Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access

In this paper, we provide joint subcarrier assignment and power allocation schemes for quality-of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum-efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, we propose a dual-layer resource allocation approach and provide a complete solution using difference-of-two-concave-functions approximation, successive convex approximation, and gradient-search methods. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated in this case such that the macro-cell optimal RE and corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings

Wide-field extended-resolution fluorescence microscopy with standing surface-plasmon-resonance waves

The resolution of conventional SPR imaging has been limited by the diffraction nature of light. A wide-field extended-resolution optical imaging technique, standing-wave surface plasmon resonance fluorescence (SW-SPRF) microscopy, has been developed. Based on evanescent SPR standing waves, SW-SPRF provides lateral resolution approaching 100 nm and offers the advantages of significant signal enhancement and background noise reduction. SW-SPRF has the potential for sensitive biomolecular detection, nanoscale imaging, and lithographic applications

Energy Efficiency Optimization for PSOAM Mode-Groups based MIMO-NOMA Systems

Plane spiral orbital angular momentum (PSOAM) mode-groups (MGs) and multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) serve as two emerging techniques for achieving high spectral efficiency (SE) in the next-generation networks. In this paper, a PSOAM MGs based multi-user MIMO-NOMA system is studied, where the base station transmits data to users by utilizing the generated PSOAM beams. For such scenario, the interference between users in different PSOAM mode groups can be avoided, which leads to a significant performance enhancement. We aim to maximize the energy efficiency (EE) of the system subject to the constraints of the total transmission power and the minimum data rate. This designed optimization problem is non-convex owing to the interference among users, and hence is quite difficult to tackle directly. To solve this issue, we develop a dual layer resource allocation algorithm where the bisection method is exploited in the outer layer to obtain the optimal EE and a resource distributed iterative algorithm is exploited in the inner layer to optimize the transmit power. Besides, an alternative resource allocation algorithm with Deep Belief Networks (DBN) is proposed to cope with the requirement for low computational complexity. Simulation results verify the theoretical findings and demonstrate the proposed algorithms on the PSOAM MGs based MIMO-NOMA system can obtain a better performance comparing to the conventional MIMO-NOMA system in terms of EE

Design, Modeling, and Performance Analysis of Multi-Antenna Heterogeneous Cellular Networks

This paper presents a stochastic geometry-based framework for the design and analysis of downlink multi-user multiple-input multiple-output (MIMO) heterogeneous cellular networks with linear zero-forcing transmit precoding and receive combining, assuming Rayleigh fading channels and perfect channel state information. The generalized tiers of base stations may differ in terms of their Poisson point process spatial density, number of transmit antennas, transmit power, artificial-biasing weight, and number of user equipments served per resource block. The spectral efficiency of a typical user equipped with multiple receive antennas is characterized using a non-direct moment-generating-function-based methodology with closed-form expressions of the useful received signal and aggregate network interference statistics systematically derived. In addition, the area spectral efficiency is formulated under different space-division multiple-access and single-user beamforming transmission schemes. We examine the impact of different cellular network deployments, propagation conditions, antenna configurations, and MIMO setups on the achievable performance through theoretical and simulation studies. Based on the state-of-the-art system parameters, the results highlight the inherent limitations of baseline single-input single-output transmission and conventional sparse macro-cell deployment, as well as the promising potential of multi-antenna communications and small-cell solution in interference-limited cellular environments

Energy Efficient Resource Allocation for UCA-Based OAM-MIMO System

The combination of orbital angular momentum (OAM) and multi-input multi-output (MIMO) is identified as an effective solution to improve energy efficiency (EE) in the next-generation wireless communication. According to the orthogonality of OAM, we adopt uniform circular array (UCA) to establish the transmitter and receiver of the OAM-MIMO system in this paper. Our goal is to maximize the EE of the system whilst satisfying the maximum total transmit power and the minimum capacity requirement of each mode. Due to the inter-interference of different UCA at the same mode, the optimization problem involving the power allocation of modes is non-convex, thus is difficult to solve directly. To tackle this problem, the optimization problem is transformed into two sub-problems by using the fractional programming. Then we develop a dual-layer iteration algorithm where the nonconvex power allocation problem is transformed into a convex problem by exploiting the the first-order Taylor approximation in the inner layer, and the dichotomy is used to update EE in the outer layer. Simulation results confirm the effectiveness of the proposed solution, and demonstrate the superiority of the OAM-MIMO system over the conventional MIMO system from the perspective of EE

Genetic study of congenital bile-duct dilatation identifies de novo and inherited variants in functionally related genes

Background: Congenital dilatation of the bile-duct (CDD) is a rare, mostly sporadic, disorder that results in bile retention with severe associated complications. CDD affects mainly Asians. To our knowledge, no genetic study has ever been conducted. Methods: We aim to identify genetic risk factors by a “trio-based” exome-sequencing approach, whereby 31 CDD probands and their unaffected parents were exome-sequenced. Seven-hundred controls from the local population were used to detect gene-sets significantly enriched with rare variants in CDD patients. Results: Twenty-one predicted damaging de novo variants (DNVs; 4 protein truncating and 17 missense) were identified in several evolutionarily constrained genes (p < 0.01). Six genes carrying DNVs were associated with human developmental disorders involving epithelial, connective or bone morphologies (PXDN, RTEL1, ANKRD11, MAP2K1, CYLD, ACAN) and four linked with cholangio- and hepatocellular carcinomas (PIK3CA, TLN1 CYLD, MAP2K1). Importantly, CDD patients have an excess of DNVs in cancer-related genes (p < 0.025). Thirteen genes were recurrently mutated at different sites, forming compound heterozygotes or functionally related complexes within patients. Conclusions: Our data supports a strong genetic basis for CDD and show that CDD is not only genetically heterogeneous but also non-monogenic, requiring mutations in more than one genes for the disease to develop. The data is consistent with the rarity and sporadic presentation of CDD