Dual Power Multiple Access with Multipacket Reception using Local CSI

Contention-based multiple access is a crucial component of many wireless systems. Multiple-packet reception (MPR) schemes that use interference cancellation techniques to receive and decode multiple packets that arrive simultaneously are known to be very efficient. However, the MPR schemes proposed in the literature require complex receivers capable of performing advanced signal processing over significant amounts of soft undecodable information received over multiple contention steps. In this paper, we show that local channel knowledge and elementary received signal strength measurements, which are available to many receivers today, can actively facilitate multipacket reception and even simplify the interference canceling receiver¿s design. We introduce two variants of a simple algorithm called Dual Power Multiple Access (DPMA) that use local channel knowledge to limit the receive power levels to two values that facilitate successive interference cancellation. The resulting receiver structure is markedly simpler, as it needs to process only the immediate received signal without having to store and process signals received previously. Remarkably, using a set of three feedback messages, the first variant, DPMA-Lite, achieves a stable throughput of 0.6865 packets per slot. Using four possible feedback messages, the second variant, Turbo-DPMA, achieves a stable throughput of 0.793 packets per slot, which is better than all contention algorithms known to date.

Simulation blocks for TOSSIM-T2

We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor. The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio, LEDs, and external flash memory. Using the manufacturerpsilas data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

Performance analysis of a slotted-ALOHA protocol on a capture channel with fading

We consider the slotted ALOHA protocol on a channel with a capture effect. There are M reception of a packet is q(i). This model contains the CDMA protocols as special cases. We obtain sufficient rate conditions, which are close to necessary for stability of the system, when the arrival streams are stationary ergodic. Under the same rate conditions, for general regenerative arrival streams, we obtain the rates of convergence to stationarity, finiteness of stationary moments and various functional limit theorems. Our arrival streams contain all the traffic models suggested in the recent literature, including the ones which display long range dependence. We also obtain bounds on the stationary moments of waiting times which can be tight under realistic conditions. Finally, we obtain several results on the transient performance of the system, e.g., first time to overflow and the limits of the overflow process. We also extend the above results to the case of a capture channel exhibiting Markov modulated fading. Most of our results and proofs will be shown to hold also for the slotted ALOHA protocol without capture.

Optimal Receive Antenna Selection in Time-Varying Fading Channels with Practical Training Constraints

Hardware constraints, which motivate receive antenna selection, also require that various antenna elements at the receiver be sounded sequentially to obtain estimates required for selecting the `best' antenna and for coherently demodulating data thereafter. Consequently, the channel state information at different antennas is outdated by different amounts and corrupted by noise. We show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. Rather, a preferable strategy is to linearly weight the channel estimates of different antennas differently, depending on the training scheme. We derive closed-form expressions for the symbol error probability (SEP) of AS for MPSK and MQAM in time-varying Rayleigh fading channels for arbitrary selection weights, and validate them with simulations. We then characterize explicitly the optimal selection weights that minimize the SEP. We also consider packet reception, in which multiple symbols of a packet are received by the same antenna. New suboptimal, but computationally efficient weighted selection schemes are proposed for reducing the packet error rate. The benefits of weighted selection are also demonstrated using a practical channel code used in third generation cellular systems. Our results show that optimal weighted selection yields a significant performance gain over conventional unweighted selection.

A Novel, Balanced, and Energy-Efficient Training Method for Receive Antenna Selection

In receive antenna selection (AS), only signals from a subset of the antennas are processed at any time by the limited number of radio frequency (RF) chains available at the receiver. Hence, the transmitter needs to send pilots multiple times to enable the receiver to estimate the channel state of all the antennas and select the best subset. Conventionally, the sensitivity of coherent reception to channel estimation errors has been tackled by boosting the energy allocated to all pilots to ensure accurate channel estimates for all antennas. Energy for pilots received by unselected antennas is mostly wasted, especially since the selection process is robust to estimation errors. In this paper, we propose a novel training method uniquely tailored for AS that transmits one extra pilot symbol that generates accurate channel estimates for the antenna subset that actually receives data. Consequently, the transmitter can selectively boost the energy allocated to the extra pilot. We derive closed-form expressions for the proposed scheme's symbol error probability for MPSK and MQAM, and optimize the energy allocated to pilot and data symbols. Through an insightful asymptotic analysis, we show that the optimal solution achieves full diversity and is better than the conventional method.

On a Ratio of Functions of Exponential Random Variables and Some Applications

Consider L independent and identically distributed exponential random variables (r.vs) X-1, X-2 ,..., X-L and positive scalars b(1), b(2) ,..., b(L). In this letter, we present the probability density function (pdf), cumulative distribution function and the Laplace transform of the pdf of the composite r.v Z = (Sigma(L)(j=1) X-j)(2) / (Sigma(L)(j=1) b(j)X(j)). We show that the r.v Z appears in various communication systems such as i) maximal ratio combining of signals received over multiple channels with mismatched noise variances, ii)M-ary phase-shift keying with spatial diversity and imperfect channel estimation, and iii) coded multi-carrier code-division multiple access reception affected by an unknown narrow-band interference, and the statistics of the r.v Z derived here enable us to carry out the performance analysis of such systems in closed-form.

Current State of Domestic Concealed Wiring Practices in Bangalore, India

In a modernising world, building and construction trends in recent urban centres such as Bangalore, set precedence for developments in other urban centres of the country. Under such conditions, evaluating the current state of building practices could prove useful for identifying the likely nature of nationwide building trends. This paper comprises a study to evaluate the current state of domestic concealed wiring practices in the context of a modern urban centre area in India. Presently, concealed wiring is the predominant wiring method adopted for residences, both bungalows and apartments. A modern residential block in the city of Bangalore (India) was chosen as the study area. The study included extensive interaction and surveys amongst residents, professionals (architects and engineers) and site personnel (contractors and electricians). In addition, the study also included site verification on the state of wiring practices in the residential block. The study indicates that while aesthetics was the prime reason that dictated the choice of concealed wiring, its effectiveness as an appropriate and safe wiring method is severely compromised. Details of the study, results and recommendations are presented in this paper.

Bayesian Decentralized Spectrum Sensing in Cognitive Radio Networks

This paper considers the problem of spectrum sensing, i.e., the detection of whether or not a primary user is transmitting data by a cognitive radio. The Bayesian framework is adopted, with the performance measure being the probability of detection error. A decentralized setup, where N sensors use M observations each to arrive at individual decisions that are combined at a fusion center to form the overall decision is considered. The unknown fading channel between the primary sensor and the cognitive radios makes the individual decision rule computationally complex, hence, a generalized likelihood ratio test (GLRT)-based approach is adopted. Analysis of the probabilities of false alarm and miss detection of the proposed method reveals that the error exponent with respect to M is zero. Also, the fusion of N individual decisions offers a diversity advantage, similar to diversity reception in communication systems, and a tight bound on the error exponent is presented. Through an analysis in the low power regime, the number of observations needed as a function of received power, to achieve a given probability of error is determined. Monte-Carlo simulations confirm the accuracy of the analysis.

Code design casing deterministic annealing

We address the problem of designing codes for specific applications using deterministic annealing. Designing a block code over any finite dimensional space may be thought of as forming the corresponding number of clusters over the particular dimensional space. We have shown that the total distortion incurred in encoding a training set is related to the probability of correct reception over a symmetric channel. While conventional deterministic annealing make use of the Euclidean squared error distance measure, we have developed an algorithm that can be used for clustering with Hamming distance as the distance measure, which is required in the error correcting, scenario.

Photogenerated radical intermediates of vitamin K-1: a time-resolved resonance Raman study

Quinones play a vital role in the process of electron transfer in bacterial photosynthetic reaction centers. It is of interest to investigate the photochemical reactions involving quinones with a view to elucidating the structure-function relationships in the biological processes. Resonance Raman spectra of radical anions and the time-resolved resonance Raman spectra of vitamin K-1 (model compound for Q(A) in Rhodopseudomonas viridis, a bacterial photosynthetic reception center) are presented. The photochemical intermediates of vitamin K-1, viz. radical anion, ketyl radical and o-quinone methide have been identified. The vibrational assignments of all these intermediates are made on the basis of comparison with our earlier TR3 studies on radical anions of naphthoquinone and menaquinone. (C) 1999 Elsevier Science B.V. All rights reserved.

On Training and Training Voids for Receive Antenna Subset Selection in Time-Varying Channels

Antenna selection (AS) provides most of the benefits of multiple-antenna systems at drastically reduced hardware costs. In receive AS, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. The "best" subset to be used for data reception is determined by means of channel estimates acquired using training sequences. Due to the nature of AS, the channel estimates at different antennas are obtained from different transmissions of the pilot sequence, and are, thus, outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N, we highlight a new issue of "training voids", in which the last pilot transmission is not fully exploited by the receiver. We present a "void-filling" method for fully exploiting these voids, which essentially provides more accurate training for some antennas, and derive the optimal subset selection rule for any void-filling method. We also derive new closed-form equations for the performance of receive AS with optimal subset selection.

Training and Voids in Receive Antenna Subset Selection in Time-Varying Channels

Receive antenna selection (AS) provides many benefits of multiple-antenna systems at drastically reduced hardware costs. In it, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. Due to the nature of AS, the channel estimates at different antennas, which are required to determine the best subset for data reception, are obtained from different transmissions of the pilot sequence. Consequently, they are outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is necessary and optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N , we highlight a new issue of ``training voids'', in which the last pilot transmission is not fully exploited by the receiver. We then present new ``void-filling'' methods that exploit these voids and greatly improve the performance of AS. The optimal subset selection rules with void-filling, in which different antennas turn out to have different numbers of estimates, are also explicitly characterized. Closed-form equations for the symbol error probability with and without void-filling are also developed.

Simulation Blocks for TOSSIM-T2"

We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor.The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio,LEDs, and external flash memory. Using the manufacturer’s data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.