, in which users can perform timesharing among multiple detectors. A formulation is provided to obtain optimal signal amplitudes, detectors, and detector Randomization factors. It is shown that the solution of this joint optimization problem can be calculated in two steps, resulting in significant reduction in computational complexity. It is proved that the optimal solution is achieved via Randomization among at most min{K,Nd} detector sets, where K is the number of users and \Nd is the number of detectors at each receiver. Lower and upper bounds are derived on the performance of optimal detector Randomization, and it is proved that the optimal detector Randomization approach can reduce the worstcase average probability of error of the optimal approach that employs a single detector for each user by up to K times. Various sufficient conditions are obtained for the improvability and nonimprovability via detector Randomization. In the special case of equal crosscorrelations and noise powers, a simple solution is developed for the optimal detector Randomization problem, and necessary and sufficient conditions are presented for the uniqueness of that solution. Numerical examples are provided to illustrate the improvements achieved via detector Randomization.

Optimal Randomization of Signal Constellations on the Downlink of a Multiuser DSCDMA System
IEEE Transactions on Wireless Communications, 2013CoAuthors: Mehmet Emin Tutay, Sinan Gezici, Orhan ArikanAbstract:In this study, the jointly optimal power control with signal constellation Randomization is proposed for the downlink of a multiuser communications system. Unlike a conventional system in which a fixed signal constellation is employed for all the bits of a user (for given channel conditions and noise power), power control with signal constellation Randomization involves Randomization/timesharing among different signal constellations for each user. A formulation is obtained for the problem of optimal power control with signal constellation Randomization, and it is shown that the optimal solution can be represented by a Randomization among (K+1) or fewer distinct signal constellations for each user, where K denotes the number of users. In addition to the original nonconvex formulation, an approximate solution based on convex relaxation is derived. Then, detailed performance analysis is presented when the receivers employ symmetric signaling and sign detectors. Specifically, the maximum asymptotical improvement ratio is shown to be equal to the number of users, and the conditions under which the maximum and minimum asymptotical improvement ratios are achieved are derived. Numerical examples are presented to investigate the theoretical results, and to illustrate performance improvements achieved via the proposed approach.

Optimal stochastic signal design and detector Randomization in the neymanpearson framework
2012 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2012CoAuthors: Berkan Dulek, Sinan GeziciAbstract:Power constrained onoff keying communications systems are investigated in the presence of stochastic signaling and detector Randomization. The joint optimal design of decision rules, stochastic signals, and detector Randomization factors is performed. It is shown that the solution to the most generic optimization problem that employs both stochastic signaling and detector Randomization can be obtained as the Randomization among no more than three NeymanPearson (NP) decision rules corresponding to three deterministic signal vectors. Numerical examples are also presented.

Detector Randomization and Stochastic Signaling for Minimum Probability of Error Receivers
IEEE Transactions on Communications, 2012CoAuthors: Berkan Dulek, Sinan GeziciAbstract:Optimal receiver design is studied for a communications system in which both detector Randomization and stochastic signaling can be performed. First, it is proven that stochastic signaling without detector Randomization cannot achieve a smaller average probability of error than detector Randomization with deterministic signaling for the same average power constraint and noise statistics. Then, it is shown that the optimal receiver design results in a Randomization between at most two maximum aposteriori probability (MAP) detectors corresponding to two deterministic signal vectors. Numerical examples are provided to explain the results.
S.m. Meerkov  One of the best experts on this subject based on the ideXlab platform.

Power Randomization in ALOHA access control for wireless networks
Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), 1998CoAuthors: S.m. MeerkovAbstract:Randomization of transmission power in ALOHA access control for wireless networks is introduced and analyzed. It is shown that the power Randomization, introduced appropriately, leads to a substantial throughput improvement and to elimination of the bistable behavior.
David J Torgerson  One of the best experts on this subject based on the ideXlab platform.

The use of unequal randomisation in clinical trials — An update
Contemporary Clinical Trials, 2015CoAuthors: Emily Peckham, Jo C Dumville, Sally Brabyn, Liz Cook, Thomas Devlin, David J TorgersonAbstract:Abstract Objective To update a 2005 review of the reasons researchers have given for the use of unequal randomisation in randomised controlled trials (RCTs). Main measures Intervention being tested; type of study; number of participants; randomisation ratio; sample size calculation and reason given for using unequal randomisation. Methods Review of trials using unequal randomisation. Databases and sources Cochrane library, Medline and CINAHL. Results A total of 86 trials were identified. Of these 82 trials (95%) recruited patients in favour of the experimental group. Various reasons for the use of unequal randomisation were given including: gaining treatment experience; identification of adverse events; ethical; logistic and enhancing recruitment. No trial reported explicitly used it for costeffectiveness. Most of the papers (i.e. 47, 55%) did not state why they had used unequal randomisation and only 38 trials (44%) appeared to have taken the unequal randomisation into account in their sample size calculation. Conclusion Most studies did not mention the rationale for unequal allocation, and a significant proportion did not appear to account for it in the sample size calculations. Unlike the previous review economic considerations were not stated as a rationale for its use. A number of trials used it to enhance recruitment, although this has not been tested.

the use of unequal randomisation ratios in clinical trials a review
Contemporary Clinical Trials, 2006CoAuthors: Jo C Dumville, Seokyung Hahn, Jeremy N V Miles, David J TorgersonAbstract:Abstract Objective To examine reasons given for the use of unequal randomisation in randomised controlled trials (RCTs). Main Measures Setting of the trial; intervention being tested; randomisation ratio; sample size calculation; reason given for randomisation. Methods Review of trials using unequal randomisation. Databases and sources Cochrane library, Medline, Pub Med and Science Citation Index. Results A total of 65 trials were identified; 56 were twoarmed trials and nine trials had more than two arms. Of the twoarm trials, 50 trials recruited patients in favour of the experimental group. Various reasons for the use of unequal randomisation were given. Six studies stated that they used unequal randomisation to reduce the cost of the trial, with one screening trial limited by the availability of the intervention. Other reasons for using unequal allocation were: avoiding loss of power from dropout or crossover, ethics and the gaining of additional information on the treatment. Thirty seven trials papers (57%) did not state why they had used unequal randomisation and only 14 trials (22%) appeared to have taken the unequal randomisation into account in their sample size calculation. Conclusion Although unequal randomisation offers a number of advantages to trials the method is rarely used and is especially underutilised to reduce trial costs. Unequal randomisation should be considered more in trial design especially where there are large differences between treatment costs.
Berkan Dulek  One of the best experts on this subject based on the ideXlab platform.

Optimal stochastic signal design and detector Randomization in the neymanpearson framework
2012 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2012CoAuthors: Berkan Dulek, Sinan GeziciAbstract:Power constrained onoff keying communications systems are investigated in the presence of stochastic signaling and detector Randomization. The joint optimal design of decision rules, stochastic signals, and detector Randomization factors is performed. It is shown that the solution to the most generic optimization problem that employs both stochastic signaling and detector Randomization can be obtained as the Randomization among no more than three NeymanPearson (NP) decision rules corresponding to three deterministic signal vectors. Numerical examples are also presented.

Detector Randomization and Stochastic Signaling for Minimum Probability of Error Receivers
IEEE Transactions on Communications, 2012CoAuthors: Berkan Dulek, Sinan GeziciAbstract:Optimal receiver design is studied for a communications system in which both detector Randomization and stochastic signaling can be performed. First, it is proven that stochastic signaling without detector Randomization cannot achieve a smaller average probability of error than detector Randomization with deterministic signaling for the same average power constraint and noise statistics. Then, it is shown that the optimal receiver design results in a Randomization between at most two maximum aposteriori probability (MAP) detectors corresponding to two deterministic signal vectors. Numerical examples are provided to explain the results.
Jo C Dumville  One of the best experts on this subject based on the ideXlab platform.

The use of unequal randomisation in clinical trials — An update
Contemporary Clinical Trials, 2015CoAuthors: Emily Peckham, Jo C Dumville, Sally Brabyn, Liz Cook, Thomas Devlin, David J TorgersonAbstract:Abstract Objective To update a 2005 review of the reasons researchers have given for the use of unequal randomisation in randomised controlled trials (RCTs). Main measures Intervention being tested; type of study; number of participants; randomisation ratio; sample size calculation and reason given for using unequal randomisation. Methods Review of trials using unequal randomisation. Databases and sources Cochrane library, Medline and CINAHL. Results A total of 86 trials were identified. Of these 82 trials (95%) recruited patients in favour of the experimental group. Various reasons for the use of unequal randomisation were given including: gaining treatment experience; identification of adverse events; ethical; logistic and enhancing recruitment. No trial reported explicitly used it for costeffectiveness. Most of the papers (i.e. 47, 55%) did not state why they had used unequal randomisation and only 38 trials (44%) appeared to have taken the unequal randomisation into account in their sample size calculation. Conclusion Most studies did not mention the rationale for unequal allocation, and a significant proportion did not appear to account for it in the sample size calculations. Unlike the previous review economic considerations were not stated as a rationale for its use. A number of trials used it to enhance recruitment, although this has not been tested.

the use of unequal randomisation ratios in clinical trials a review
Contemporary Clinical Trials, 2006CoAuthors: Jo C Dumville, Seokyung Hahn, Jeremy N V Miles, David J TorgersonAbstract:Abstract Objective To examine reasons given for the use of unequal randomisation in randomised controlled trials (RCTs). Main Measures Setting of the trial; intervention being tested; randomisation ratio; sample size calculation; reason given for randomisation. Methods Review of trials using unequal randomisation. Databases and sources Cochrane library, Medline, Pub Med and Science Citation Index. Results A total of 65 trials were identified; 56 were twoarmed trials and nine trials had more than two arms. Of the twoarm trials, 50 trials recruited patients in favour of the experimental group. Various reasons for the use of unequal randomisation were given. Six studies stated that they used unequal randomisation to reduce the cost of the trial, with one screening trial limited by the availability of the intervention. Other reasons for using unequal allocation were: avoiding loss of power from dropout or crossover, ethics and the gaining of additional information on the treatment. Thirty seven trials papers (57%) did not state why they had used unequal randomisation and only 14 trials (22%) appeared to have taken the unequal randomisation into account in their sample size calculation. Conclusion Although unequal randomisation offers a number of advantages to trials the method is rarely used and is especially underutilised to reduce trial costs. Unequal randomisation should be considered more in trial design especially where there are large differences between treatment costs.