Adaptively Grouped Multilevel Space-Time Trellis Codes

Grouped multilevel space-time trellis codes (GMLSTTCs) utilize multilevel coding (MLC), antenna grouping and space time trellis codes (STTCs) for simultaneously providing coding gain, diversity improvement and increased spectral efficiency. The performance of GMLSTTCs is limited due to predefining of the antenna groups. It has been shown that when perfect or partial channel state information is available at the transmitter, the performance and capacity of space-time coded system can be further improved. In this paper, we present a new code designed by combining MLC, STTCs, antenna grouping and channel state information at transmitter, henceforth referred to as adaptively grouped multilevel space time trellis codes (AGMLSTTCs). AGMLSTTCs use a single full-diversity STTC at initial some levels and multiple STTCs at some later levels. The single full diversity STTC at each initial level spans all transmit antennas and the STTC at each later level spans a group of transmit antennas. The channel state information at the transmitter is used to adaptively group the transmit antennas for the later levels. Instantaneous channel power gain is calculated between each transmit antenna and all the receive antennas. A subset of transmit antennas having maximum channel power gain is selected to form a group. The simulation results show that AGMLSTTCs enable to transmit more than one data symbol per time slot with improved error performance over GMLSTTCs with predefined transmit antenna grouping.     

Two-stage decision making policy for opportunistic spectrum access and validation on USRP testbed

“Recently, various paradigms, for instance, device-to-device communications, LTE-unlicensed and cognitive radio based on an opportunistic spectrum access (OSA) are being envisioned to improve the average spectrum utilization. In OSA, secondary (unlicensed) users (SUs) need decision making policies (DMPs) to identify and transmit over optimum frequency bands without any interference to the primary (licensed) users as well as minimize the number of collisions among SUs. In this paper, we have proposed a two-stage DMP consisting of Bayesian Multi-armed Bandit algorithm to accurately characterize the frequency band statistics independently at each SU and frequency band selection scheme for orthogonalization of SUs. The analytical and simulation results show that the proposed DMP leads to 45% improvement in the average spectrum utilization compared to 36–39% in the existing DMPs. Furthermore, the number of collisions are 58.5% lower in the proposed DMP making SU terminals energy-efficient. The performance of the proposed DMP has been verified on the proposed USRP testbed in real radio environment and the experimental results closely match the simulated results .”     

A model of front-illuminated n+-p-p+high-efficiency silicon solar cell

A realistic model of a front-illuminated n⁺-p-p⁺ silicon solar cell is developed by solving the current continuity equations for minority carriers in the quasi-neutral regions in steady state, assuming the light in the cell is trapped as a result of multiple reflections at the front and the back of the cell. This model is used to study the effects of the front emitter thickness and doping level and the light trapping on the J-V characteristic and thereby on the open-circuit voltage, short-circuit current density, curve factor, and the efficiency of the cell. A textured cell with an emitter thickness in the range of 0.3-1.0 μm with its doping ≈5×10¹⁸ cm^-3 and the recombination velocities of minority carriers as large as 200 cm/s at the n⁺ front surface and 10 cm/s at the back of the p base can exhibit an efficiency in excess of 26% (under AM 1.5 sunlight of 100 mW/cm² intensity) at 25°C if the light reflection losses at the front surface can be made small     

Stochastic model of k-parallel service channels

With the enhanced rate of inflow of units, especially in randomly distributed batch sizes, service through parallel channels appears to be the optimal course for relieving congestion and reducing the waiting time of customers. Keeping this fact in view, this paper involves k-parallel service channels which operate together for dealing with the situation of bulk arrivals. The time-dependent and steady state behaviour of the queueing system is dealt with at length. Laplace transforms of the probability generating functions for queue length distributions are obtained and the steady state results are derived therefrom. Finally, some particular cases which can be derived from the main theorem are also discussed.     

Channel capacity with suboptimal adaptation technique over generalized-K fading using marginal moment generating function

In this paper we have computed the channel capacity for suboptimal adaptation technique over the generalized-K fading environment. The analytical expression for channel capacity in case of the truncated channel inversion with fixed rate (C_TCIFR) has been exploited in terms of marginal moment generating function (MMGF) and its performance is evaluated over the generalized-K faded environment. The MMGF based approach for the computation of channel capacity has been validated with the reported literature for channel capacity in case of the channel inversion with fixed rate using the suboptimal adaptive technique.     

On a Non-linear Electronic Circuit Filtering

The stochastic versions of non-linear dynamic circuits are formalized using non-linear stochastic differential equations. Stochastic differential equations (SDEs) are exploited to analyse dynamical systems in noisy environments. A potential application of the SDEs can be regarded as ‘stochastic processes in electronic circuits’. The noisy sampling mixer, a component of digital wireless communications, is an appealing and standard case from the dynamical systems’ viewpoint. It assumes the structure of a non-linear SDE, and its linearized version becomes time-varying bilinear SDE. This paper derives the filtering equations for the noisy non-linear sampling mixer circuit utilizing the filtering density evolution equation. The filtering model for the stochastic problem of concern here comprises the following: (1) a non-linear SDE describing the noisy sampling mixer and (2) a non-linear noisy observation equation. It is interesting to note that the filtered estimate accounts for observations. On the other hand, the predicted estimate does not account for the observation terms in evolution equations. As a result of this, the filtered estimate confirms the greater accuracy of estimated state trajectory in contrast to the predicted trajectory. The filtering equation of this paper can be further utilized for control of the noisy sampling mixer, where the observations are available.     

A Markov Decision Process based flow assignment framework for heterogeneous network access

We consider a scenario where devices with multiple networking capabilities access networks with heterogeneous characteristics. In such a setting, we address the problem of efficient utilization of multiple access networks by devices via optimal assignment of traffic flows with given utilities to different networks. We develop and analyze a device middleware functionality that monitors network characteristics and employs a Markov Decision Process (MDP) based control scheme that in conjunction with stochastic characterization of the available bit rate and delay of the networks generates an optimal policy for allocation of flows to different networks. The optimal policy maximizes, under available bit rate and delay constraints on the access networks, a discounted reward which is a function of the flow utilities. The flow assignment policy is periodically updated and is consulted by the flows to dynamically perform network selection during their lifetimes. We perform measurement tests to collect traces of available bit rate and delay characteristics on Ethernet and WLAN networks on a work day in a corporate work environment. We implement our flow assignment framework in ns-2 and simulate the system performance for a set of elastic video-like flows using the collected traces. We demonstrate that the MDP based flow assignment policy leads to significant enhancement in the QoS provisioning (higher rate allocation, lower packet delays and packet loss rates) for the flows and better access network utilization, as compared to policies that allocate flows to different networks using greedy approaches or heuristics like average available bit rate on the networks.     

Multichannel ECG data compression based on multiscale principal component analysis

In this paper, multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression. In wavelet domain, principal components analysis (PCA) of multiscale multivariate matrices of multichannel signals helps reduce dimension and remove redundant information present in signals. The selection of principal components (PCs) is based on average fractional energy contribution of eigenvalue in a data matrix. Multichannel compression is implemented using uniform quantizer and entropy coding of PCA coefficients. The compressed signal quality is evaluated quantitatively using percentage root mean square difference (PRD), and wavelet energy-based diagnostic distortion (WEDD) measures. Using dataset from CSE multilead measurement library, multichannel compression ratio of 5.98:1 is found with PRD value 2.09% and the lowest WEDD value of 4.19%. Based on, gold standard subjective quality measure, the lowest mean opinion score error value of 5.56% is found.