6 research outputs found
Channel Estimation in Coded Modulation Systems
With the outstanding performance of coded modulation techniques in fading channels,
much research efforts have been carried out on the design of communication
systems able to operate at low signal-to-noise ratios (SNRs). From this perspective,
the so-called iterative decoding principle has been applied to many signal processing
tasks at the receiver: demodulation, detection, decoding, synchronization and
channel estimation. Nevertheless, at low SNRs, conventional channel estimators do
not perform satisfactorily. This thesis is mainly concerned with channel estimation
issues in coded modulation systems where different diversity techniques are exploited
to combat fading in single or multiple antenna systems.
First, for single antenna systems in fast time-varying fading channels, the thesis
focuses on designing a training sequence by exploiting signal space diversity (SSD).
Motivated by the power/bandwidth efficiency of the SSD technique, the proposed
training sequence inserts pilot bits into the coded bits prior to constellation mapping
and signal rotation. This scheme spreads the training sequence during a transmitted
codeword and helps the estimator to track fast variation of the channel gains. A comprehensive
comparison between the proposed training scheme and the conventional
training scheme is then carried out, which reveals several interesting conclusions with
respect to both error performance of the system and mean square error of the channel
estimator.
For multiple antenna systems, different schemes are examined in this thesis for
the estimation of block-fading channels. For typical coded modulation systems with
multiple antennas, the first scheme makes a distinction between the iteration in the
channel estimation and the iteration in the decoding. Then, the estimator begins
iteration when the soft output of the decoder at the decoding iteration meets some
specified reliability conditions. This scheme guarantees the convergence of the iterative
receiver with iterative channel estimator. To accelerate the convergence process
and decrease the complexity of successive iterations, in the second scheme, the channel estimator estimates channel state information (CSI) at each iteration with a combination
of the training sequence and soft information. For coded modulation systems
with precoding technique, in which a precoder is used after the modulator, the training
sequence and data symbols are combined using a linear precoder to decrease the
required training overhead. The power allocation and the placement of the training
sequence to be precoded are obtained based on a lower bound on the mean square
error of the channel estimation. It is demonstrated that considerable performance
improvement is possible when the training symbols are embedded within data symbols
with an equi-spaced pattern. In the last scheme, a joint precoder and training
sequence is developed to maximize the achievable coding gain and diversity order
under imperfect CSI. In particular, both the asymptotic performance behavior of the
system with the precoded training scheme under imperfect CSI and the mean square
error of the channel estimation are derived to obtain achievable diversity order and
coding gain. Simulation results demonstrate that the joint optimized scheme outperforms
the existing training schemes for systems with given precoders in terms of error
rate and the amount of training overhead
Recommended from our members
Adaptive Coded Modulation Classification and Spectrum Sensing for Cognitive Radio Systems. Adaptive Coded Modulation Techniques for Cognitive Radio Using Kalman Filter and Interacting Multiple Model Methods
The current and future trends of modern wireless communication systems place heavy demands on fast data transmissions in order to satisfy end users’ requirements anytime, anywhere. Such demands are obvious in recent applications such as smart phones, long term evolution (LTE), 4 & 5 Generations (4G & 5G), and worldwide interoperability for microwave access (WiMAX) platforms, where robust coding and modulations are essential especially in streaming on-line video material, social media and gaming. This eventually resulted in extreme exhaustion imposed on the frequency spectrum as a rare natural resource due to stagnation in current spectrum management policies. Since its advent in the late 1990s, cognitive radio (CR) has been conceived as an enabling technology aiming at the efficient utilisation of frequency spectrum that can lead to potential direct spectrum access (DSA) management. This is mainly attributed to its internal capabilities inherited from the concept of software defined radio (SDR) to sniff its surroundings, learn and adapt its operational parameters accordingly. CR systems (CRs) may commonly comprise one or all of the following core engines that characterise their architectures; namely, adaptive coded modulation (ACM), automatic modulation classification (AMC) and spectrum sensing (SS).
Motivated by the above challenges, this programme of research is primarily aimed at the design and development of new paradigms to help improve the adaptability of CRs and thereby achieve the desirable signal processing tasks at the physical layer of the above core engines. Approximate modelling of Rayleigh and finite state Markov channels (FSMC) with a new concept borrowed from econometric studies have been approached. Then insightful channel estimation by using Kalman filter (KF) augmented with interacting multiple model (IMM) has been examined for the purpose of robust adaptability, which is applied for the first time in wireless communication systems. Such new IMM-KF combination has been facilitated in the feedback channel between wireless transmitter and receiver to adjust the transmitted power, by using a water-filling (WF) technique, and constellation pattern and rate in the ACM algorithm. The AMC has also benefited from such IMM-KF integration to boost the performance against conventional parametric estimation methods such as maximum likelihood estimate (MLE) for channel interrogation and the estimated parameters of both inserted into the ML classification algorithm. Expectation-maximisation (EM) has been applied to examine unknown transmitted modulation sequences and channel parameters in tandem. Finally, the non-parametric multitaper method (MTM) has been thoroughly examined for spectrum estimation (SE) and SS, by relying on Neyman-Pearson (NP) detection principle for hypothesis test, to allow licensed primary users (PUs) to coexist with opportunistic unlicensed secondary users (SUs) in the same frequency bands of interest without harmful effects. The performance of the above newly suggested paradigms have been simulated and assessed under various transmission settings and revealed substantial improvements
Impact of Uncertain Channel Estimation and Outdated Feedback on the Adaptive M-PSK Modulation
This paper investigates an adaptive M-ary phaseshiftkeying (M-PSK) modulation scheme over Rayleigh flatfading channels. The data rate is adapted according to thechannel state. At the receiver, the fading is estimated using pilot symbols. To cancel the channel impact, we correct the received signal by dividing it by the estimated value of the fading. So, we propose to adjust the modulation level by examining the statistics of the corrected signal. In contrast to the previous works on the adaptive M-PSK modulation techniques, our modulation switching protocol takes into account the channel estimation error variance. Moreover, we derive a new closed-form expression for the average bit error rate of the considered system
Radio Communications
In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks