Efficient layered data transport over multicarrier systems usingoptimized embedded modulation

We tackle the problem of efficient layered or multiresolution (MR) data transmission over multicarrier modulation (MCM) systems. We treat the source as being characterized by multiple layers of importance, i.e., having different bit error rate (BER) requirements. First we consider the MCM systems in a multiresolution framework using multiplexing techniques. Then we present the idea of embedded multicarrier modulation (E-MCM) as an effective way of achieving this, and introduce a fast table-lookup-based power allocation algorithm that optimizes the multicarrier constellation design in terms of maximizing the deliverable throughput bit-rate, subject to a total power constraint. Simulation results of our E-MCM system reveal substantial gains (up to about 25%) in deliverable bit-rates over optimized time-division-multiplexed-based designs     

High speed multiplier using Nikhilam Sutra algorithm of Vedic mathematics

This article presents the design of a new high-speed multiplier architecture using Nikhilam Sutra of Vedic mathematics. The proposed multiplier architecture finds out the compliment of the large operand from its nearest base to perform the multiplication. The multiplication of two large operands is reduced to the multiplication of their compliments and addition. It is more efficient when the magnitudes of both operands are more than half of their maximum values. The carry save adder in the multiplier architecture increases the speed of addition of partial products. The multiplier circuit is synthesised and simulated using Xilinx ISE 10.1 software and implemented on Spartan 2 FPGA device XC2S30-5pq208. The output parameters such as propagation delay and device utilisation are calculated from synthesis results. The performance evaluation results in terms of speed and device utilisation are compared with earlier multiplier architecture. The proposed design has speed improvements compared to multiplier architecture presented in the literature.     

Pseudo-Parallel Datapath Structure for Power Optimal Implementation of 128-pt FFT/IFFT for WPAN

An optimal implementation of 128-Pt FFT/IFFT for low power IEEE 802.15.3a WPAN using pseudo-parallel datapath structure is presented, where the 128-Pt FFT is devolved into 8-Pt and 16-Pt FFTs and then once again by devolving the 16-Pt FFT into 4×4 and 2×8. We analyze 128-Pt FFT/IFFT architecture for various pseudo-parallel 8-Pt and 16-Pt FFTs and an optimum datapath architecture is explored. It is suggested that there exists an optimum degree of parallelism for the given algorithm. The analysis demonstrated that with a modest increase in area one can achieve significant reduction in power. The proposed architectures complete one parallel-to-parallel (i.e., when all input data are available in parallel and all output data are generated in parallel) 128-point FFT computation in less than 312.5 ns and thereby meet the standard specification. The relative merits and demerits of these architectures have been analyzed from the algorithm as well as implementation point of view. Detailed power analysis of each of the architectures with a different number of data paths at block level is described. We found that from power perspective the architecture with eight datapaths is optimum. The core power consumption with optimum case is 60.6 MW which is only less than half of the latest reported 128-point FFT design in 0.18u technology. Furthermore, a Single Event Upset (SEU) tolerant scheme for registers is also explored. The SEU tolerant scheme will not affect the performance, however, there is an increase power consumption of about 42 percent. Apart from the low power consumption, the advantages of the proposed architectures include reduced hardware complexity, regular data flow and simple counter based control.     

Yield optimization in large RAM's with hierarchical redundancy

The authors present and analyze large RAM architectures with hierarchical redundancy and determine the optimal redundancy organization for yield enhancement. A two-level redundancy scheme is used for defect tolerance, and the defect distribution is modeled using the compounded Poisson model. The tree random access memory (TRAM), which has been proposed as a design methodology for future multimegabit memories (N. Jarwala et al., 1988) is considered as an example for modeling and optimization. The results show that the two-level hierarchical redundancy approach, with spare bit and word lines within memory quadrants, and additional spare modules for global sparing, along with redundant interconnections can efficiently provide defect tolerance and viable yields for future generations of high-density dynamic random access memories     

Low noise wide bandgap SiC based IMPATT diodes at sub-millimeter wave frequencies and at high temperature

We have presented a comparative account of the high frequency prospective as well as noise behaviors of wide-bandgap 4H-SiC and 6H-SiC based on different structures of IMPATT diodes at sub-millimeter-wave frequencies up to 2.18 THz. The computer simulation study establishes the feasibility of the SiC based IMPATT diode as a high power density terahertz source. The most significant feature lies in the noise behavior of the SiC IMPATT diodes. It is noticed that the 6H-SiC DDR diode shows the least noise measure of 26.1 dB as compared to that of other structures. Further, it is noticed that the noise measure of the SiC IMPATT diode is less at a higher operating frequency compared to that at a lower operating frequency.     

Handover scheme for mobile cellular communication systems

A new scheme for minimising handover failure probability in mobile cellular communication systems, by exchanging channels between two mobiles moving in opposite directions across the endeavour area of adjacent cells is presented. The performance evaluation of the new scheme is carried out by computer simulation of a two cell model     

Radial Sub-band Allocation with Downlink Interference Mitigation in Macro–Femto Environment

Wireless Personal Communications - Femtocell deployment is an important strategy when it comes to improvement of QoS metrics in areas of poor cell coverage like indoors in an LTE environment. This,...     

Hand-Gesture Computing for the Hearing and Speech Impaired

An instrumented data glove with a wireless interface provides convenient and natural human-computer interaction for people with speech or hearing impairments.     

Distributed compression in a dense microsensor network

Distributed nature of the sensor network architecture introduces unique challenges and opportunities for collaborative networked signal processing techniques that can potentially lead to significant performance gains. Many evolving low-power sensor network scenarios need to have high spatial density to enable reliable operation in the face of component node failures as well as to facilitate high spatial localization of events of interest. This induces a high level of network data redundancy, where spatially proximal sensor readings are highly correlated. We propose a new way of removing this redundancy in a completely distributed manner, i.e., without the sensors needing to talk, to one another. Our constructive framework for this problem is dubbed DISCUS (distributed source coding using syndromes) and is inspired by fundamental concepts from information theory. We review the main ideas, provide illustrations, and give the intuition behind the theory that enables this framework.We present a new domain of collaborative information communication and processing through the framework on distributed source coding. This framework enables highly effective and efficient compression across a sensor network without the need to establish inter-node communication, using well-studied and fast error-correcting coding algorithms     

Distributed source coding using syndromes (DISCUS): design and construction

We address the problem of compressing correlated distributed sources, i.e., correlated sources which are not co-located or which cannot cooperate to directly exploit their correlation. We consider the related problem of compressing a source which is correlated with another source that is available only at the decoder. This problem has been studied in the information theory literature under the name of the Slepian-Wolf (1973) source coding problem for the lossless coding case, and as "rate-distortion with side information" for the lossy coding case. We provide a constructive practical framework based on algebraic trellis codes dubbed as DIstributed Source Coding Using Syndromes (DISCUS), that can be applicable in a variety of settings. Simulation results are presented for source coding of independent and identically distributed (i.i.d.) Gaussian sources with side information available at the decoder in the form of a noisy version of the source to be coded. Our results reveal the promise of this approach: using trellis-based quantization and coset construction, the performance of the proposed approach is 2-5 dB from the Wyner-Ziv (1976) bound.