Near-infrared light-responsive graphene oxide composite multilayer capsules: a novel route for remote controlled drug delivery

A novel and simple route for near-infrared (NIR)-light controlled release of drugs has been demonstrated using graphene oxide (GO) composite microcapsules based on the unique optical properties of GO. Upon NIR-laser irradiation, the microcapsules were ruptured in a point-wise fashion due to local heating which in turn triggers the light-controlled release of the encapsulated anticancer drug doxorubicin (Dox) from these capsules.

Energy-efficient training for antenna selection in time-varying channels

Training for receive antenna selection (AS) differs from that for conventional multiple antenna systems because of the limited hardware usage inherent in AS. We analyze and optimize the performance of a novel energy-efficient training method tailored for receive AS. In it, the transmitter sends not only pilots that enable the selection process, but also an extra pilot that leads to accurate channel estimates for the selected antenna that actually receives data. For time-varying channels, we propose a novel antenna selection rule and prove that it minimizes the symbol error probability (SEP). We also derive closed-form expressions for the SEP of MPSK, and show that the considered training method is significantly more energy-efficient than the conventional AS training method.

Multi-port network modeling for fractal shape microstrip antenna

In this paper we demonstrate the use of multi-port network modeling to analyze one such antenna with fractal shaped parts. Based on simulation and experimental studies, it has been demonstrated that model can accurately predict the input characteristics of antennas with Minkowski geometry replacing a side micro strip square ring.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.

Antenna selection in spatial modulation systems

Novel transmit antenna selection techniques are conceived for Spatial Modulation (SM) systems and their symbol error rate (SER) performance is investigated. Specifically, low-complexity Euclidean Distance optimized Antenna Selection (EDAS) and Capacity Optimized Antenna Selection (COAS) are studied. It is observed that the COAS scheme gives a better SER performance than the EDAS scheme. We show that the proposed antenna selection based SM systems are capable of attaining a significant gain in signal-to-noise ratio (SNR) compared to conventional SM systems, and also outperform the conventional MIMO systems employing antenna selection at both low and medium SNRs.

Channel training signal design for reciprocal multiple antenna systems with beamforming

Fast and efficient channel estimation is key to achieving high data rate performance in mobile and vehicular communication systems, where the channel is fast time-varying. To this end, this work proposes and optimizes channel-dependent training schemes for reciprocal Multiple-Input Multiple-Output (MIMO) channels with beamforming (BF) at the transmitter and receiver. First, assuming that Channel State Information (CSI) is available at the receiver, a channel-dependent Reverse Channel Training (RCT) signal is proposed that enables efficient estimation of the BF vector at the transmitter with a minimum training duration of only one symbol. In contrast, conventional orthogonal training requires a minimum training duration equal to the number of receive antennas. A tight approximation to the capacity lower bound on the system is derived, which is used as a performance metric to optimize the parameters of the RCT. Next, assuming that CSI is available at the transmitter, a channel-dependent forward-link training signal is proposed and its power and duration are optimized with respect to an approximate capacity lower bound. Monte Carlo simulations illustrate the significant performance improvement offered by the proposed channel-dependent training schemes over the existing channel-agnostic orthogonal training schemes.

Composite cyclodextrin-calcium carbonate porous microparticles and modified multilayer capsules: novel carriers for encapsulation of hydrophobic drugs

Novel composite cyclodextrin (CD)-CaCO3 spherical porous microparticles have been synthesized through Ca2+-CD complex formation, which influences the crystal growth of CaCO3. The CDs are entrapped and distributed uniformly in the matrix of CaCO3 microparticles during crystallization. The hydrophobic fluorescent molecules coumarin and Nile red (NR) are efficiently encapsulated into these composite CD-CaCO3 porous particles through supramolecular inclusion complexation between entrapped CDs and hydrophobic molecules. Thermogravimetric (TGA) and infrared spectroscopy (IR) analysis of composite CD-CaCO3 particles reveals the presence of large CDs and their strong interaction with calcium carbonate nanoparticles. The resulting composite CD-CaCO3 microparticles are utilized as sacrificial templates for preparation of CD-modified layer-by-layer (LbL) capsules. After dissolution of the carbonate core, CDs are retained in the interior of the capsules in a network fashion and assist in the encapsulation of hydrophobic molecules. The efficient encapsulation of the hydrophobic fluorescent dye, coumarin, was successfully demonstrated using CD-modified capsules. In vitro release of the encapsulated coumarin from the CD-CaCO3 and CD-modified capsules has been demonstrated.

Evolution of microstructure and texture during deformation and recrystallization of heavily rolled Cu-Cu multilayer

A Cu-Cu multilayer processed by accumulative roll bonding was deformed to large strains and further annealed. The texture of the deformed Cu-Cu multilayer differs from the conventional fcc rolling textures in terms of higher fractions of Bs and RD-rotated cube components, compared with the volume fraction of Cu component. The elongated grain shape significantly affects the deformation characteristics. Characteristic microstructural features of both continuous dynamic recrystallization and discontinuous dynamic recrystallization were observed in the microtexture measurements. X-ray texture measurements of annealing of heavily deformed multilayer demonstrate constrained recrystallization and resulted in a bimodal grain size distribution in the annealed material at higher strains. The presence of cube- and BR-oriented grains in the deformed material confirms the oriented nucleation as the major influence on texture change during recrystallization. Persistence of cube component throughout the deformation is attributed to dynamic recrystallization. Evolution of RD-rotated cube is attributed to the deformation of cube components that evolve from dynamic recrystallization. The relaxation of strain components leads to Bs at larger strains. Further, the Bs component is found to recover rather than recrystallize during deformation. The presence of predominantly Cu and Bs orientations surrounding the interface layer suggests constrained annealing behavior.

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N+1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N+1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.

Joint Antenna Selection and Frequency-Domain Scheduling in OFDMA Systems with Imperfect Estimates from Dual Pilot Training Scheme

Transmit antenna selection (AS) has been adopted in contemporary wideband wireless standards such as Long Term Evolution (LTE). We analyze a comprehensive new model for AS that captures several key features about its operation in wideband orthogonal frequency division multiple access (OFDMA) systems. These include the use of channel-aware frequency-domain scheduling (FDS) in conjunction with AS, the hardware constraint that a user must transmit using the same antenna over all its assigned subcarriers, and the scheduling constraint that the subcarriers assigned to a user must be contiguous. The model also captures the novel dual pilot training scheme that is used in LTE, in which a coarse system bandwidth-wide sounding reference signal is used to acquire relatively noisy channel state information (CSI) for AS and FDS, and a dense narrow-band demodulation reference signal is used to acquire accurate CSI for data demodulation. We analyze the symbol error probability when AS is done in conjunction with the channel-unaware, but fair, round-robin scheduling and with channel-aware greedy FDS. Our results quantify how effective joint AS-FDS is in dispersive environments, the interactions between the above features, and the ability of the user to lower SRS power with minimal performance degradation.

A Markov Decision Theoretic Approach to Pilot Allocation and Receive Antenna Selection

This paper considers antenna selection (AS) at a receiver equipped with multiple antenna elements but only a single radio frequency chain for packet reception. As information about the channel state is acquired using training symbols (pilots), the receiver makes its AS decisions based on noisy channel estimates. Additional information that can be exploited for AS includes the time-correlation of the wireless channel and the results of the link-layer error checks upon receiving the data packets. In this scenario, the task of the receiver is to sequentially select (a) the pilot symbol allocation, i.e., how to distribute the available pilot symbols among the antenna elements, for channel estimation on each of the receive antennas; and (b) the antenna to be used for data packet reception. The goal is to maximize the expected throughput, based on the past history of allocation and selection decisions, and the corresponding noisy channel estimates and error check results. Since the channel state is only partially observed through the noisy pilots and the error checks, the joint problem of pilot allocation and AS is modeled as a partially observed Markov decision process (POMDP). The solution to the POMDP yields the policy that maximizes the long-term expected throughput. Using the Finite State Markov Chain (FSMC) model for the wireless channel, the performance of the POMDP solution is compared with that of other existing schemes, and it is illustrated through numerical evaluation that the POMDP solution significantly outperforms them.

SEP-optimal antenna selection for average interference constrained underlay cognitive radios

In the underlay mode of cognitive radio, secondary users can transmit when the primary is transmitting, but under tight interference constraints, which limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which require less hardware and yet exploit spatial diversity, help improve the secondary system performance. In this paper, we develop the optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gains of the channels from secondary transmit antenna to primary receiver and secondary transmit antenna to secondary receive antenna. The optimal rule is different from the several ad hoc rules that have been proposed in the literature. We also propose a closed-form, tractable variant of the optimal rule and analyze its SEP. Several results are presented to compare the performance of the closed-form rule with the ad hoc rules, and interesting inter-relationships among them are brought out.

Multi-port network modeling of stub loaded Microstrip ring antenna for dual-band operations

A square ring microstrip antenna can be modified for dual-band operations by appropriately attaching an open ended stub. The input impedance of this antenna is analyzed here using multi-port network modeling (MNM) approach. The coupled feed is included by defining additional terms in the model. A prototype antenna is fabricated and tested to validate these computations.

Polyelectrolyte/silver nanocomposite multilayer films as multifunctional thin film platforms for remote activated protein and drug delivery

We demonstrate a nanoparticle loading protocol to develop a transparent, multifunctional polyelectrolyte multilayer film for externally activated drug and protein delivery. The composite film was designed by alternate adsorption of poly(allylamine hydrochloride) (PAH) and dextran sulfate (DS) on a glass substrate followed by nanoparticle synthesis through a polyol reduction method. The films showed a uniform distribution of spherical silver nanoparticles with an average diameter of 50 +/- 20 nm, which increased to 80 +/- 20 nm when the AgNO3 concentration was increased from 25 to 50 mM. The porous and supramolecular structure of the polyelectrolyte multilayer film was used to immobilize ciprofloxacin hydrochloride (CH) and bovine serum albumin (BSA) within the polymeric network of the film. When exposed to external triggers such as ultrasonication and laser light the loaded films were ruptured and released the loaded BSA and CH. The release of CH is faster than that of BSA due to a higher diffusion rate. Circular dichroism measurements confirmed that there was no significant change in the conformation of released BSA in comparison with native BSA. The fabricated films showed significant antibacterial activity against the bacterial pathogen Staphylococcus aureus. Applications envisioned for such drug-loaded films include drug and vaccine delivery through the transdermal route, antimicrobial or anti-inflammatory coatings on implants and drug-releasing coatings for stents. (C) 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Optimal Joint Antenna Selection and Power Adaptation in Underlay Cognitive Radios

Transmit antenna selection (AS) is a popular, low hardware complexity technique that improves the performance of an underlay cognitive radio system, in which a secondary transmitter can transmit when the primary is on but under tight constraints on the interference it causes to the primary. The underlay interference constraint fundamentally changes the criterion used to select the antenna because the channel gains to the secondary and primary receivers must be both taken into account. We develop a novel and optimal joint AS and transmit power adaptation policy that minimizes a Chernoff upper bound on the symbol error probability (SEP) at the secondary receiver subject to an average transmit power constraint and an average primary interference constraint. Explicit expressions for the optimal antenna and power are provided in terms of the channel gains to the primary and secondary receivers. The SEP of the optimal policy is at least an order of magnitude lower than that achieved by several ad hoc selection rules proposed in the literature and even the optimal antenna selection rule for the case where the transmit power is either zero or a fixed value.