FPGA implementation of a sub-400ns 6G free-space optical wireless communications transmitter.

Future wireless networks are planned to service many applications with an Ultra Low-Latency (ULL) requirement. Numerous 6G systems have been proposed including more traditional electro-magnetic (EM) antenna transmissions and optical wireless communications (OWC). For extremely wide-band operation, the traditional approaches require digital pre-distortion and other processing techniques which, in turn, require more computational resources and processing times thus increasing latency. Alternatively, OWC has the potential for extremely wide bandwidths in 6G without the need for as much digital signal processing. In order to realise ULL performance, a minimum number of digital signal processing (DSP) blocks is required, as well as an optimal design of each of these. In this letter, we propose a DSP solution for ULL and peak to average power ratio (PAPR) reduction for OWC systems. Unitary checkerboard precoding - orthogonal frequency division multiplexing (UCP-OFDM) is chosen as the modulation scheme and has been implemented within a single digital block avoiding the use of standard OFDM which would otherwise require multiple digital blocks. Experimentally validated results successfully demonstrate a 2.21184 GSps wireless link at distances of up to 2m in noisy daylight settings. Bit error rates (BER) of 0 at root mean square (RMS) error vector magnitude (EVM) of 4.09% are achieved. A complete digital line-up of an OWC transmitter chain for this work contains only three core blocks and ULL of less than 400 ns.

High frequency resistive switching behavior of amorphous TiO2 and NiO.

Resistive switching (RS) of Transition Metal Oxides (TMOs) has become not only an attractive choice for the development of next generation non-volatile memory, but also as a suitable family of materials capable of supporting high-frequency and high-speed switching needed for the next generation wireless communication technologies, such as 6G. The exact mechanism of RS is not yet clearly understood; however, it is widely accepted to be related to the formation and rupture of sub-stoichiometric conductive filaments (Magnéli phases) of the respective oxides upon activation. Here, we examine the switching behaviour of amorphous TiO2 and NiO both under the DC regime and in the high frequency mode. We show that the DC resistance of amorphous TiO2 is invariant of the length of the active region. In contrast, the resistance of the NiO samples exhibits a strong dependence on the length, and its DC resistance reduces as the length is increased. We further show that the high frequency switching characteristics of TiO2, reflected in insertion losses in the ON state and isolation in the OFF state, are far superior to those of NiO. Fundamental inferences stem from these findings, which not only enrich our understanding of the mechanism of conduction in binary/multinary oxides but are essential for the enablement of widespread use of binary/multinary oxides in emerging non-volatile memory and 6G mm-wave applications. As an example of a possible application supported by TMOs, is a Reflective-Type Variable Attenuator (RTVA), shown here. It is designed to operate at a centre frequency of 15 GHz. The results indicate that it has a dynamic range of no less than 18 dB with a maximum insertion loss of 2.1 dB.

Towards Automation and Augmentation of the Design of Schedulers for Cellular Communications Networks.

Evolutionary computation is used to automatically evolve small cell schedulers on a realistic simulation of a 4G-LTE heterogeneous cellular network. Evolved schedulers are then further augmented by human design to improve robustness. Extensive analysis of evolved solutions and their performance across a wide range of metrics reveals evolution has uncovered a new human-competitive scheduling technique which generalises well across cells of varying sizes. Furthermore, evolved methods are shown to conform to accepted scheduling frameworks without the evolutionary process being explicitly told the form of the desired solution. Evolved solutions are shown to out-perform a human-engineered state-of-the-art benchmark by up to 50%. Finally, the approach is shown to be flexible in that tailored algorithms can be evolved for specific scenarios and corner cases, allowing network operators to create unique algorithms for different deployments, and to postpone the need for costly hardware upgrades.

Multilayer Optimization of Heterogeneous Networks Using Grammatical Genetic Programming.

Heterogeneous cellular networks are composed of macro cells (MCs) and small cells (SCs) in which all cells occupy the same bandwidth. Provision has been made under the third generation partnership project-long term evolution framework for enhanced intercell interference coordination (eICIC) between cell tiers. Expanding on previous works, this paper instruments grammatical genetic programming to evolve control heuristics for heterogeneous networks. Three aspects of the eICIC framework are addressed including setting SC powers and selection biases, MC duty cycles, and scheduling of user equipments (UEs) at SCs. The evolved heuristics yield minimum downlink rates three times higher than a baseline method, and twice that of a state-of-the-art benchmark. Furthermore, a greater number of UEs receive transmissions under the proposed scheme than in either the baseline or benchmark cases.

Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function.

The HYDE scoring function consistently describes hydrogen bonding, the hydrophobic effect and desolvation. It relies on HYdration and DEsolvation terms which are calibrated using octanol/water partition coefficients of small molecules. We do not use affinity data for calibration, therefore HYDE is generally applicable to all protein targets. HYDE reflects the Gibbs free energy of binding while only considering the essential interactions of protein-ligand complexes. The greatest benefit of HYDE is that it yields a very intuitive atom-based score, which can be mapped onto the ligand and protein atoms. This allows the direct visualization of the score and consequently facilitates analysis of protein-ligand complexes during the lead optimization process. In this study, we validated our new scoring function by applying it in large-scale docking experiments. We could successfully predict the correct binding mode in 93% of complexes in redocking calculations on the Astex diverse set, while our performance in virtual screening experiments using the DUD dataset showed significant enrichment values with a mean AUC of 0.77 across all protein targets with little or no structural defects. As part of these studies, we also carried out a very detailed analysis of the data that revealed interesting pitfalls, which we highlight here and which should be addressed in future benchmark datasets.

Second-generation de novo design: a view from a medicinal chemist perspective.

For computational de novo design, a general retrospective validation work is a very challenging task. Here we propose a comprehensive workflow to de novo design driven by the needs of computational and medicinal chemists and, at the same time, we propose a general validation scheme for this technique. The study was conducted combining a suite of already published programs developed within the framework of the NovoBench project, which involved three different pharmaceutical companies and four groups of developers. Based on 188 PDB protein-ligand complexes with diverse functions, the study involved the ligand reconstruction by means of a fragment-based de-novo design approach. The structure-based de novo search engine FlexNovo showed in five out of eight total cases the ability to reconstruct native ligands and to rank them in four cases out of five within the first five candidates. The generated structures were ranked according to their synthetic accessibilities evaluated by the program SYLVIA. This investigation showed that the final candidate molecules have about the same synthetic complexity as the respective reference ligands. Furthermore, the plausibility of being true actives was assessed through literature searches.

Searching Fragment Spaces with feature trees.

Virtual combinatorial chemistry easily produces billions of compounds, for which conventional virtual screening cannot be performed even with the fastest methods available. An efficient solution for such a scenario is the generation of Fragment Spaces, which encode huge numbers of virtual compounds by their fragments/reagents and rules of how to combine them. Similarity-based searches can be performed in such spaces without ever fully enumerating all virtual products. Here we describe the generation of a huge Fragment Space encoding about 5 * 10(11) compounds based on established in-house synthesis protocols for combinatorial libraries, i.e., we encode practically evaluated combinatorial chemistry protocols in a machine readable form, rendering them accessible to in silico search methods. We show how such searches in this Fragment Space can be integrated as a first step in an overall workflow. It reduces the extremely huge number of virtual products by several orders of magnitude so that the resulting list of molecules becomes more manageable for further more elaborated and time-consuming analysis steps. Results of a case study are presented and discussed, which lead to some general conclusions for an efficient expansion of the chemical space to be screened in pharmaceutical companies.

Similarity searching and scaffold hopping in synthetically accessible combinatorial chemistry spaces.

Large collections of combinatorial libraries are an integral element in today's pharmaceutical industry. It is of great interest to perform similarity searches against all virtual compounds that are synthetically accessible by any such library. Here we describe the successful application of a new software tool CoLibri on 358 combinatorial libraries based on validated reaction protocols to create a single chemistry space containing over 10 (12) possible products. Similarity searching with FTrees-FS allows the systematic exploration of this space without the need to enumerate all product structures. The search result is a set of virtual hits which are synthetically accessible by one or more of the existing reaction protocols. Grouping these virtual hits by their synthetic protocols allows the rapid design and synthesis of multiple follow-up libraries. Such library ideas support hit-to-lead design efforts for tasks like follow-up from high-throughput screening hits or scaffold hopping from one hit to another attractive series.

Ultrafast de novo docking combining pharmacophores and combinatorics.

We report on a successful de novo design approach which relies on the combination of multi-million compound combinatorial docking under receptor-based pharmacophore constraints. Inspired by a rationale by A.R. Leach et al., we document on the unification of two steps into one for ligand assembly. In the original work, fragments known to bind in protein active sites were connected forming novel ligand compounds by means of generic skeleton linkers and following a combinatorial approach. In our approach, the knowledge of fragments binding to the protein has been expressed in terms of a receptor-based pharmacophore definition. The combinatorial linking step is performed in situ during docking, starting from combinatorial libraries. Three sample scenarios growing in size and complexity (combinatorial libraries of 1 million, 1.3 million, and 22.4 million compounds) have been created to illustrate the method. Docking could be accomplished between minutes and several hours depending on the outset; the results were throughout promising. Technically, a module compatibility between FlexX(C) and FlexX-Pharm has been established. The background is explained, and the crucial points from an information scientist's perspective are highlighted.

The FlexX database docking environment--rational extraction of receptor based pharmacophores.

We present an integrated docking environment that allows for iterative and interactive detailed analysis of many docking solutions. All docking information is stored in an ORACLE database. New scoring schemes (e.g. target-specific scoring functions) as well as various types of filters can be easily defined and tested within this environment. As an example application we investigated the validity of the following hypothesis: If a docking procedure can lead to enrichments significantly better than random then a bias towards (partially) correct placements should be detectable. Such bias in terms of a preference for certain interacting groups within the active site can be used to select a set of receptor-based pharmacophore constraints, which in turn might be used to enhance the docking procedure. As a proof of concept for this approach we performed docking studies on three targets: thrombin, the cyclin-dependent kinase 2 (CDK2) and the angiotensin converting enzyme (ACE). We docked a set of known active compounds with standard FlexX and derived three sets of target-specific receptor-based pharmacophore constraints by statistical analysis of the predicted placements. Applying these receptor-based constraints in a virtual screening protocol utilizing FlexX-Pharm led to significantly improved enrichments.