Layer-by-Layer Self-Assembled Metal-Ion- (Ag-, Co-, Ni-, and Pd-) Doped TiO2 Nanoparticles: Synthesis, Characterisation, and Visible Light Degradation of Rhodamine B

Metal-ion- (Ag, Co, Ni and Pd) doped titania nanocatalysts were successfully deposited on glass slides by layer-by-layer (LbL) self-assembly technique using a poly(styrene sulfonate sodium salt) (PSS) and poly(allylamine hydrochloride) (PAH) polyelectrolyte system. Solid diffuse reflectance (SDR) studies showed a linear increase in absorbance at 416 nm with increase in the number of m-TiO2 thin films. The LbL assembled thin films were tested for their photocatalytic activity through the degradation of Rhodamine B under visible-light illumination. From the scanning electron microscope (SEM), the thin films had a porous morphology and the atomic force microscope (AFM) studies showed ``rough'' surfaces. The porous and rough surface morphology resulted in high surface areas hence the high photocatalytic degradation (up to 97% over a 6.5 h irradiation period) using visible-light observed. Increasing the number of multilayers deposited on the glass slides resulted in increased film thickness and an increased rate of photodegradation due to increase in the availability of more nanocatalysts (more sites for photodegradation). The LbL assembled thin films had strong adhesion properties which made them highly stable thus displaying the same efficiencies after five (5) reusability cycles.

A hybrid RTS-BP algorithm for improved detection of large-MIMO M-QAM signals

Low-complexity near-optimal detection of large-MIMO signals has attracted recent research. Recently, we proposed a local neighborhood search algorithm, namely reactive tabu search (RTS) algorithm, as well as a factor-graph based belief propagation (BP) algorithm for low-complexity large-MIMO detection. The motivation for the present work arises from the following two observations on the above two algorithms: i) Although RTS achieved close to optimal performance for 4-QAM in large dimensions, significant performance improvement was still possible for higher-order QAM (e.g., 16-, 64-QAM). ii) BP also achieved near-optimal performance for large dimensions, but only for {±1} alphabet. In this paper, we improve the large-MIMO detection performance of higher-order QAM signals by using a hybrid algorithm that employs RTS and BP. In particular, motivated by the observation that when a detection error occurs at the RTS output, the least significant bits (LSB) of the symbols are mostly in error, we propose to first reconstruct and cancel the interference due to bits other than LSBs at the RTS output and feed the interference cancelled received signal to the BP algorithm to improve the reliability of the LSBs. The output of the BP is then fed back to RTS for the next iteration. Simulation results show that the proposed algorithm performs better than the RTS algorithm, and semi-definite relaxation (SDR) and Gaussian tree approximation (GTA) algorithms.

Cognitive radio implementation for a frequency hopping primary signal

Frequency hopping communications, used in the military present significant opportunities for spectrum reuse via the cognitive radio technology. We propose a MAC which incorporates hop instant identification, and supports network discovery and formation, QOS Scheduling and secondary communications. The spectrum sensing algorithm is optimized to deal with the problem of spectral leakage. The algorithms are implemented in a SDR platform based test bed and measurement results are presented.

Fast Eigen solution for homogeneous quadratic minimization with at most three constraints

We propose an eigenvalue based technique to solve the Homogeneous Quadratic Constrained Quadratic Programming problem (HQCQP) with at most three constraints which arise in many signal processing problems. Semi-Definite Relaxation (SDR) is the only known approach and is computationally intensive. We study the performance of the proposed fast eigen approach through simulations in the context of MIMO relays and show that the solution converges to the solution obtained using the SDR approach with significant reduction in complexity.

Secure Communication in Amplify-and-Forward Networks with Multiple Eavesdroppers: Decoding with SNR Thresholds

The problem of secure unicast communication over a two hop Amplify-and-Forward wireless relay network with multiple eavesdroppers is considered. Assuming that a receiver (destination or eavesdropper) can decode a message only if the received SNR is above a predefined threshold, we consider this problem in two scenarios. In the first scenario, we maximize the SNR at the legitimate destination, subject to the condition that the received SNR at each eavesdropper is below the target threshold. Due to the non-convex nature of the objective function and eavesdroppers' constraints, we transform variables and obtain a quadratically constrained quadratic program (QCQP) with convex constraints, which can be solved efficiently. When the constraints are not convex, we consider a semidefinite relaxation (SDR) to obtain computationally efficient approximate solution. In the second scenario, we minimize the total power consumed by all relay nodes, subject to the condition that the received SNR at the legitimate destination is above the threshold and at every eavesdropper, it is below the corresponding threshold. We propose a semidefinite relaxation of the problem in this scenario and also provide an analytical lower bound.