Capacity-achieving Sparse Regression Codes via approximate message passing decoding

Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the AWGN channel at rates approaching the channel capacity. In this code, the codewords are sparse linear combinations of columns of a design matrix. In this paper, we propose an approximate message passing decoder for sparse superposition codes. The complexity of the decoder scales linearly with the size of the design matrix. The performance of the decoder is rigorously analyzed and it is shown to asymptotically achieve the AWGN capacity. We also provide simulation results to demonstrate the performance of the decoder at finite block lengths, and introduce a power allocation that significantly improves the empirical performance.RV would like to acknowledge support from a Marie Curie Career Integration Grant (GA Number 631489). AG is supported by an EPSRC Doctoral Training Award.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ISIT.2015.728280

Capacity-Achieving Sparse Superposition Codes via Approximate Message Passing Decoding.

Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the AWGN channel at rates approaching the channel capacity. The codebook is defined in terms of a Gaussian design matrix, and codewords are sparse linear combinations of columns of the matrix. In this paper, we propose an approximate message passing decoder for sparse superposition codes, whose decoding complexity scales linearly with the size of the design matrix. The performance of the decoder is rigorously analyzed and it is shown to asymptotically achieve the AWGN capacity with an appropriate power allocation. Simulation results are provided to demonstrate the performance of the decoder at finite blocklengths. We introduce a power allocation scheme to improve the empirical performance, and demonstrate how the decoding complexity can be significantly reduced by using Hadamard design matrices.Comment: 25 pages, 4 figures. IEEE Transactions on Information Theor

Design Techniques for Efficient Sparse Regression Codes

Sparse regression codes (SPARCs) are a recently introduced coding scheme for the additive white Gaussian noise channel, for which polynomial time decoding algorithms have been proposed which provably achieve the Shannon channel capacity. One such algorithm is the approximate message passing (AMP) decoder. However, directly implementing these decoders does not yield good empirical performance at practical block lengths. This thesis develops techniques for improving both the error rate performance, and the time and memory complexity, of the AMP decoder. It focuses on practical and efficient implementations for both single- and multi-user scenarios. A key design parameter for SPARCs is the power allocation, which is a vector of coefficients which determines how codewords are constructed. In this thesis, novel power allocation schemes are proposed which result in several orders of magnitude improvement to error rate compared to previous designs. Further improvements to error rate come from investigating the role of other SPARC construction parameters, and from performing an online estimation of a key AMP parameter instead of using a pre-computed value. Another significant improvement to error rates comes from a novel three-stage decoder which combines SPARCs with an outer code based on low-density parity-check codes. This construction protects only vulnerable sections of the SPARC codeword with the outer code, minimising the impact to the code rate. The combination provides a sharp waterfall in bit error rates and very low overall codeword error rates. Two changes to the basic SPARC structure are proposed to reduce computational and memory complexity. First, the design matrix is replaced with an efficient in-place transform based on Hadamard matrices, which dramatically reduces the overall decoder time and memory complexity with no impact on error rate. Second, an alternative SPARC design is developed, called Modulated SPARCs. These are shown to also achieve the Shannon channel capacity, while obtaining similar empirical error rates to the original SPARC, and permitting a further reduction in time and memory complexity. Finally, SPARCs are implemented for the broadcast and multiple access channels, and for the multiple description and Wyner-Ziv source coding models. Designs for appropriate power allocations and decoding strategies are proposed and are found to give good empirical results, demonstrating that SPARCs are also well suited to these multi-user settings.Funded by a Doctoral Training Award from the Engineering and Physical Sciences Research Council

Injury incidence and burden in a youth elite football academy: A four-season prospective studyof 551 players aged from under 9 to under 19 years

Objective Investigate the incidence and burden of injuries by age group in youth football (soccer) academy players during four consecutive seasons. Methods All injuries that caused time-loss or required medical attention (as per consensus definitions) were prospectively recorded in 551 youth football players from under 9 years to under 19 years. Injury incidence (II) and burden (IB) were calculated as number of injuries per squad season (s-s), as well as for type, location and age groups. Results A total of 2204 injuries were recorded. 40% (n=882) required medical attention and 60% (n=1322) caused time-loss. The total time-loss was 25 034 days. A squad of 25 players sustained an average of 30 time-loss injuries (TLI) per s-s with an IB of 574 days lost per s-s. Compared with the other age groups, U-16 players had the highest TLI incidence per s-s (95% CI lower-upper): II= 59 (52 to 67); IB=992 days; (963 to 1022) and U-18 players had the greatest burden per s-s: II= 42.1 (36.1 to 49.1); IB= 1408 days (1373 to 1444). Across the cohort of players, contusions (II=7.7/s-s), sprains (II=4.9/s-s) and growth-related injuries (II=4.3/s-s) were the most common TLI. Meniscus/cartilage injuries had the greatest injury severity (95% CI lower-upper): II= 0.4 (0.3 to 0.7), IB= 73 days (22 to 181). The burden (95% CI lower-upper) of physeal fractures (II= 0.8; 0.6 to 1.2; IB= 58 days; 33 to 78) was double than non-physeal fractures. Summary At this youth football academy, each squad of 25 players averaged 30 injuries per season which resulted in 574 days lost. The highest incidence of TLI occurred in under-16 players, while the highest IB occurred in under-18 players

Association of Skeletal Maturity and Injury Risk in Elite Youth Soccer Players:A 4-Season Prospective Study With Survival Analysis

Background: The association between injury risk and skeletal maturity in youth soccer has received little attention. Purpose: To prospectively investigate injury patterns and incidence in relation to skeletal maturity in elite youth academy soccer players and to determine the injury risks associated with the skeletal maturity status, both overall and to the lower limb apophysis. Study Design: Descriptive epidemiology study. Methods: All injuries that required medical attention and led to time loss were recorded prospectively during 4 consecutive seasons in 283 unique soccer players from U-13 (12 years of age) to U-19 (18 years). The skeletal age (SA) was assessed in 454 player-seasons using the Fels method, and skeletal maturity status (SA minus chronological age) was classified as follows: late, SA >1 year behind chronological age; normal, SA ±1 year of chronological age; early, SA >1 year ahead of chronological age; and mature, SA = 18 years. An adjusted Cox regression model was used to analyze the injury risk. Results: A total of 1565 injuries were recorded; 60% were time-loss injuries, resulting in 17,772 days lost. Adjusted injury-free survival analysis showed a significantly greater hazard ratio (HR) for different status of skeletal maturity: early vs normal (HR = 1.26 [95% CI, 1.11-1.42]; P < .001) and early vs mature (HR = 1.35 [95% CI, 1.17-1.56]; P < .001). Players who were skeletally mature at the wrist had a substantially decreased risk of lower extremity apophyseal injuries (by 45%-61%) compared with late (P < .05), normal (P < .05), and early (P < .001) maturers. Conclusion: Musculoskeletal injury patterns and injury risks varied depending on the players’ skeletal maturity status. Early maturers had the greatest overall adjusted injury risk. Players who were already skeletally mature at the wrist had the lowest risk of lower extremity apophyseal injuries but were still vulnerable for hip and pelvis apophyseal injuries

Prevalence of multimorbidity and its association with outcomes in older emergency general surgical patients : an observational study

Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.Peer reviewedPublisher PD

A dynamic microsimulation model for epidemics.

Funder: Aerospace Technology InstituteFunder: UK Research and InnovationFunder: The Alan Turing InstituteA large evidence base demonstrates that the outcomes of COVID-19 and national and local interventions are not distributed equally across different communities. The need to inform policies and mitigation measures aimed at reducing the spread of COVID-19 highlights the need to understand the complex links between our daily activities and COVID-19 transmission that reflect the characteristics of British society. As a result of a partnership between academic and private sector researchers, we introduce a novel data driven modelling framework together with a computationally efficient approach to running complex simulation models of this type. We demonstrate the power and spatial flexibility of the framework to assess the effects of different interventions in a case study where the effects of the first UK national lockdown are estimated for the county of Devon. Here we find that an earlier lockdown is estimated to result in a lower peak in COVID-19 cases and 47% fewer infections overall during the initial COVID-19 outbreak. The framework we outline here will be crucial in gaining a greater understanding of the effects of policy interventions in different areas and within different populations