Channel Estimation

Cognitive radio has the ability to sense the environment and adapt its behavior to optimize communication features, such as quality of service in the presence of interference and noise. In physical layer to achieve this goal, different phases of sensing, channel estimation, and configuration selection are necessary. The sensing part measures the interference level, recognize the spectrum holes, and send this information to channel estimator. In the next step, channel state information (CSI) is used for data detection and also sent to the transmitter through a limited feedback. CSI feedback consists of achievable rate, SNR value, modulation or coding schemes (MCS). Feedback link improves the system performance in the cost of complexity and delay. In this paper, we present and compare different feedback schemes for cognitive radio and study the channel capacity when an imperfect feedback link is corrupted by noise and delay.

This paper discusses the design and implementation of frequency offset estimation algorithms for DOCSIS upstream channels. A cost-effective estimator which approaches the Cramer-Rao bound for high SNRs is derived. The effect of ISI generated by upstream micro-reflections in typical cable networks is considered, and a condition upon the transmitted preamble sequence which guarantees unbiased estimation is presented. It is shown

In this study, a model based on the generalised-K (GK) distribution is proposed for identifying ultra-wideband (UWB) indoor channel profiles. In particular, an index (y-index) based on a proper combination of GK parameters is proposed to unambiguously and effectively distinguish among line-of-sight (LOS) and non-LOS propagation conditions. This clear distinction is achieved by defining two non-overlapping sets which correspond to the two well-defined profiles. The technique is user-friendly since it does not call for any complex estimation process. Comparison among the results achieved by both real measurements and IEEE.802.15.4a channel model simulations confirm the soundness of the employed method and the effectiveness of the proposed y-index.

In this paper, we propose a method for user selection and channel estimation for the multiple-input multiple-output (MIMO) broadcast channel for the downlink of a cellular mobile or local-area wireless communication system.A distributed self-selection procedure is combined with a code-division multiple access (CDMA) uplink signaling strategy to reduce the uplink signaling bandwidth, and the computational complexity of user selection at the base station. We exploit recent advances in sparse signal recovery, which we apply to the uplink multi-user detection and channel estimation problems to reduce the signaling bandwidth. We establish that full channel state information (and not just channel quality) for each self-selecting user can be obtained at the base station via a compressed-sensing technique with no increase in overhead for the uplink feedback channel. We demonstrate the new method as a medium access technique for MIMO downlink broadcast with transmitter precoding and linear receiver processing.

The high data transmission rates in the communication channel is a recent growing demand which is achieved by using the multiple input multiple output systems because of their unique properties.. The OFDM systems that adopt the cyclic require only one inverse discrete Fourier transform (IDFT) operation at the low-complexity by means of increasing the transmission diversity in MIMO pilot sequences which minimize the mean square error (MSE) of the channel estimate in traditional MIMO systems are inapplicable to CDD minimum MSE of both the least square (LS) channel estimate and the MMSE channel estimate in CDD systems. The derived criteria are then used to develop a general methodology for determining the sequence. Significantly, the proposed design methodology enables the status of the channel to be estimated using single OFDM symbol. We have compared the performances of channel estimation algorithm by measuring bit error rate vs. SNR with BPSK, QPSK 16

This paper deals with the robust minimum mean square error
(MMSE) channel estimation for LTE (Long Term Evolution)
downlink OFDM (Orthogonal Frequency Division Multiplexing)
system over time varying mobile environments. Recently robust
estimators are proposed for OFDM systems with block type pilot
structure. These estimators do not require channel correlation
functions for estimation and give robust performance independent
of actual power delay profile (PDP). However, LTE pilot structure
is a combination of both block type and comb type pilot structure.
Hence, there is a need to develop a channel estimator giving robust
performance for LTE system. This allows the system to be
deployed in rural areas having complex mobile environment such
as more mud houses and dense trees. The mean square error
(MSE) performance of the proposed estimator is analyzed with
various power delay profiles applicable to LTE systems. Analytical
expressions are derived for MSE and it is verified that both
analytical and simulation results are exactly matching.

Major river valleys (e.g. Ganga, Brahmaputra, Narmada, Godavari, Kosi etc.) of India have remained as cradles of human livelihood and achievements throughout the course of human history. In the same way, contributing with floods the Damodar valley of eastern India is nurturing its civilization in different phases through almost 3,500 year. Documented history of ruinous extreme floods is more than 347 years old (1665 – 2012) in the Damodar River. It is true that when this river is in the extreme phase, none can withstand against its power. Still we are not now fully capable to manage the adamant nature of river particularly in the monsoon period. Simultaneously the uncertain event, e.g. cloud burst, heavy monsoon rainfall and cyclones etc., and resultant flash floods are not forecast accurately. As the catchment of Damodar has good physiographic and hydro-meteorological potentiality of floods, it is imperative to know the current status of flood probability and risk. So here an attempt is made to investigate the temporal variation (i.e. natural phase – without dams and controlled phase – with dams) of annual peak flows understanding the dam induced flood hydrological changes in the Damodar River. Using the quantitative techniques, viz., Flood Potential Index (FPI), Flash Flood Magnitude Index (FFMI) and Flood Frequency Analysis (FFA), the magnitude of flash floods and channel dimensions are analyzed to derive significant explanation and prediction about the flood risk in the lower segment of Damodar River.

Underwater communication is one of the challenging fields in communication engineering with wired and wireless communication. In underwater communication there are several possibilities for mitigating terrestrial communication limitations. Familiar methods for underwater communication are using radio waves, optical fibers and acoustic waves. Limitation of short distance range of communication with RF and fiber, low frequency sound waves are used here as the medium and also acoustic waves are capable of withstanding ambient noises and vibrations in water.
This project intend to the design of an underwater acoustic communication system. For an underwater communication cost is not a factor for initial deployment of the system as the frequent maintenance is not practically possible. To design a reliable communication system the main aims are long distance, secure and accurate. Here such a system is selected as existing system and it is analyzed. An amplifier and forward relay assisted system is considered as the existing system to study about underwater acoustic communication system in detail for designing a reliable system. One of the specialty of this paper is it covers almost all fields in communication engineering, especially signal processing, wireless communication, estimation and detection, etc.
The main focus of this paper is sparse channel estimation and equalization with AF relaying for underwater cooperative systems based on OFDM. For the channel estimation Matching Pursuit (MP) algorithm is used in combination with maximum a posteriori probability (MAP) based SAGE technique. This algorithm is low complex for good performance channel estimation and it will provide a better symbol error rate and can overcome the mismatching effects of Doppler shift. In simulation results for CGM-MP-SAGE algorithm, Doppler effects and multipath system for BPSK modulation are analyzed in terms of SER performance and average MSE based on SNR values. This system has a poor reliability in terms of practical implementation. Thus a new system is proposed to compensate the drawbacks and for practical implementation. Some reliable approaches can be used by including different ideas such as compress and forward relay can be used to increase the data rate and avoiding error, instead of AF relaying. For frequency and time analyzing pilot based estimation with PN sequence can be used.
In addition to this for providing high diversity MIMO system can be integrated. Zero force equalizer can be provided and adaptive filter is used for equalization, here RLS filter is used to avoid interferences. For the removal of channel error and burst error, a channel encoder and interleaver is used respectively. More important a fast converging estimation technique is used instead of MAP is MMSE. Minimum mean square error estimation is used, as it is suitable for practical deployment in underwater with excellent SNR performance results than MP-SAGE algorithm.
As UWAC system has to suffer from fading, interferences and noises, the system should design in such a way that to compensate these problems. So interference alignment is included to improve capacity, power allocation is provided with SVD and DPC algorithms for separate SNR regions. When the energy efficiency is maximized, the capacity of the system increases. For high SNR singular value decomposition is used with water filling power adaptation algorithm and EE is optimized. The optimization of EE and power allocation is easy to implement as noise and interference is less.
For moderate SNR regions, the power is less so by using DPC algorithm the distorted or low power signal at receiver can be boosted so power can increased and thereby energy efficiency get maximized. This work introduces a design for reliable underwater communication system using acoustic waves is implementing with CGM-MP-MMSE estimation and the capacity of the system is improving for variable SNR regions with SVD and DPC algorithms.

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The Chinese digital television terrestrial broadcasting (DTTB) standard uses pseudo-noise (PN) sequence as guard interval (GI) and the training sequence. This PN sequence is used to do channel estimation and synchronization in the system. The existing channel estimation methods often have to adopt iterative scheme when the length of channel impulse response (CIR) is long, which will increase the receiver complexity dramatically. In this paper, a channel estimation scheme for time domain synchronous OFDM (TDS-OFDM) systems is proposed. Interference free CIR information can be obtained by constructing special correlation windows, rather than removing interference from the time domain sequences through iteration. Moreover, the estimation can be achieved by using correlation process. Comparing to conventional schemes, the proposed algorithm greatly reduces the computational complexity. Simulation results show that the proposed method can meet the requirement of the Chinese DTTB systems. And the scheme is also suitable for other communication OFDM systems with time domain sequence headers.

Severe tropical weather dynamics impairments on the earth-sky signal quality at the Ku-band relative to temperate weather increase the demand for land mobile satellite (LMS) channel characterization and modeling specific to tropical regions. Variation in weather dynamics decreases the accuracy of the existing LMS channel models if applied to the tropics. This paper presents a tropical weather-aware LMS channel model that can be applied at areas with diverse atmospheric (rain, clouds, and tropospheric scintillation) and mobility impairments. The proposed tropical-LMS channel (TRO-LMSC) model is designed based on actual experimental measurements conducted in a tropical area. The TRO-LMSC model involves multipath design, mobility model, rain impairment model, cloud impairment model, tropospheric scintillation model, and link budget module (LBM). The proposed model shows improved channel modeling accuracy and comprehensiveness with relatively less root mean square error (rmse), compared with existing models. Consequently, this improvement enhances the identification of the type and performance of the fade mitigation technique, the management of available communication resources, and the reliability and efficiency of the communication services.

Performance of pilot-aided channel estimation
techniques such as the Least Squares (LS) method depends on
not only on the signal-to-noise ratio (SNR), channel conditions
and pilot ratio, but also on the choice of interpolation method
for deriving channel estimates at non-pilot subcarriers. This
paper investigates the bit-error-rate (BER) performance of
linear, spline and Piecewise Cubic Hermite Interpolating
Polynomial (PCHIP) interpolation methods in LS channel
estimation over the three extended ITU channel profiles defined
for Long Term Evolution (LTE) testing. Simulation results
show that applying the linear interpolation method produces
the best BER performance over the fading channel with the
smallest multipath delay spread. It is also shown that the choice
of best interpolation method actually depends on the SNR in
some of the fading channel profiles.

A combination of multiple-input multiple-output (MIMO) systems and orthogonal frequency division multiplexing (OFDM) technologies can be employed in modern wireless communication systems to achieve high data rates and improved spectrum efficiency. For multiple input multiple output (MIMO) systems, this paper provides a Rayleigh fading channel estimation technique based on pilot carriers. The channel is estimated using traditional Least Square (LS) and Minimum Mean Square (MMSE) estimation techniques. The MIMO-OFDM system's performance is measured using the Bit Error Rate (BER) and Mean Square Error (MSE) levels.