Existing metaheuristic algorithms often struggle to balance diversity, convergence, and stability when solving complex, high-dimensional multiobjective optimization problems due to their sensitivity to parameter settings. To address this issue, we propose CMOPSO/DR, an adaptive co-competitive multiobjective PSO algorithm incorporating dimensionality reduction. First, the denoising adversarial autoencoder (DAAE) network is automatically determined to construct a compressed coordinate system (CCS) to accelerate convergence. Second, simulated binary crossover (SBX) is used to enhance both the diversity and stability of the algorithm. Finally, the co-competitive strategy of coupling CCS and SBX is developed to respond to various optimization demands at different optimization stages adaptively. The experimental results show that CMOPSO/DR performs better than other advanced optimization algorithms on various benchmark and real-world problems, and it achieves efficient acquisition of high-quality optimal solutions, demonstrating its obvious improvements in theory and application.

Yield estimation and optimization is ubiquitous in modern circuit design but remains elusive for large-scale chips. This is largely due to the mounting cost of transistor-level simulation and one's often limited resources. In this study, we propose a novel framework to estimate and optimize yield using Bayesian Neural Network (BNN-YEO). By coupling machine learning method with Bayesian network, our approach can effectively integrate prior knowledge and is unaffected by the overfitting problem prevalent in most surrogate models. With the introduction of a smooth approximation of the indicator function, it incorporates gradient information to facilitate global yield optimization. We examine its effectiveness via numerical experiments on 6T SRAM and found that BNN-YEO provides 100x speedup (in terms of SPICE simulations) over standard Monte Carlo in yield estimation, and 20x faster than the state-of-the-art method for total yield estimation and optimization with improved accuracy.

In this work, a LOcation based RAN resource Management and Access (LOMA) map is designed for future radio access networks (RAN) to allocate radio resources in complex wireless environment, and to facilitate uplink/downlink data transmissions. Enabled by the AI and high-precise positioning techniques, the LOMA map can associate a set of radio resources and data transmission parameters (e.g, transmit power, MCS level) with a geographical location in the RAN area. Given the LOMA map, each user equipment (UE) or infrastructure associated with the RAN can directly determine the radio resources and parameters used for uplink/downlink data transmissions according to its location. An AI enabled LOMA map generation method are proposed to generate LOMA maps according to the statistical traffic and wireless environment data collected by UEs and infrastructures. A reinforcement learning (RL) based algorithm is further proposed in the LOMA map generation method to dynamically quantify the available radio resources according to the real-time data traffic and the performance of applied resource scheduling scheme. Case studies with numerical results are presented to show the benefits provided by LOMA map technique in terms of increasing resource sharing efficiency, reducing signal overheads in data transmissions, and enabling resource scheduling schemes with less computing cost.

The underlying waveform has always been a shaping factor for each generation of the cellular networks, such as orthogonal frequency division multiplexing (OFDM) for the 4th generation cellular networks (4G). To meet the diversified and pronounced expectations upon the upcoming 5G cellular networks, here we present an enabler for flexible waveform configuration, named as filtered-OFDM (f-OFDM). With the conventional OFDM, a unified numerology is applied across the bandwidth provided, balancing among the channel characteristics and the service requirements, and the spectrum efficiency is limited by the compromise we made. In contrast, with f-OFDM, the assigned bandwidth is split up into several subbands, and different types of services are accommodated in different subbands with the most suitable waveform and numerology, leading to an improved spectrum utilization. After outlining the general framework of f-OFDM, several important design aspects are also discussed, including filter design and guard tone arrangement. In addition, an extensive comparison among the existing 5G waveform candidates is also included to illustrate the advantages of f-OFDM. Our simulations indicate that, in a specific scenario with four distinct types of services, f-OFDM provides up to 46% of throughput gains over the conventional OFDM scheme.

An adjustable pulse bandwidth single carrier waveform for asynchronous low-cost low-power 5G M2M applications is proposed. The solution uses ultra narrow-band pulse to improve coverage, which is a much more efficient coverage enhancement solution than existing repetition solutions. Frequency localized pulse shaping is used, which allows asynchronous transmission and packing more machine-type devices (MTDs) for the same spectrum resources. In addition, bandwidth of each MTD is configurable based on long term channel quality and system load, which supports higher throughput and lower power consumption. Performance comparison with the repetition solution of 3GPP LTE demonstrates significant gain in terms of number of supported connections.

The weighted circularly convolved OFDM/OQAM (WCC-OFDM/OQAM), a variant of OFDM/OQAM without time-domain tail overhead, is investigated in a doubly dispersive fading environment. A new receiver is proposed that resolves the self-interference present at a regular WCC-OFDM/OQAM receiver when the channel variations are too fast compared to the signal burst duration. This is achieved by exploiting the channel state information (CSI) available at the receiver to compensate for the channel discontinuity that appears in the receiver's circular operations. The proposed receiver is universal in two regards: first, it performs equally well for a wide range of speeds and modulation and coding schemes (MCSs), and second, it does not require any change to the WCC-OFDM/OQAM signal structure, and thus, is transparent to the transmitter.

A K-user downlink transmission is considered, wherein the Nyquist sequences of different users are transmitted with different time offsets so that the entire transmitted signal is deemed a K times faster than Nyquist (FTN) signal. An inter-user interference removal technique is proposed that successively removes the interference using successive trellis update. It is shown by simulations that when the power difference between users is large enough, using only one round of trellis decoding, the system approaches the performance of the successive trellis update.

This work presents the channel estimation for Generalized Frequency Division Multiplexing (GFDM). GFDM can be considered as a filtered bank multicarrier scheme, where a spectrally-contained pulse shaping is applied over each subcarrier to reduce out of band radiation (OOB). However, due to pulse shaping, subcarriers in GFDM are no longer orthogonal and there is inherent interference. Due to such interference, the channel estimation for GFDM is not trivial. In this work, two channel estimation methods for GFDM are proposed, 1) Pilot Interference Cancellation (Pilot-IC) where interference is pre-canceled only at pilot symbols, 2) Transmitter IC (Tx-IC) where interference is pre-cancelled at both data and pilot symbols. With scattered pilots over frequency and time grid, this allows frequency selective and time varying fading channels to be estimated, with reduced overhead. The simulation results show that these two methods can provide the same MSE performance. Moreover, the Pilot-IC pairing with a Zero Forcing (ZF) receiver, and the Tx-IC pairing with a simple Matched Filter (MF) receiver, also provide the same BER performance. Hence, it is possible to cancel the interference either at the transmitter or the receiver.

A novel technique for removing the edge time transitions, a.k.a. tails, as well as the half symbol offset overhead of OFDM/OQAM signal is proposed. The proposed technique, which is called weighted circular convolution, totally removes the signal overheads, while preserving the real-orthogonality of the prototype filter, and as such, does not incur any ISI/ICI on the demodulated OQAM symbols. It is based on extension of the finite-length OQAM sequence to infinite-length such that the resulting signal is periodic. This periodicity together with special structure of OFDM/OQAM enables one to transmit only the desired overhead-removed portion of signal. This is equivalent to a weighted circular convolution instead of linear convolution in the OFDM/OQAM modulator/demodulator. The spectral sidelobe augmentation due to the sharp edge transitions of the overhead-removed signal is resolved by a weighted time-domain windowing. The proposed overhead-removal technique is applicable to an OFDM/OQAM burst of arbitrary length (either even or odd) and, among other benefits, significantly improves the spectral efficiency especially for short-burst signals.

BACKGROUND: Linking high-throughput experimental data with biological networks is a key step for understanding complex biological systems. Currently, visualization tools for large metabolic networks often result in a dense web of connections that is difficult to interpret biologically. The MetNetGE application organizes and visualizes biological networks in a meaningful way to improve performance and biological interpretability. RESULTS: MetNetGE is an interactive visualization tool based on the Google Earth platform. MetNetGE features novel visualization techniques for pathway and ontology information display. Instead of simply showing hundreds of pathways in a complex graph, MetNetGE gives an overview of the network using the hierarchical pathway ontology using a novel layout, called the Enhanced Radial Space-Filling (ERSF) approach that allows the network to be summarized compactly. The non-tree edges in the pathway or gene ontology, which represent pathways or genes that belong to multiple categories, are linked using orbital connections in a third dimension. Biologists can easily identify highly activated pathways or gene ontology categories by mapping of summary experiment statistics such as coefficient of variation and overrepresentation values onto the visualization. After identifying such pathways, biologists can focus on the corresponding region to explore detailed pathway structure and experimental data in an aligned 3D tiered layout. In this paper, the use of MetNetGE is illustrated with pathway diagrams and data from E. coli and Arabidopsis. CONCLUSIONS: MetNetGE is a visualization tool that organizes biological networks according to a hierarchical ontology structure. The ERSF technique assigns attributes in 3D space, such as color, height, and transparency, to any ontological structure. For hierarchical data, the novel ERSF layout enables the user to identify pathways or categories that are differentially regulated in particular experiments. MetNetGE also displays complex biological pathway in an aligned 3D tiered layout for exploration.

Collaborative Filtering (CF) is widely used in web recommender systems, while most existing CF applications focus on transactions or page views within a single site. In this paper, we build a recommender system prototype, which suggests web sites to users, by collecting browsing events at routers without neither user nor website effort. 100 million HTTP flows, involving 11, 327 websites, are converted to user-site ratings using access frequency as the implicit rating metric. With this rating dataset, we evaluate six CF algorithms including one proposed algorithm based on IP address locality. Our experiments show that the recommendation from K nearest neighbors (Runn) performs the best by 50% p@10 (precision of top 10) and 53% p@5 (precision of top 5). Although the precision is far from ideal, our preliminary results suggest the potential value of such a centralized web site recommender system.

Code-division multiple-access (CDMA) is a serious candidate for personal communication systems at 1.9 GHz in North America. We consider the issue of bandwidth management in a CDMA integrated wireless-access network with heterogeneous services. A framework for adaptive connection admission in the up-link direction is proposed. It is based on estimation of the interference at the base station receivers. The estimation algorithm employs a linear Kalman filter which is driven by a measurement of the interference and by predicted traffic parameters of the admitted connections. We derived several generic variants of the control architecture for the up-link direction to assess the main characteristics of the framework and to determine the trade-offs between complexity and performance. They vary from a fixed strategy with fixed power control to an adaptive strategy with full information about network state and adaptive power control. A numerical study of the proposed framework shows that the estimated value of the average interference adapts well to the real value under nonstationary and nonuniform environment. This feature results in high network utilization for arbitrary traffic conditions.

Error-trapping decoding techniques are attractive due to their simple structure. Since 1962 several improved error-trapping methods have been devised in an effort to extend the capability and effectiveness in decoding multiple-error-correcting cyclic codes. Prange (1962) and MacWilliams (1964) introduced a (T, U) permutation group applied to this error-trapping decoding strategy by making use of a set of code-preserving permutation to obtain k error-free positions from which the rest of the code word could be reconstructed. Recently, exact lower bounds on the code length n for (n, k, 2t+1) cyclic codes have been found by using 5-step and 3-step (T, U) permutation groups. The present paper presents a study on the relationship between the code parameters n, k, t and the number of permutation steps s, with t being odd. Some examples on the capability of (T, U) permutation decodable (PD) cyclic codes are illustrated.>

The exact lower bounds on codelength n for three-step (T, U) permutation decodable binary cyclic codes of even-valued error number t (t>or=4) are presented. Since the derivation of these results involves only the error position, the results are applicable to cyclic codes over GF(2/sup m/).>