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.

Hybrid organogels and aerogels from co-assembly of structurally different low molecular weight gelators

The blending of perfluorinated bile ester derivatives with the gelator 2,3-didecyloxyanthracene (DDOA) yields a new class of hybrid organo- and aerogels displaying a combination of optical and mechanical properties that differ from those of pure gels. Indeed, the nanofibers constituting the hybrid organogels emit polarized blue light and display dichroic near-UV absorption via the achiral DDOA molecules, thanks to their association with a chiral bile ester. Moreover, the thermal stability and the mechanical yield stress of the mixed organogels in DMSO are enhanced for blends of DDOA with the deoxycholic gelator (DC11) having a C-11 chain, as compared to the pure components' gels. When the chain length of the ester is increased to C-13 (DC13) a novel compound for aerogel formation directly in scCO(2) is obtained under the studied conditions. A mixture of this compound with DDOA is also able to gelate scCO(2) leading to novel composite aerogel materials. As revealed by SAXS measurements, the hybrid and the pure DDOA and DC13 aerogels display cell parameters that are very similar. These SAXS experiments suggest that crystallographic conditions are very favorable for the growth of hybrid molecular arrangements in which DDOA and DC13 units could be interchanged. Specific molecular interactions between two components are not always a pre-requisite condition for the formation of a hybrid nanostructured material in which the components mutually induce properties.

Synthesis and application of weight function for edge cracked semicircular disk (ECSD)

We analyze the utility of edge cracked semicircular disk (ECSD) for rapid assessment of fracture toughness using compressive loading. Continuing our earlier work on ECSD, a theoretical examination here leads to a novel way for synthesizing weight functions using two distinct form factors. The efficacy of ECSD mode-I weight function synthesized using displacement and form factor methods is demonstrated by comparing with finite element results. Theory of elasticity in conjunction with finite element method is utilized to analyze crack opening potency of ECSD under eccentric compression to explore newer configurations of ECSD for fracture testing.

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.

Power-Controlled Reverse Channel Training in a Multiuser TDD-MIMO Spatial Multiplexing System With CSIR

This paper considers the design of a power-controlled reverse channel training (RCT) scheme for spatial multiplexing (SM)-based data transmission along the dominant modes of the channel in a time-division duplex (TDD) multiple-input and multiple-output (MIMO) system, when channel knowledge is available at the receiver. A channel-dependent power-controlled RCT scheme is proposed, using which the transmitter estimates the beamforming (BF) vectors required for the forward-link SM data transmission. Tight approximate expressions for 1) the mean square error (MSE) in the estimate of the BF vectors, and 2) a capacity lower bound (CLB) for an SM system, are derived and used to optimize the parameters of the training sequence. Moreover, an extension of the channel-dependent training scheme and the data rate analysis to a multiuser scenario with M user terminals is presented. For the single-mode BF system, a closed-form expression for an upper bound on the average sum data rate is derived, which is shown to scale as ((L-c - L-B,L- tau)/L-c) log logM asymptotically in M, where L-c and L-B,L- tau are the channel coherence time and training duration, respectively. The significant performance gain offered by the proposed training sequence over the conventional constant-power orthogonal RCT sequence is demonstrated using Monte Carlo simulations.

Combinatorial effect of rolling and carbonaceous nanoparticles on the evolution of crystallographic texture and structural properties of ultra high molecular weight polyethylene

Ultra high molecular weight polyethylene (PE) is a structural polymer widely used in biomedical implants. The mechanical properties of PE can be improved either by controlled crystalline orientation (texture) or by the addition of reinforcing agents. However, the combinatorial effect has not received much attention. The objective of this study was to characterize the structure and mechanical properties of PE composites incorporating multiwall carbon nanotubes (MWCNT) and reduced graphene oxide (RGO) subjected to hot rolling. The wide angle X-ray diffraction studies revealed that mechanical deformation resulted in a mixture of orthorhombic and monoclinic crystals. Furthermore, the presence of nanoparticles resulted in lower crystallinity in PE with smaller crystallite size, more so in RGO than in MWCNT composites. Rolling strengthened the texture of both orthorhombic and the monoclinic phases in PE. Presence of RGO weakened the texture of both phases of PE after rolling whereas MWCNT only mildly weakened the texture. This resulted in a reduction in the elastic modulus of RGO composites whereas moduli of neat polymer and the MWCNT composite increased after rolling. This study provides new insight into the role of nanoparticles in texture evolution during polymer processing with implications for processing of structural polymer composites.

Belief propagation for minimum weight many-to-one matchings in the random complete graph

In a complete bipartite graph with vertex sets of cardinalities n and n', assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as n -> infinity, with n' = n/alpha] for any fixed alpha > 1, the minimum weight of many-to-one matchings converges to a constant (depending on alpha). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.

THEORY OF NEWFORMS OF HALF-INTEGRAL WEIGHT

We set up the theory of newforms of half-integral weight on Gamma(0)(8N) and Gamma(0)(16N), where N is odd and squarefree. Further, we extend the definition of the Kohnen plus space in general for trivial character and also study the theory of newforms in the plus spaces on Gamma(0)(8N), Gamma(0)(16N), where N is odd and squarefree. Finally, we show that the Atkin-Lehner W-operator W-4 acts as the identity operator on S-2k(new)(4N), where N is odd and squarefree. This proves that S-2k(-)(4) = S-2k(4).

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Minuscule weight percent of graphene oxide and reduced graphene oxide modified Ag3PO4: new insight into improved photocatalytic activity

Designing and fabricating hybrid systems with a visible light active semiconductor as one of its components is an important research area for the development of highly efficient photocatalysts. Herein, we report visible-light driven photocatalytic activity of graphene oxide (GO) and controllably reduced GO (rGO) modified Ag3PO4 composites fabricated by an in situ method. Concentration of graphene derivatives in GO/rGO-Ag3PO4 composites was in the range of 0.13-0.52 wt% which is very minute compared to those reported previously. The optimal concentration of GO in Ag3PO4 with a kinetics (k = 1.23 +/- 0.04 min(-1)) for the degradation of rhodamine B is 0.26 wt%. GO-Ag3PO4 photocatalysts display an improved catalytic activity compared with pristine and rGOs modified Ag3PO4. In line with this, GO/rGO-Ag3PO4 composites show improved photocatalytic activity for the degradation of 2-chlorophenol compared with Degussa P-25. Our experiments with GO reduced to different extents show that, rGO with more polar functional groups exhibits a higher photocatalytic efficiency. The photocatalytic activity in the presence of different scavengers reveals that holes and O-2(-center dot) reactive species play major roles in the degradation phenomenon. In view of our experimental results and reported theoretical studies, a change in conduction band energy level and variation in the contribution of different charge orbitals (C 2p and O 2p) to the conduction band in the composite favours electron flow from graphene derivatives to the semiconductor, enhancing its photocatalytic response.

Unsupervised training for mandarin broadcast news and conversation transcription

A significant cost in obtaining acoustic training data is the generation of accurate transcriptions. For some sources close-caption data is available. This allows the use of lightly-supervised training techniques. However, for some sources and languages close-caption is not available. In these cases unsupervised training techniques must be used. This paper examines the use of unsupervised techniques for discriminative training. In unsupervised training automatic transcriptions from a recognition system are used for training. As these transcriptions may be errorful data selection may be useful. Two forms of selection are described, one to remove non-target language shows, the other to remove segments with low confidence. Experiments were carried out on a Mandarin transcriptions task. Two types of test data were considered, Broadcast News (BN) and Broadcast Conversations (BC). Results show that the gains from unsupervised discriminative training are highly dependent on the accuracy of the automatic transcriptions. © 2007 IEEE.

Comparison between weight loss of bends in a pneumatic conveyor and erosion rate obtained in a centrifugal erosion tester for the same materials

In order to find a link between results obtained from a laboratory erosion tester and tests carried out on a pneumatic conveyor, a comparison has been made between weight loss from bends on an industrial-scale pneumatic conveyor and erosion rates obtained in a small centrifugal erosion tester, for the same materials. Identical test conditions have been applied to both experiments so that comparable test results have been obtained. The erosion rate of mild steel commonly used as the wall material of conveyor pipes and pipe bends was determined individually on both test rigs. A relationship between weight loss from the bends and erosion rate determined from the tester has been developed. A discussion based on the results and their applicability to the prediction of wear in pneumatic conveyors concludes the paper. © 2004 Elsevier B.V. All rights reserved.

The Stability of a Vertical Single-Walled Carbon Nanotube Under Its Own Weight

It has been reported recently that single carbon nanotubes were attached to AFM tips to act as nanotweezers. In order to investigate its stability, a vertical single-walled carbon nanotube (SWCNT) under its own weight is studied in this paper. The lower end of the carbon nanotube is clamped. Firstly the governing dimensionless numbers are derived by dimensional analysis. Then the theoretical analysis based on an elastic column model is carried out. Two ratios, I.e., the ratio of half wall thickness to radius (t=R) and the ratio of gravity to elastic resilience ($\rho$gR=E), and their influences on the ratio of critical length to radius are discussed. It is found that the relationship between the critical ratio of altitude to radius and ratio of half thickness to radius is approximately linear. As the dimensionless number $\rho$gR=E increases, the compressive force per unit length (weight) becomes larger, thus critical ratio of altitude to radius must become smaller to maintain stability. At last the critical length of SWCNT is calculated. The results of this paper will be helpful for the stability design of nanotweezers-like nanostructures.