Steady state distribution of a hyperbolic digital tanlock loop with extended pull-in range for frequency synchronization in high doppler environment

A hyperbolic arctan based Digital Tanlock Loop (D-TLL) operating with complex signals at base-band or intermediate frequencies in high Doppler environments is treated here. The arctan based loop, known as the tanlock loop (TLL), is used in software defined radio architectures for frequency acquisition and tracking. The hyperbolic nonlinearity intentionally introduced within the phase detector extends the pull-in range of the frequency for a given loop, compared to the normal D-TLL, allowing a wider frequency acquisition range which is suitable for high Doppler communications environment. In this paper we study the steady state phase noise performances of such a feedback loop for additive Gaussian noise using stochastic analysis. The stochastic model of a first-order hyperbolic loop and the theoretical analysis for the corresponding statistical distribution of the closed loop steady state phase noise are presented. The theoretical results are also verified by simulations

Cognitive relay nodes for airborne LTE emergency networks

This paper is proposing a novel concept of Cognitive Relay Node for intelligently improving the radio coverage of an airborne LTE emergency network, considering the scenarios outlined in the ABSOLUTE research project. The proposed network model was simulated comparing the different cases of deploying relay nodes to complement the coverage of an aerial LTE network. Simulation results of the proposed Cognitive Relay Nodes show significant performance improvement in terms of radio coverage quantified by the regional outage probability enhancement. Also, this paper is presenting the methodology and results of choosing the optimum aerial eNodeB altitude

Bias-free phase tracking with linear and nonlinear systems

The arctan function is a well-known Maximum Likelihood (ML) estimator of the phase angle of a complex signal in additive white Gaussian noise. In this paper we revisit the arctan-based ML phase estimator and identify the bias problem for phase tracking. We show that the posteriori probability density function of becomes a bi-modal distribution for small values of signal to noise ratio and larger values of . In such cases the mean and the mode differ from each other, and as a result when such ML phase estimates are used as an input to a linear system (LS), example for phase tracking, the resulting output (which is essentially the mean value of the phase) differs from its true value which is the mode. In such situations there exist a mean (tracking) error at the output of the LS from its true value, and in (non-Bayesian) statistical terms there exist a bias in the estimates. In this paper, we provide some statistical analysis to explain the above problem, and also provide solutions for bias correction when a LS is used for tracking phase. Furthermore, we also provide two nonlinear phase tracking systems, 1) a Monte- Carlo based sequential phase tracking technique and 2) a secondorder digital-phase locked loop based method, for bias-free phase tracking which eliminate the bias problem that occurs in the case of linear phase tracking with ML estimates

Power-trading in wireless communications: a cooperative networking business model

Managing the power resource in battery operated wireless devices is very crucial for extending the lifetime, here we propose the concept of power trading in wireless communications. We present a business model using sealed bid procurement auction based game theory for power-trading in cooperative wireless communication with quality of service (QoS) constraints. We formulate the problem as an auction in a buyer's market sequentially/repeatedly played with a single source and a multiple relay network. The source, in-need of cooperation of a relay due to lack of battery power to communicate with the destination, broadcasts a cooperation-request specifying its QoS requirements. The QoS that we consider here are the bit error rate and the total delay associated with relaying the source data. The relays respond with their bids in terms of Euros/bit, and the source selects the best relay based on the bids. The relays compete with each other to win the game and profit from power trading. Each relay updates its pricing index via reinforcement learning to win the game during successive bidding intervals of the repeated game. Based on this model our results show that the relay node with the best features such as a better wireless channel and a better geographical position with respect to the source and destination nodes has a better chance of winning the game, and hence giving rise to a dominant strategy. More importantly, we show that the gains from the wireless channels can be converted into economic profits which is an attractive feature of the proposed business model for power trading

Aerial-terrestrial communications: terrestrial cooperation and energy-efficient transmissions to aerial-base stations

Hybrid aerial-terrestrial communication networks based on low-altitude platforms are expected to meet optimally the urgent communication needs of emergency relief and recovery operations for tackling large-scale natural disasters. The energy-efficient operation of such networks is important given that the entire network infrastructure, including the battery-operated ground terminals, exhibits requirements to operate under power-constrained situations. In this paper, we discuss the design and evaluation of an adaptive cooperative scheme intended to extend the survivability of the battery-operated aerial-terrestrial communication links. We propose and evaluate a real-time adaptive cooperative transmission strategy for dynamic selection between direct and cooperative links based on the channel conditions for improved energy efficiency. We show that the cooperation between mobile terrestrial terminals on the ground could improve energy efficiency in the uplink, depending on the temporal behavior of the terrestrial and aerial uplink channels. The corresponding delay in having cooperative (relay-based) communications with relay selection is also addressed. The simulation analysis corroborates that the adaptive transmission technique improves overall energy efficiency of the network whilst maintaining low latency, enabling real-time applications

Performance evaluation of a linear predictor frequency estimator for mobile flat fading wireless channels

A well known frequency estimation algorithm using the linear prediction method is analyzed for flat fading wireless channels. The estimator outputs are statistically analyzed and its jitter performances are compared with the non-fading case and the Cramer-Rao bound. We provide a closed form solution for the distribution and the variance of the frequency estimates under fading conditions by making valid assumptions. We also verify the theoretical model using simulations. Analysis shows that the variance of the estimates for flat fading channels reaches a threshold point and increasing the transmit power does not necessarily improve the performances any further

Statistical spectrum occupancy prediction for dynamic spectrum access: a classification

Spectrum scarcity due to inefficient utilisation has ignited a plethora of dynamic spectrum access solutions to accommodate the expanding demand for future wireless networks. Dynamic spectrum access systems allow secondary users to utilise spectrum bands owned by primary users if the resulting interference is kept below a pre-designated threshold. Primary and secondary user spectrum occupancy patterns determine if minimum interference and seamless communications can be guaranteed. Thus, spectrum occupancy prediction is a key component of an optimised dynamic spectrum access system. Spectrum occupancy prediction recently received significant attention in the wireless communications literature. Nevertheless, a single consolidated literature source on statistical spectrum occupancy prediction is not yet available in the open literature. Our main contribution in this paper is to provide a statistical prediction classification framework to categorise and assess current spectrum occupancy models. An overview of statistical sequential prediction is presented first. This statistical background is used to analyse current techniques for spectrum occupancy prediction. This review also extends spectrum occupancy prediction to include cooperative prediction. Finally, theoretical and implementation challenges are discussed

Digital PLL assisted frequency estimation with improved error variance

In this paper we present a novel frequency estimation technique, assisted by an imperfect second order arctan based Digital Phase-Locked Loop (D-PLL), for complex single sinusoidal signals in additive white Gaussian noise. The imperfect loop contains the frequency information in its phase error process, at steady state, which is then used to estimate the frequency after the signal has been acquired by the D-PLL. For N samples, this particular estimator has a lower bound on the frequency error variance proportional to 1/N which is different to the well known Maximum Likelihood (ML) estimator that has a lower bound proportional to 1/N3 known as the Cramer- Rao bound (CRB). However, for given combinations of the loop parameters of the D-PLL, the error variance of the proposed estimator gives an improvement over the CRB for small values of N. We also present some detailed noise analysis on the proposed frequency estimator and derive a lower bound for the frequency error variance

A software phase locked loop from theory to practice: TMS320C6000 DSP based implementation and analysis

The study of phase locked loops (PLL) has been heavily treated in literature and most of the theoretical and the analytical results of such are verified using simulations. Here we provide a real-time implementation of a PLL on a digital signal processor (DSP) and analyse and verify the theoretical results associated with it on the implemented system. Such work takes us one step above from the traditional simulation and analysis of PLL to real-time implementation and analysis. The steady state and the acquisition of the PLL are analysed. Issues such as quantization errors are also discussed

Frequency tracking performance using a hyperbolic digital-phase locked loop for ka-band communication in rain fading channels

In this paper we study and present some results on the performances of frequency tracking for Ka-band satellite communications in rain fading channels. The carrier frequency is tracked using a 2nd order hyperbolic phase detector based digital-phase locked loop (D-PLL). The hyperbolic D-PLL has the capability of extending the tracking range compared to the other D-PLL and hence can be designed such that to achieve low phase jitter performance for improved carrier tracking. We present the design and analysis of the D-PLL and show some simulation results on the frequency tracking performance for Kaband rain fading channel. The results are compared with the non-fading noise only case and comparative analyses are made