Multistage decoding-aided channel estimation and equalization for DVB-H in single-frequency networks

For digital terrestrial television broadcasting (DT-TB) systems, orthogonal frequency division multiplexing (OFDM) technique is considered to be an effective method to combat the frequency selective channel cause by multi-path effect. In the single frequency network (SFN) scenario, Alamouti space frequency block coding (SFBC) is introduced to provide spatial diversity gain and improve the link stability. However, both OFDM and Alamouti SFBC are sensitive to time-variant during mobile reception. In this paper, we propose a decision feedback equalization algorithm for inter-carrier interference (ICI) can-celation of the dual (PN) padded time domain synchronization OFDM (TDS-OFDM) DTTB system over doubly selective channel. Our algorithm is proven by numerical simulations which show bit error rate (BER) gain over mobile SFN channel and can be adopted in mobile high density television (HDTV) transmission systems.

Multi-carrier code division multiple access (MC-CDMA)has been considered as a strong candidate for next generation wireless communication system due to its excellent performance in multi-path fading channel and simple receiver structure. However, like all the multi-carrier transmission technologies such as OFDM, the inter-carrier interference (ICI) produced by the frequency offset between the transmitter and receiver local oscillators or by Doppler shift due to high mobility causes significant BER (bit error rate) performance degradation in MC-CDMA system. Many ICI cancellation methods such as windowing and frequency domain coding have been proposed in the literature to cancel ICI and improve the BER performance for multi-carrier transmission technologies. However, existing ICI cancellation methods do not cancel ICI entirely and the BER performance after ICI cancellation is still much worse than the BER performance of original system without ICI. Moreover, popular ICI cancellation methods like ICI self-cancellation reduce ICI at the price of lowering the transmission rate and reducing the bandwidth efficiency. Other frequency-domain coding methods do not reduce the data rate, but produce less reduction in ICI as well. In this paper, we propose a novel ICI cancellation scheme that can eliminate the ICI entirely and offer a MC-CDMA mobile system with the same BER performance of a MC-CDMA system without ICI. More importantly, the proposed ICI cancellation scheme (namely Total ICI Cancellation) does not lower the transmission rate or reduce the bandwidth efficiency. Specifically, by exploiting frequency offset quantization, the proposed scheme takes advantage of the orthogonality of the ICI matrix and offers perfect ICI cancellation and significant BER improvement at linearly growing cost. Simulation results in AWGN channel and multi-path fading channel confirm the excellent performance of the proposed Total ICI Cancellation scheme in the presence of frequency offset or time variations in the channel, outperforming existing ICI cancellation methods.

Orthogonal frequency-division multiplexing (OFDM) is robust against frequency selective fading because of the increase of the symbol duration. However, the time-varying nature of the channel causes inter-carrier interference (ICI) which destroys the orthogonal of sub-carriers and degrades the system performance severely. To alleviate the detrimental effect of ICI, there is a need for ICI mitigation within one OFDM symbol. We propose an iterative Inter-Carrier Interference (ICI) estimation and cancellation technique for OFDM systems based on regularized constrained total least squares. In the proposed scheme, ICI aren’t treated as additional additive white Gaussian noise (AWGN). The effect of Inter-Carrier Interference (ICI) and inter-symbol interference (ISI) on channel estimation is regarded as perturbation of channel. We propose a novel algorithm for channel estimation o based on regularized constrained total least squares. Computer simulations show that significant improvement can be obtained by the proposed scheme in fast fading channels.

In this paper, we propose an enhanced iterative ICI (Inter Carrier Interference) cancellation method for cooperative STBC-OFDM (Space Time Block Coded-Orthogonal Frequency Division Multiplexing) system. In cooperative STBC-OFDM system, ICI cancellation is necessary because ICI due to the independent local oscillators always exits. The conventional iterative ICI cancellation method has severe performance degradation due to the initial estimation error. Also the performance degradation increases as CFOs (Carrier Frequency Offsets) and modulation order increases. Therefore, in this paper, we propose an enhanced iterative ICI cancellation method which can reduce the initial estimation error by giving a priority to initial estimation and cancellation process. Through the complexity and performance comparisons, we verify that the proposed method has better performance with approximately same complexity compared with the conventional method.

In single frequency network (SFN), there exist some special long delay spread channels as well as conventional multi-path channels. For pilot-aided orthogonal frequency division multiplex (OFDM) systems, channel estimation is usually accomplished by interpolation with pilots. However, few pilot subcarriers exist within coherent bandwidth under the long delay spread channels in SFN. In this case, conventional interpolation methods cannot work properly. This paper proposes a sine-wave based frequency domain interpolation method for channel estimation of pilot-aided OFDM systems in SFN. As simulation results show, the proposed method gives accurate channel estimation under the long delay spread channels, whereas the mismatched Wiener interpolation filter (WIF) estimates channel response inaccurately. Moreover, the proposed method performs well under conventional multi-path channels, especially for systems which adopt high order modulations.

Digital terrestrial television systems (DVB-T) using single frequency networks (SFN) based on OFDM modulation schemes have been deployed during the last years. Such SFN topology make it possible to increase the number and quality of services offered due to their more efficient use of the spectrum compared to multiple frequency networks (MFN). Moreover, SFN can cut down on the number of transmitters along with their powers because of the internal gain of the network, saving overall deployment and maintenance costs, and even achieving coverage improvements or a decrease of the outage probability over larger geographical areas through the reuse of frequencies. In this work, an approach to analyze and improve the coverage of a SFN over the most populated regions with the least possible economic investment is proposed, considering several strategies to synchronize and combine the signals at the receiver side and using a hybrid algorithm, mixing up the real and binary versions of the Particle Swarm Optimization algorithm (PSO), to optimize the static delays, gains and orientations for each SFN transmitter and decide whether each sector antenna must be active or not.

For a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, time-varying multipath fading of channel destroys the orthogonality among subcarriers and leads to serious intercarrier interference (ICI). The system performance degrades more severely as normalized Doppler frequency increases. In order to mitigate the effect of time-varying fading, a low-complexity iterative receiver with joint ICI cancellation and pilot-assisted channel estimation is proposed. The initial channel state information (CSI) is estimated by performing time-domain interpolation and least-square (LS) method on the received pilot symbols. The soft outputs are obtained from the decoders after low-complexity linear minimum mean-square error (LC-LMMSE) detection. In the following stages, the soft outputs are feedback to update the CSI estimation. Furthermore, a ¿linear statistics combining¿ (LSC) technique is used to improve the performance of the proposed equalizer by combining the outputs of LC-LMMSE and parallel interference canceler (PIC) with weighting coefficients estimated by maximizing the signal to interference-plus-noise ratio (SINR) at the output of LSC. The complexity of system is significantly reduced by restricting the interference to neighboring subcarriers and employing the LC-LMMSE by limiting the frequency-domain CSI into diagonal region. The simulation results show that the proposed iterative receiver with estimated CSI approaches the ICI-free bound even at very high mobility scenarios.

FD-MC-CDMA is an attractive candidate for next generation high speed aerial vehicle communication for its high spectrum efficiency and excellent BER performance. Similar to other multi-carrier transmission technologies, FD-MC-CDMA suffers significant performance degradation resulting from intercarrier interference (ICI) in high mobility environments. Particularly, because of the ICI is observed from all other subcarriers, the benefit of decomposing subcarriers into non-contiguous sets diminishes. In this paper, we propose a parallel processing based blind frequency offset estimation and ICI cancelation method for FD-MC-CDMA system to significantly improve the BER performance in high mobility environment. Specifically, by exploiting frequency offset quantization, the proposed scheme takes advantage of the orthogonality of the ICI matrix and offers excellent ICI cancelation and significant BER improvement. Moreover, the proposed scheme does not lower the transmission rate or reduce the network capacity. It is important to note that the proposed ICI cancelation scheme maintains the low complexity of optimum multi-user detection (MUD) receiver and achieves the ICI cancelation and excellent BER performance at linearly growing cost. Simulation results in AWGN channel and multi-path fading channel confirm the performance of the proposed scheme in the presence of frequency offset and in mobile channel.

In Single Frequency Networks, the effect of intersymbol interference (ISI) and inter-carrier interference (ICI) is great due to the delay spread of wireless channels is much longer than a cyclic prefix (CP). The performance of OFDM systems is degenerating seriously. This paper discusses a receiver design based on the implementation of a Decision Feed-back Equalizer (DFE). The proposed DFE receiver incorporates a Parallel Interference Canceller (PIC) as its feed-forward filter. The result shows that in long time delay or more serious fading multi-path, the proposed receiver has better performance for canceling ICI and ISI compared with the conventional OFDM receiver.

In this work, the usefulness and limitations of a planning tool that combines a propagation prediction method and a modern heuristic technique when applied to improve the coverage area in single frequency networks (SFN) is presented. The propagation prediction method uses 3D digital terrain maps along with a propagation model to estimate the contribution of any transmitter of the SFN at each location within the region in which the SFN is intended to be deployed, given in terms of parameters such as the received power and propagation delay. Furthermore, a particle swarm optimization (PSO) algorithm is used to optimize the transmission parameters of any of the transmitters within the SFN, including transmitters delay or gain for their sector antennas, in order to exploit the multipath tolerance in OFDM receivers. Preliminary results comparing the performance of different PSO schemes considering as the canonical problem a SFN consisting of eighteen transmitters, in which transmitters and receivers have been simplified, are reported and discussed. Moreover, results considering sector and directive antennas at the transmitter and receiver sides, respectively, are also included.

In SFN (Single Frequency Network) broadcasting systems the equivalent CIR (Channel Impulse Response) can be very long but typically it has a sparse nature. This means that the equivalent CIR has several clusters of paths, each one associated to the CIR between a given transmitter and the receiver. These clusters have several multipath components and are typically well separated in time. In this paper we consider OFDM-based (Orthogonal Frequency Division Multiplexing) broadcasting systems with SFN operation and we propose an efficient channel estimation method that takes advantage of the sparse nature of the equivalent CIR. For this purpose, we employ low-power training sequences and we employ an iterative receiver with joint detection and channel estimation. The receiver can know the location of the different clusters that constitute the overall CIR or not. Our performance results show that we can have excellent performance, close to the performance with perfect channel estimation, even with employ low-power training blocks and also for the case where the receiver does not know the location of the different clusters that constitute the overall CIR.

Single carrier frequency-domain equalization (SC-FDE) modulations are known to be suitable for broadband wireless communications due to their robustness against severe time-dispersion effects and the relatively low envelope fluctuations of the transmitted signals. In this paper, we consider the use of SC-FDE schemes in broadcasting systems. A single frequency network transmission is assumed, and we study the impact of distinct carrier frequency offset (CFO) between the local oscillator at each transmitter and the local oscillator at the receiver. We propose an efficient method for estimating the channel frequency response and CFO associated to each transmitter and propose receiver structures able to compensate the equivalent channel variations due to different CFO for different transmitters. Our performance results show that we can have excellent performance, even when transmitters have substantially different frequency offsets.

Orthogonal frequency division multiplexing (OFDM) is a method suitable for high-rate data transmission in wireline and wireless communications. However, it is very sensitive to frequency offset due to Doppler shifts and carrier synchronization errors. This frequency offset results in inter-carrier interference (ICI) and, as a result, the performance of the OFDM system degrades drastically. Consequently, it, is necessary to remove as many ICI effects as possible to achieve the desired OFDM system performance. Therefore, in this paper, we propose a new method based on a nonlinear adaptive filter to suppress these ICI effects. In addition to showing that the ICI effects can be reduced significantly, the results also demonstrate that the nonlinear filter scheme is superior to the conventional linear filter.

OFDM is a convenient vehicle for high rate transmission. However, this requires an accurate estimation of the channel at the receiver side. This paper proposes an iterative/adaptive algorithm for semi-blind channel estimation. An initial channel estimate is obtained by relying on the artificial constraint of pilots. The algorithm subsequently switches to the blind mode powered by the natural constraints imposed by the sparsity of the channel and the redundant and finite alphabet nature of the data. It iterates between using the channel estimate to detect the data, and using the data estimate to further improve the channel estimate. The diagonal nature of the OFDM channel makes it possible to optimally detect the data with low complexity. The complexity of the algorithm is further reduced by performing channel estimation adaptively. The simulation results demonstrate the favorable behavior of the algorithm and the tradeoff that it provides between the number of pilots used and convergence speed.

This paper addresses the effective sparse channel estimation based on the most significant taps (MST) selection with high spectral efficiency and moderate computational complexity for orthogonal frequency division multiplexing (OFDM) systems. The main goal of this paper is to obtain an efficient time domain threshold and achieve the channel estimation performance approaching the least squares (LS) method with exact sparsity (exact number of non-zero channel taps) without using prior knowledge of both channel statistics and noise standard deviation. Firstly, classical LS method is used to get an initial channel impulse response (CIR) estimate. Then a novel effective threshold, estimated from the noise coefficients of the initial estimated CIR, is proposed. Finally, the obtained threshold is used to select the most significant taps. Simulations show that the proposed method is able to achieve good channel estimation performances for sparse channel within a comparatively wide range of sparsity with small number of pilots and moderate computational complexity.