Application of hidden markov models to blind channel estimation and data detection in a gsm environment

In this paper, we present an algorithm based on the Hidden Markov Models (HMM) theory to solve the problem of blind channel estimation and sequence detection in mobile digital communications. The environment in which the algorithm is tested is the Paneuropean Mobile Radio System, also known as GSM. In this system, a large part in each burst is devoted to allocate a training sequence used to obtain a channel estimate. The algorithm presented would not require this sequence, and that would imply an increase of the system capacity. Performance, evaluated for standard test channels, is close to that of non-blind algorithms.Peer ReviewedPostprint (published version

Equalization of Third-Order Intermodulation Products in Wideband Direct Conversion Receivers

This paper reports a SAW-less direct-conversion receiver which utilizes a mixed-signal feedforward path to regenerate and adaptively cancel IM3 products, thus accomplishing system-level linearization. The receiver system performance is dominated by a custom integrated RF front end implemented in 130-nm CMOS and achieves an uncorrected out-of-band IIP3 of -7.1 dBm under the worst-case UMTS FDD Region 1 blocking specifications. Under IM3 equalization, the receiver achieves an effective IIP3 of +5.3 dBm and meets the UMTS BER sensitivity requirement with 3.7 dB of margin

Bacterial Foraging Based Channel Equalizers

A channel equalizer is one of the most important subsystems in any digital communication receiver. It is also the subsystem that consumes maximum computation time in the receiver. Traditionally maximum-likelihood sequence estimation (MLSE) was the most popular form of equalizer. Owing to non-stationary characteristics of the communication channel MLSE receivers perform poorly. Under these circumstances ‘Maximum A-posteriori Probability (MAP)’ receivers also called Bayesian receivers perform better. Natural selection tends to eliminate animals with poor “foraging strategies” and favor the propagation of genes of those animals that have successful foraging strategies since they are more likely to enjoy reproductive success. After many generations, poor foraging strategies are either eliminated or shaped into good ones (redesigned). Logically, such evolutionary principles have led scientists in the field of “foraging theory” to hypothesize that it is appropriate to model the activity of foraging as an optimization process. This thesis presents an investigation on design of bacterial foraging based channel equalizer for digital communication. Extensive simulation studies shows that the performance of the proposed receiver is close to optimal receiver for variety of channel conditions. The proposed receiver also provides near optimal performance when channel suffers from nonlinearities

The collapse of cooperation in evolving games

Game theory provides a quantitative framework for analyzing the behavior of rational agents. The Iterated Prisoner's Dilemma in particular has become a standard model for studying cooperation and cheating, with cooperation often emerging as a robust outcome in evolving populations. Here we extend evolutionary game theory by allowing players' strategies as well as their payoffs to evolve in response to selection on heritable mutations. In nature, many organisms engage in mutually beneficial interactions, and individuals may seek to change the ratio of risk to reward for cooperation by altering the resources they commit to cooperative interactions. To study this, we construct a general framework for the co-evolution of strategies and payoffs in arbitrary iterated games. We show that, as payoffs evolve, a trade-off between the benefits and costs of cooperation precipitates a dramatic loss of cooperation under the Iterated Prisoner's Dilemma; and eventually to evolution away from the Prisoner's Dilemma altogether. The collapse of cooperation is so extreme that the average payoff in a population may decline, even as the potential payoff for mutual cooperation increases. Our work offers a new perspective on the Prisoner's Dilemma and its predictions for cooperation in natural populations; and it provides a general framework to understand the co-evolution of strategies and payoffs in iterated interactions.Comment: 33 pages, 13 figure

Blind Search for Optimal Wiener Equalizers Using an Artificial Immune Network Model

This work proposes a framework to determine the optimal Wiener equalizer by using an artificial immune network model together with the constant modulus (CM) cost function. This study was primarily motivated by recent theoretical results concerning the CM criterion and its relation to the Wiener approach. The proposed immune-based technique was tested under different channel models and filter orders, and benchmarked against a procedure using a genetic algorithm with niching. The results demonstrated that the proposed strategy has a clear superiority when compared with the more traditional technique. The proposed algorithm presents interesting features from the perspective of multimodal search, being capable of determining the optimal Wiener equalizer in most runs for all tested channels

Blind multiuser detection using hidden markov models theory

We present an adaptive algorithm based on the theory of hidden Markov models (HMM) which is capable of jointly detecting the users in a DS-CDMA system. The proposed technique is near-far resistant and completely blind in the sense that no knowledge of the signature sequences, channel state information or training sequences is required for any user. In addition to this, an estimate of the signature of each user convolved with its physical channel impulse response (CIR), and an estimate of the background noise variance are provided once convergence is achieved (as well as estimated data sequences). At this moment, and using that CIR estimate, we can switch to any decision-directed (DD) adaptation scheme.Peer ReviewedPostprint (published version

Low Probability of Intercept Waveforms via Intersymbol Dither Performance under Multipath Conditions

This thesis examines the effects of multipath interference on Low Probability of Intercept (LPI) waveforms generated using intersymbol dither. LPI waveforms are designed to be difficult for non-cooperative receivers to detect and manipulate, and have many uses in secure communications applications. In prior research, such a waveform was designed using a dither algorithm to vary the time between the transmission of data symbols in a communication system. This work showed that such a method can be used to frustrate attempts to use non-cooperative receiver algorithms to recover the data. This thesis expands on prior work by examining the effects of multipath interference on cooperative and non-cooperative receiver performance to assess the above method’s effectiveness using a more realistic model of the physical transmission channel. Both two and four ray multipath interference channel models were randomly generated using typical multipath power profiles found in existing literature. Different combinations of maximum allowable symbol delay, pulse shapes and multipath channels were used to examine the bit error rate performance of 1) a Minimum Mean Squared Error (MMSE) cooperative equalizer structure with prior knowledge of the dither pattern and 2) a Constant Modulus Algorithm (CMA) non-cooperative equalizer. Cooperative MMSE equalization resulted in approximately 6-8 dB BER performance improvement in Eb/No over non-cooperative equalization, and for a full range symbol timing dither non-cooperative equalization yields a theoretical BER limit of Pb=10−1. For 50 randomly generated multipath channels, six of the four ray channels and 15 of the two ray channels exhibited extremely poor equalization results, indicating a level of algorithm sensitivity to multipath conditions

Statistical Analysis of 100 Gbps per Wavelength SWDM VCSEL-MMF Data Center Links on a Large Set of OM3 and OM4 Fibers

We present a detailed statistical study on achievable reach of 100 Gbps data center optical links based on vertical cavity surface emitting lasers (VCSEL) and multimode fibers (MMF). Based on the characterization of the spectral and spatial properties of eight lasers and of the modal and dispersion behavior of a large set of 20233 OM3 and OM4 modeled fibers (obtained by properly extending an initial set of 500 measured fibers), we compute the resulting frequency responses of all of the VCSEL-MMF combinations. Then, we feed them to a numerical tool modeling PAM-4 transmission at 100 Gbps net bit rate per wavelength. Our model analyzes performance at distances up to 400 meters, using three different adaptive equalizers at the receiver and considering two forward error correction overheads. We show that 100 Gbps operation is feasible for 99% of the simulated links reaching up to 120 m over OM4 at 850 nm and using a decision feedback equalizer (DFE). Aggregated data rates of 200 Gbps and 400 Gbps per fiber using Shortwave Wavelength Division Multiplexing (SWDM) are achievable for 99% of the links reaching 80 m over OM4 using two wavelengths and feed-forward equalizer (FFE) and four wavelengths and maximum likelihood sequence estimation (MLSE)-based equalizer, respectively