Time-varying Frequency-selective Channels Research Articles

Multi-antenna GFDM for resilient decentralized communications

Owing to the superior performance of generalized frequency division multiplexing (GFDM), in terms of enhanced spectral efficiency and lower out-of-band radiations, it is considered as a potential replacement of traditional orthogonal frequency division multiplexing (OFDM) for next generation wireless communication systems. However, non-orthogonal pulse shaping in GFDM gives rise to intrinsic self-interference complicating the receiver design. Moreover, its extension to multi-input multi-output (MIMO) designs for spatial diversity and enhanced reliability is also not straightforward as overlapping of transmitted symbols in time and frequency hinders the extension of conventional diversity techniques to MIMO GFDM. In this work, we consider a multi-antenna GFDM decentralized communication system and present a generic framework to achieve spatial transmit diversity along with a low complexity transceiver design. We extend our proposal by presenting a novel multi-antenna preamble that helps not only in acquisition of robust time and frequency synchronization but also in reliable estimation of time-varying frequency selective channels. Performance evaluation over realistic 3GPP simulation scenarios, confirms the attainment of full diversity order along with superior preamble-based time–frequency synchronization and channel estimation performance as compared to state of the art.

Channel Estimator Time Varying Frequency Selective Channel by Deeplearning

Channel Estimator Time Varying Frequency Selective Channel by Deeplearning

Maximum likelihood-based adaptive iteration algorithm design for joint CFO and channel estimation in MIMO-OFDM systems

In this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) systems for mobile users. The signal model of the MIMO-OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. The computational complexity of the proposed algorithm is considerably lower than that of the maximum likelihood-based grid search method. In a simulation, the mean squared error performance of the proposed algorithm was close to the Cramer-Rao lower bound. The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. The results also suggest that the proposed method has reliable tracking performance in Jakes’ channel models.

Comparing the performance of OFDM and FBMC multicarrier systems in doubly-dispersive wireless channels

In mobile communications, the most widely used multicarrier technique, namely OFDM, is known to exhibit performance limitations in high speed scenarios. FBMC is an alternative approach and, among FBMC techniques, the recently introduced FBMC-PAM scheme has emerged as the most robust to CFO. Therefore, it is chosen here as the challenger of OFDM for performance comparison in doubly dispersive channels. After presentation of the system model, multicarrier scheme and wireless channel, an analytical evaluation of the BER in the particular case of single path time-varying channel is provided for FBMC-PAM and validated through simulations. Then, simulation results are reported for both OFDM and FBMC-PAM, using the 3GPP multipath channel models. It appears that FBMC-PAM can outperform OFDM in highly time-varying frequency-selective channels.

Sparse Doubly-Selective Channel Estimation Techniques for OSTBC MIMO-OFDM Systems: A Hierarchical Bayesian Kalman Filter Based Approach

Hierarchical Bayesian Kalman filter (HBKF) based schemes are conceived for doubly-selective sparse channel estimation in orthogonal space-time block coded (OSTBC) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless systems. Initially, a pilot based multiple measurement vector (MMV) model is formulated for estimating the OSTBC MIMO-OFDM channel. This is followed by the development of a low-complexity, online pilot-based HBKF (P-HBKF) scheme for tracking the sparse time-varying frequency-selective channel. The salient advantages of the proposed P-HBKF technique are that it requires significantly lower number of pilot subcarriers, while also exploiting the inherent sparsity of the wireless channel. Subsequently, data detection is also incorporated in the proposed framework, leading to the development of a procedure for joint sparse doubly-selective channel estimation and symbol detection. Recursive Bayesian Cramér-Rao bounds and closed form expressions are also obtained for the asymptotic mean square error (MSE) based on the solution of the Riccati equation for the KF for benchmarking the performance. Simulation results are presented for validating the theoretical bounds and for comparing the performance of the proposed and existing techniques.

Energy efficient VLSI decoder chip with reduced PAPR in FECG monitoring

ABSTRACT Medical data transmission is a major challenge in wireless communication to preserve their integrity and coherence. Orthogonal frequency division multiplexing (OFDM) has emerged as a modulation scheme that can achieve high data rates over frequency selective fading channel by multipath effects. As the foetal ECG (FECG) signal is large to process, the dimensionality of the data is reduced by linear discriminant analysis (LDA) and is then sent through the space time block coded (STBC) multiple input multiple output (MIMO) upon using cockroach swarm pptimisation algorithm as a classifier to demarcate the FECG signal from noise. This paper also proposes decoder design for STBC transmission over frequency-selective time-variant channels with data recovery at the receiver by using proposed error prediction and correction adders (EPD) to achieve reduced peak to average power ration (PAPR). The simulation results prove that the PAPR reduces by 1.3 dB and the sensitivity of classifier is 96.4%. The implementations are carried out over 200 data sets taken from MIT-BIH arrhythmia using simulation tools such as MATLAB 2013b, ModelSim 10.0b and Cadence Virtuoso under 65 nm. The finally fabricated and tested decoder chip consumes an average power of 0.64 µW.

Spatial Channel Covariance Estimation for Hybrid Architectures Based on Tensor Decompositions

Spatial channel covariance information can replace full instantaneous channel state information for the analog precoder design in hybrid analog/digital architectures. Obtaining spatial channel covariance estimation, however, is challenging in the hybrid structure due to the use of fewer radio frequency (RF) chains than the number of antennas. In this paper, we propose a spatial channel covariance estimation method based on higher-order tensor decomposition for spatially sparse time-varying frequency-selective channels. The proposed method leverages the fact that the channel can be represented as a low-rank higher-order tensor. We also derive the Cramer-Rao lower bound on the estimation accuracy of the proposed method. Numerical results and theoretical analysis show that the proposed tensor-based approach achieves higher estimation accuracy in comparison with prior compressive-sensing-based approaches or conventional angle-of-arrival estimation approaches.

ML-Type EM-Based Estimation of Fast Time-Varying Frequency-Selective Channels Over SIMO OFDM Transmissions

This paper investigates the problem of fast time-varying frequency-selective (i.e., multipath) channel estimation over single-input multiple-output orthogonal frequency-division multiplexing (SIMO OFDM)-type transmissions. We do so by tracking the variations of each complex gain coefficient using a polynomial-in-time expansion. To that end, we derive the log-likelihood function (LLF) both in the data-aided (DA) and non-data-aided (NDA) cases. The DA maximum likelihood (ML) estimates over fast SIMO OFDM channels are derived here for the first time in closed-form expressions and hereby shown to be limited to applying over each receive antenna the DA least squares (LS) estimator tailored in [1] to fast SISO OFDM channels. This DA ML is used to initialize periodically, over a relatively large number of data blocks (i.e., with further reduced and relatively close-to-negligible pilot overhead compared to DA ML), a new expectation maximization (EM) ML-type solution we developed here in the NDA case to iteratively maximize the LLF. We also introduce an alternative regularized DA ML (RDM) initialization solution no longer requesting - in contrast to DA ML - more per-carrier pilot frames than the number of paths to further reduce overhead without incurring significant performance losses. Simulation results show that the proposed hybrid ML-EM estimator (i.e., combines all new NDA ML-EM and DA ML or RDM versions) converges within few iterations, thereby providing very accurate estimates of all multipath channel gains. Most importantly, this increased estimation accuracy translates into very significant BER and link-level per-carrier throughput gains over the best representative benchmark solution available so far for the problem at hand, the SISO DA LS technique in [1] with its new generalization here to SIMO systems.

Angle-Domain Approach for Parameter Estimation in High-Mobility OFDM With Fully/Partly Calibrated Massive ULA

In this paper, we consider a downlink orthogonal frequency division multiplexing (OFDM) system from a base station to a high-speed train (HST) equipped with fully/partly calibrated massive uniform linear antenna-array (ULA) in wireless environments with abundant scatterers. Multiple Doppler frequency offsets (DFOs) stemming from intensive propagation paths together with transceiver oscillator frequency offset (OFO) result in a fast time-varying frequency-selective channel. We develop an angle domain carrier frequency offset (CFO, general designation for DFO and OFO) estimation approach. A high-resolution beamforming network is designed to separate different DFOs into a set of parallel branches in angle domain such that each branch is mainly affected by a single dominant DFO. Then, a joint estimation algorithm for both maximum DFO and OFO is developed for fully calibrated ULA. Next, its estimation mean square error (MSE) performance is analyzed under inter-subarray mismatches. To mitigate the detrimental effects of inter-subarray mismatches, we introduce a calibration-oriented beamforming parameter (COBP) and develop the corresponding modified joint estimation algorithm for partly calibrated ULA. Moreover, the Cramer-Rao lower bound of CFO estimation is derived. Both theoretical and numerical results are provided to corroborate the proposed method.

A complete cell search and synchronization in LTE

The initial process of identifying any available base station (BS) by a user equipment (UE) that wants to communicate is termed as cell search. To ensure a reliable communication, any UE has to be synchronized with the BS both in time and frequency domains. Cell search process is said to be complete once cell ID associated with long-term evolution (LTE) BS is decoded successfully. This paper presents a series of cell search and synchronization algorithms, which efficiently estimated time and frequency offsets as well as cell ID. The synchronization signals present in LTE, namely, primary synchronization signal (PSS) and secondary synchronization signal, that carry cell ID are critically exploited in the algorithms. The aforementioned algorithms are classified into two modules, namely, module I and module II, based on their computation complexity.In module I, a cyclic prefix (CP)-based maximum likelihood (ML) estimator is employed to obtain a coarse estimate of time and fractional frequency offset; however, the estimates are refined using synchronization signals. A joint estimation of timing, integer frequency offset (IFO), and PSS ID (sector ID) is carried out in module II. Both the modules operate on the cross-correlation approach of PSS with the received signal for obtaining timing and sector ID. IFO as a part of module II is detected from a finite hypotheses set using synchronization signals. Extensive simulations are carried out on a time-varying frequency-selective channel to analyze the performance of the algorithms.

An Efficient Practical MIMO–OFDM Scheme with Coded Modulation Diversity for Future Wireless Communications

An efficient coded modulation diversity scheme is proposed to improve the performance of multiple-input-multiple-output orthogonal-frequency-division-multiplexing (MIMO---OFDM) systems in frequency-selective time-varying fading channels. By introducing the rotated modulation and space-time-frequency component interleavers, the proposed scheme globally optimizes powerful forward error correction codes, rotated quadrature amplitude modulation, linear precoding MIMO, and OFDM, thus can achieve modulation diversity and space-time-frequency diversities as much as possible. A simple efficient optimal precoder selection criterion is put forward for this scheme. Based on the analysis of average mutual information, optimal rotation angles are given for different modulation and coding schemes, and the superiority of the proposed scheme is proved. Both software simulation and hardware prototype test results also verify that this new scheme can significantly outperform the conventional bit-interleaved coded modulation scheme under the non-ideal channel estimation, which is up to 4.5 dB signal-to-noise-ratio gain. In a word, the proposed scheme is a simple, efficient and robust transmission technique for the future MIMO---OFDM wireless systems.

Generalized spatial representation for digital modulation and its potential application

Constellation mapping has provided a great convenience to measure the performance of digital signal modulation in Euclid space. However, traditional in-phase and quadrature (IQ) plane is difficult to express the frequency modulation scheme such as minimum shift keying (MSK) and the time domain modulation such as cyclic code shift keying (CCSK). How to represent the digital signal modulation visually through constellation mapping is an attractive problem. To address this issue, in this paper, the combined frequency and phase modulation are utilized to define a new kind of constellation mapping, where the phase and frequency are quantized to the same elements. The uniform geometric construction for combined phase and frequency modulation is redefined in the 3D cylindrical coordinate system based on frequency (f), in-phase component (I) and quadrature component (Q). In the new coordinates, the quadrature frequency-phase shift keying (QFPSK) is produced by the QPSK with dimensional rotation matrix and denoted by the reduced dual quaternion. Furthermore, the spatial extension from QFPSK to chirp cyclic shift keying (Chirp CSK) is analyzed with bandwidth efficiency and energy efficiency. At last, the QFPSK is combined with the 2D OFDM, yielding the image OFDM system. Experimental results verify the effectiveness of QFPSK in the proposed system with the time-varying wireless channel and frequency selective fading channel respectively.

Frequency-Shift Offset-QAM for GFDM

This paper presents a novel perspective to apply the offset quadrature amplitude modulation (OQAM) scheme on top of the multicarrier waveform termed Generalized Frequency Division Multiplexing (GFDM). The conventional time-shift OQAM is described for GFDM and, with the introducing of the general use of unitary transform, an interesting counterpart, i.e., frequency-shift OQAM, is proposed. The conventional long prototype pulse with time-shift of one half subsymbol becomes a short prototype pulse with frequency-shift of one half subcarrier. The frequency-shift OQAM scheme offers advantages such as low out-of-band emission and low implementation complexity. The concept can be applied to the broader scope of filtered OFDM without penalties in terms of performance in time variant frequency-selective channels.

Multi-user time-reversal STC-GFDMA for future wireless networks

The challenges of future wireless networks imply that the physical layer of the next generation mobile communication system needs to be compatible with multiple-input multiple-output and allow a flexible multiple access scheme. Time-reversal space-time coding can be applied to a recent filtered multicarrier modulation scheme, named generalized frequency division multiplexing, to achieve a multiple-input multiple-output non-orthogonal multicarrier modulation with flexibility to address the requirements of future mobile networks. In this paper, the subcarriers of the physical layer block are shared between multiple users, allowing for an efficient and simple multiple access solution. A channel estimation technique that can simultaneously estimate channel frequency response and timing misalignment in generalized frequency division multiple access is described. The paper also shows that the knowledge of channel state information can improve the overall performance when used to schedule the subchannel distribution among the users. Symbol error rate performance analysis shows that the resources of the time-reversal space-time coding generalized frequency division multiple access block can be shared among users that have one or two transmit antennas simultaneously under frequency-selective time-variant channels.

Precoding based on Signal-to-leakage and Noise Ratio to Reduce ICI in MIMO-OFDM Systems

Current trends in the development of high-data-rate wireless systems focus on the integration of orthogonal frequencydivision multiplexing (OFDM) and multiple-input?multiple-output (MIMO).The combination of OFDM and the Multiple-InputMultiple-Output (MIMO) technique represents a promising candidate for future broadband wireless systems. This paper addresses the Inter Carrier Interference (ICI) issue in multiuser MIMO-OFDM systems operating in time-varying frequency selective channel environments.In our proposed method precoding based on signal-to-leakage-and-noise ratio (SLNR) is considered.In this paper model using precoding in MIMOOFDM is introduced.Based on the model algorithm for precoding matrix is developed.Simulation results confirms reduction in ICI without increasing complexity of a system.

Minimizing Base Station Power Consumption

We propose a new radio resource management algorithm which aims at minimizing the base station supply power consumption for multi-user MIMO-OFDM. Given a base station power model that establishes a relation between the RF transmit power and the supply power consumption, the algorithm optimizes the trade-off between three basic power-saving mechanisms: antenna adaptation, power control and discontinuous transmission. The algorithm comprises two steps: a) the first step estimates sleep mode duration, resource shares and antenna configuration based on average channel conditions and b) the second step exploits instantaneous channel knowledge at the transmitter for frequency selective time-variant channels. The proposed algorithm finds the number of transmit antennas, the RF transmission power per resource unit and spatial channel, the number of discontinuous transmission time slots, and the multi-user resource allocation, such that supply power consumption is minimized. Simulation results indicate that the proposed algorithm is capable of reducing the supply power consumption by between 25% and 40%, dependend on the system load.

Iterative Soft-Kalman Channel Estimation for Fast Time-Varying MIMO-OFDM Channels

This letter addresses the problem of channel estimation in fast time-varying frequency selective channels. Considering orthogonal frequency division multiplexing in a multiple-input multiple-output system, we perform soft-Kalman filtering for channel estimation in conjunction with soft-interference canceling at the receiver to reduce the inter-carrier interference. We also propose two simplified implementations of the soft-Kalman filter for the case of constant-modulus signal constellations that allow considerable reductions in the receiver computational complexity, while performing more or less closely to the exact soft-Kalman estimator, depending on channel conditions. For non-constant-modulus signal constellations, however, the exact formulation of the soft-Kalman filter should be used.

Analyses and Performance of Techniques PAPR Reduction for STBC MIMO-OFDM System in (4G) Wireless Communication

An OFDM system is combined with multiple-input multiple-output (MIMO) in order to increase the diversity gain and system capacity over the time variant frequency-selective channels. However, a major drawback of MIMO-OFDM system is that the transmitted signals on different antennas might exhibit high peak-to-average power ratio (PAPR).In this paper, we present a PAPR analysis reduction of space-timeblock-coded (STBC) MIMO-OFDM system for 4G wireless networks. Several techniques have been used to reduce the PAPR of the (STBC) MIMOOFDM system: clipping and filtering, partial transmit sequence (PTS) and selected mapping (SLM). Simulation results show that clipping and filtering provides a better PAPR reduction than the others methods and only SLM technique conserve the PAPR reduction in reception part of signal.

Performance analysis of OFDM system with transmit antenna selection using delayed feedback

We consider orthogonal frequency division multiplexing (OFDM) in a multiple input single output (MISO) system. In the presence of spatially uncorrelated time-varying frequency selective channel, we use subcarrier by subcarrier antenna selection using delayed feedback. We derive closed-form expressions for the pdf of the received SNR and BER for MQAM constellation. The expressions have been obtained as a function of the correlation (ρ) between perfect channel state information (CSI) and delayed CSI, where 0≤ρ≤1. We have verified our analytical expressions by comparing them with simulation results. We have also reduced the BER expression for some special cases and compared them with the results available in the literature. We conclude that the diversity gain of the considered system is reduced to one for ρ<1, i.e. not having perfect antenna selection for each subcarrier. However, we get some coding gain compared to single input single output system, the coding gain reduces with decreasing the correlation.

Joint channel and phase noise estimation in OFDM systems at very high speeds

In this paper, the problem of joint phase noise and channel estimation for OFDM systems over a fast time-varying frequency-selective channel is explored. Each channel tap time-variation within one OFDM symbol is approximated by a Basis Expansion Model (BEM). Joint estimation is performed on multiple OFDM symbols via the Extended Kalman Filtering in order to exploit the time-correlation of the parameters. The data symbols are estimated by means of an iterative pilot-based algorithm. It is shown that, with only 2 iterations, our algorithm outperforms the conventional one, and the performance approaches that of the ideal case for which the channel response and phase noise are known.