Large-Scale Multiuser SM-MIMO Versus Massive MIMO

Spatial modulation (SM) is attractive for multiantenna wireless communications. SM uses multiple transmit antenna elements but only one transmit radio frequency (RF) chain. In SM, in addition to the information bits conveyed through conventional modulation symbols (e.g., QAM), the index of the active transmit antenna also conveys information bits. In this paper, we establish that SM has significant signal-to-noise (SNR) advantage over conventional modulation in large-scale multiuser (multiple-input multiple-output) MIMO systems. Our new contribution in this paper addresses the key issue of large-dimension signal processing at the base station (BS) receiver (e.g., signal detection) in large-scale multiuser SM-MIMO systems, where each user is equipped with multiple transmit antennas (e.g., 2 or 4 antennas) but only one transmit RF chain, and the BS is equipped with tens to hundreds of (e.g., 128) receive antennas. Specifically, we propose two novel algorithms for detection of large-scale SM-MIMO signals at the BS; one is based on message passing and the other is based on local search. The proposed algorithms achieve very good performance and scale well. For the same spectral efficiency, multiuser SM-MIMO outperforms conventional multiuser MIMO (recently being referred to as massive MIMO) by several dBs. The SNR advantage of SM-MIMO over massive MIMO can be attributed to: (i) because of the spatial index bits, SM-MIMO can use a lower-order QAM alphabet compared to that in massive MIMO to achieve the same spectral efficiency, and (ii) for the same spectral efficiency and QAM size, massive MIMO will need more spatial streams per user which leads to increased spatial interference.

LDPC Code Designs Based on root I Matrices

LDPC codes can be constructed by tiling permutation matrices that belong to the square root of identity type and similar algebraic structures. We investigate into the properties of such codes. We also present code structures that are amenable for efficient encoding.

Low Complexity Power and Scheduling Policies for Wireless Networks to Provide Quality of Service

We consider optimal power allocation policies for a single server, multiuser system. The power is consumed in transmission of data only. The transmission channel may experience multipath fading. We obtain very efficient, low computational complexity algorithms which minimize power and ensure stability of the data queues. We also obtain policies when the users may have mean delay constraints. If the power required is a linear function of rate then we exploit linearity and obtain linear programs with low complexity.

Strongly minimal triangulations of (S (3) x S (1))(#3) and (S (3) x S (1))(#3)

A triangulated d-manifold K, satisfies the inequality for da parts per thousand yen3. The triangulated d-manifolds that meet the bound with equality are called tight neighbourly. In this paper, we present tight neighbourly triangulations of 4-manifolds on 15 vertices with as an automorphism group. One such example was constructed by Bagchi and Datta (Discrete Math. 311 (citeyearbd102011) 986-995). We show that there are exactly 12 such triangulations up to isomorphism, 10 of which are orientable.

Mixed Mode Analysis of Obliquely Oriented Edge Cracked Semicircular Disk Under Compression

A new mixed-mode compression fracture specimen, obliquely oriented edge cracked semicircular disk (OECSD) is analyzed by extending pure opening mode configuration of edge cracked semicircular disk (ECSD) under Hertzian compression. Photoelastic experiments are conducted on two different specimens of OECSD of same size and different crack lengths and inclinations. Finite element method (FEM) is used to solve a number of cases of the problem varying crack length and crack inclination. FE results show a good match with experiments. Inclination of edge crack in OECSD can be so made as to obtain any mode-mixity ratio between zero and one and beyond for any crack length. The new specimen can be used for fracture testing under compression more conveniently than the existing ones in several ways.

Extremely High Near Field Enhancement in a Novel Plasmonic Nano Material used for Photovoltage Generation

Enhancement of localized electric field near metal (plasmonic) nanostructures can have various interesting applications in sensing, imaging, photovoltage generation etc., for which significant efforts are aimed towards developing plasmonic systems with well designed and large electromagnetic response. In this paper, we discuss the wafer scale fabrication and optical characterization of a unique three dimensional plasmonic material. The near field enhancement in the visible range of the electromagnetic spectrum obtained in these structures (order of 106), is close to the fundamental limit that can be obtained in this and similar EM field enhancement schemes. The large near field enhancement has been reflected in a huge Raman signal of graphene layer in close proximity to the plasmonic system, which has been validated with FEM simulations. We have integrated graphene photodetectors with this material to obtain record photovoltage generation, with responsivity as high as A/W. As far as we know, this is the highest sensitivity obtained in any plasmonic-graphene hybrid photodetection system till date.

Photonic monitoring of chitosan nanostructured alginate microcapsules for drug release

By using a novel microfluidic set-up for drug screening applications, this study examines delivery of a novel risedronate based drug formulation for treatment of osteoporosis that was developed to overcome the usual shortcomings of risedronate, such as its low bioavailability and adverse gastric effects. Risedronate nanoparticles were prepared using muco-adhesive polymers such as chitosan as matrix for improving the intestinal cellular absorption of risedronate and also using a gastric-resistant polymer such as sodium alginate for reducing the gastric inflammation of risedronate. The in-vitro characteristics of the alginate encapsulated chitosan nanoparticles are investigated, including their stability, muco-adhesiveness, and Caco-2 cell permeability. Fluorescent markers are tagged with the polymers and their morphology within the microcapsules is imaged at various stages of drug release.

A new approach to depict bone surfaces in finger imaging using photoacoustic tomography

Imaging the vasculature close around the finger joints is of interest in the field of rheumatology. Locally increased vasculature in the synovial membrane of these joints can be a marker for rheumatoid arthritis. In previous work we showed that part of the photoacoustically induced ultrasound from the epidermis reflects on the bone surface within the finger. These reflected signals could be wrongly interpreted as new photoacoustic sources. In this work we show that a conventional ultrasound reconstruction algorithm, that considers the skin as a collection of ultrasound transmitters and the PA tomography probe as the detector array, can be used to delineate bone surfaces of a finger. This can in the future assist in the localization of the joint gaps. This can provide us with a landmark to localize the region of the inflamed synovial membrane. We test the approach on finger mimicking phantoms.

Photoacoustic tomography of the human finger: towards the assessment of inflammatory joint diseases

Inflammatory arthritis is often manifested in finger joints. The growth of new or withdrawal of old blood vessels can be a sensitive marker for these diseases. Photoacoustic (PA) imaging has great potential in this respect since it allows the sensitive and highly resolved visualization of blood. We systematically investigated PA imaging of finger vasculature in healthy volunteers using a newly developed PA tomographic system. We present the PA results which show excellent detail of the vasculature. Vessels with diameters ranging between 100 mu m and 1.5 mm are visible along with details of the skin, including the epidermis and the subpapillary plexus. The focus of all the studies is at the proximal and distal interphalangeal joints, and in the context of ultimately visualizing the inflamed synovial membrane in patients. This work is important in laying the foundation for detailed research into PA imaging of the phalangeal vasculature in patients suffering from rheumatoid arthritis.

Optoelectronic Properties of Graphene on Silicon Substrate: Effect of Defects in Graphene

Engineering of electronic energy band structure in graphene based nanostructures has several potential applications. Substrate induced bandgap opening in graphene results several optoelectronic properties due to the inter-band transitions. Various defects like structures, including Stone-Walls and higher-order defects are observed when a graphene sheet is exfoliated from graphite and in many other growth conditions. Existence of defect in graphene based nanostructures may cause changes in optoelectronic properties. Defect engineered graphene on silicon system are considered in this paper to study the tunability of optoelectronic properties. Graphene on silicon atomic system is equilibrated using molecular dynamics simulation scheme. Based on this study, we confirm the existence of a stable super-lattice. Density functional calculations are employed to determine the energy band structure for the super-lattice. Increase in the optical energy bandgap is observed with increasing of order of the complexity in the defect structure. Optical conductivity is computed as a function of incident electromagnetic energy which is also increasing with increase in the defect order. Tunability in optoelectronic properties will be useful in understanding graphene based design of photodetectors, photodiodes and tunnelling transistors.

Wireless Aircraft Fuel Quantity Indication System

A wireless fuel quantity indication system (FQIS) has been developed using an RFID-enabled sensing platform. The system comprises a fully passive tag, modified reader protocol, capacitive fuel probe, and auxiliary antenna for additional energy harvesting. Results of fluid testing show sensitivity to changes in fluid height of less than 0.25in. An RF-DC harvesting circuit was developed, which delivers up to 5dBm of input power through a remote radio frequency (RF) source. Testing was conducted in a loaded reverberation chamber to emulate the fuel tank environment. Results demonstrate feasibility of the remote source to power the sensor with less than 1W of maximum transmit power and under 100ms dwell time (100mW average power) into the tank. This indicates adequate coverage for large transport aircraft at safe operating levels with a sample rate of up to 1 sample/s.

A Polymatroid Approach to Separable Convex Optimization with Linear Ascending Constraints

We revisit a problem studied by Padakandla and Sundaresan SIAM J. Optim., August 2009] on the minimization of a separable convex function subject to linear ascending constraints. The problem arises as the core optimization in several resource allocation problems in wireless communication settings. It is also a special case of an optimization of a separable convex function over the bases of a specially structured polymatroid. We give an alternative proof of the correctness of the algorithm of Padakandla and Sundaresan. In the process we relax some of their restrictions placed on the objective function.

Throughput Analysis of Best-m Feedback in OFDM Systems with Uniformly Correlated Subchannels

Practical orthogonal frequency division multiplexing (OFDM) systems, such as Long Term Evolution (LTE), exploit multi-user diversity using very limited feedback. The best-m feedback scheme is one such limited feedback scheme, in which users report only the gains of their m best subchannels (SCs) and their indices. While the scheme has been extensively studied and adopted in standards such as LTE, an analysis of its throughput for the practically important case in which the SCs are correlated has received less attention. We derive new closed-form expressions for the throughput when the SC gains of a user are uniformly correlated. We analyze the performance of the greedy but unfair frequency-domain scheduler and the fair round-robin scheduler for the general case in which the users see statistically non-identical SCs. An asymptotic analysis is then developed to gain further insights. The analysis and extensive numerical results bring out how correlation reduces throughput.

Modified Greedy Pursuits for Improving Sparse Recovery

Compressive Sensing (CS) theory combines the signal sampling and compression for sparse signals resulting in reduction in sampling rate. In recent years, many recovery algorithms have been proposed to reconstruct the signal efficiently. Subspace Pursuit and Compressive Sampling Matching Pursuit are some of the popular greedy methods. Also, Fusion of Algorithms for Compressed Sensing is a recently proposed method where several CS reconstruction algorithms participate and the final estimate of the underlying sparse signal is determined by fusing the estimates obtained from the participating algorithms. All these methods involve solving a least squares problem which may be ill-conditioned, especially in the low dimension measurement regime. In this paper, we propose a step prior to least squares to ensure the well-conditioning of the least squares problem. Using Monte Carlo simulations, we show that in low dimension measurement scenario, this modification improves the reconstruction capability of the algorithm in clean as well as noisy measurement cases.

A New Algorithm for Nonparametric Sequential Detection

We consider nonparametric sequential hypothesis testing problem when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to a general family of distributions. We propose a simple algorithm to address the problem. Its performance is analysed and asymptotic properties are proved. The simulated and analysed performance of the algorithm is compared with an earlier algorithm addressing the same problem with similar assumptions. Finally, we provide a justification for our model motivated by a Cognitive Radio scenario and modify the algorithm for optimizing performance when information about the prior probabilities of occurrence of the two hypotheses is available.