Low complexity ranging algorithm based on TOA for IEEE 802.15.4a system

In this study, a computationally efficient ranging scheme exploiting a minimum mean square error (MMSE) and a matrix-pencil (MP) technique is proposed for the IEEE 802.15.4a chirp spread spectrum (CSS) system. Based on the characteristics of the CSS signal, a practical methodology for the MMSE process is devised and the appropriate values of parameters, which are cutoff bandwidth, number of samples and sampling duration in frequency domain, are investigated and numerically determined to enhance the performance. The performance of proposed scheme is analyzed in terms of the computational complexity and the ranging estimation errors. Simulation results demonstrate that the proposed scheme performs as well as the conventional scheme at remarkably reduced computational costs.

In this thesis, we cope with the fundamental mathematical and physical problems of the space-time-Doppler UWB system design for fading channels: multi-input multi-output (MIMO) wireless communication with adaptive filtering. The estimation algorithm from equalizer providing an accurate parameters estimate is investigated. UWB radio is a fast emerging technology with uniquely attractively features inviting major advances in wireless communications, networking, radar, imaging, and positioning systems. By its rule-making proposal in 2002, the Federal Communications Commission (FCC) in the United States essentially unleashed huge new bandwidth (3.6-10.6 GHz) at the noise floor, where UWB radios overlaying coexistence RF systems cerate using low-power ultra-short information bearing pulses. Right now, there are three basic types of UWB: multiband OFDM UWB (MB-OFDM UWB), impulse-UWB (I-UWB), and direct sequence UWB (DS-UWB). We focus on I-UWB and MB-OFDM-UWB, and compare their performance. A simple means for spreading the spectrum of low duty cycle pulse trains is time hopping (TH), with pulse position modulation (PPM) for data modulation at the rate of many pulses per data bit. The main contribution of this thesis for I-UWB is the design of leading edge detectors, coherent correlation detector (CCD), and pilot performance enhancement compared with different Rayleigh and Ricean fading conditions. For MB-OFDM UWB, we have considered the performance analysis and design criteria of MIMO OFDM UWB systems for high data-rate wireless transmission. The signal processing of frame detection, time synchronization, frequency synchronization, channel estimation, synchronization tracking using pilot subcarriers and 2-D MIMO detection algorithms is discussed. The main contributions of this thesis are 1) Compared with receiver employing the Maximum Likelihood (ML) detector, the receiver employing a low-complexity linear Minimum Mean Square Error (MMSE) demodulator can perform a limited performance loss in spatially uncorrelated channels. 2) Due to the operations of spreading and dispreading combined with MMSE-based frequency domain equalization, the adverse effects of the low-SNR subcarriers on the average BER performance are potentially improved. This is a direct consequence of spreading, because even if the signal corresponding to a specific chip is obliterated by a deep frequency domain channel fade, after dispreading these effects are spread over the Walsh-Hadamard Transform (WHT) length. Hence there is a high chance of still recovering all the partially affected subcarrier symbols without errors. 3) As a test case, the OFDM-based 200 Mb/s MB-UWB network (IEEE 802.15.3a) are considered, but the simulation results are shown above section. 4) The simulation channel can be easily applied to NOS and NLOS situation with WHT transformation from Simulink model. The fading channels of UWB with low/high signal to noise ratio (SNR), multipath effects, and multiuser interference may introduce large errors in location. The location engine performs the following tasks: █ Data fusion techniques: Different data fusion techniques are implemented using Time Of Arrival (TOA), Angle Of Arrival (AOA), or a combination of both. █ Channel modeling: A multipath, multiuser channel environment is created that models path loss, shadowing, Rayleigh fading, and Doppler frequency effects. █ Parameter estimation: TOA and AOA estimation algorithms are implemented as part of the location finding engine. Different variations of algorithms are implemented for performance and comparison purposes. █ Configuring the physical layer for different wireless networks. Among the programmable parameters are spreading factor, packet size, training length, constellation type, modulation technique, carrier frequency, level of transmitted signal power, and the number of antennas at the transmitter for both sides. █ Configuring the mobile user conditions. The wireless channel models depend on the Doppler frequencies present in the environment. The Doppler frequency depends on the mobile speed and carrier frequencies as input and generates a Rayleigh fading channel with the U-shape Doppler spectrum. █ Configuring the environmental parameters and network geographical structure. One of the factors affecting the performance of the wireless location system is the environment type (e.g., bad urban, urban, suburban, or rural area). For example, in a bad urban area with many blocking objects and buildings, non-line of sight (NLOS) effects plays an important role in the estimation accuracy.

Filtered multitone (FMT) modulation divides the communication band into several subbands to shorten the span of symbols affected by multipath in underwater acoustic (UWA) communications. However, there is still intersymbol interference (ISI) in each subband of FMT modulation degrading communication performance. Therefore, ISI suppression techniques must be applied to FMT modulation UWA communications. The suppression performance of traditional adaptive equalization methods often exploited in FMT modulation UWA communications is limited when the effect of ISI spans tens of symbols or large constellation sizes are used. Turbo equalization consisting of adaptive equalization and channel decoding can improve equalization performance through information exchanging and iterative processes. To overcome the shortcoming of traditional minimum mean square error (MMSE) equalization and effectively suppress the ISI with relatively low computation complexity, an FMT modulation UWA communication using low-complexity channel-estimation-based (CE-based) MMSE turbo equalization is proposed in this paper. In the proposed method, turbo equalization is first exploited to suppress the ISI in FMT modulation UWA communications, and the equalizer coefficients of turbo equalization are adjusted using the low-complexity CE-based MMSE algorithm. The proposed method is analyzed in theory and verified by simulation analysis and real data collected in the experiment carried out in a pool with multipath propagation. The results demonstrate that the proposed method can achieve better communication performance with a higher bit rate than the FMT modulation UWA communication using traditional MMSE adaptive equalization.

We introduce a new structured channel impulse response (CIR) estimation method for sparse multipath channels where we demonstrate a robust way of restoring the pulse shape into the composite CIR. We call this novel CIR estimation method time-of-arrival based blended least squares (TOA-BLS) which uses symbol rate sampled signals, and it is based on blending correlation processing followed by TOA estimation in the frequency domain by the least squares based channel estimation. TOA estimation in the frequency domain is accomplished by estimating the AR model parameters by solving the forward and forward-backward linear prediction equations in the least squares sense. Simulation examples are drawn from the ATSC digital TV 8-VSB system (ATSC Digital Television Standard, A/53, 1995). The delay spread for digital TV systems can be as long as several hundred times the symbol duration; however, digital TV channels are sparse where there are only a few dominant multipaths.

Accurate localization has gained significant interest in the field of sensor networks, impulse radio60GHz signals which is low cost, low complexity are even much more practical for ranging, localization and tracking systems because of the high time and multipath resolution and so on. Typically, accurate Time of Arrival (TOA) estimation of the 60GHz signals is very important. In order to improve the precision of the TOA estimation, a new TOA estimation algorithm based on Energy Detector is proposed which is based on a joint metric of the Skewness, Kurtosis, Maximum Slope and Standard Deviation after Energy Detection. The best threshold based on the signal-to-noise ratio (SNR) is investigated and the effects of the integration period and channel model are examined. Simulation results are presented which show that for theIEEE802.15.3c channel models CM1.1 and CM2.1, the proposed algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.

We first develop a reduced-rank minimum mean square error (MMSE) detector for direct-sequence (DS) code division multiple access (CDMA) by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which is obtained from an estimated covariance matrix. Our analysis and simulation results show that when the desired user's signal is in a low-dimensional subspace, there exists an optimal subspace so that the blind reduced-rank MMSE detector lying in this subspace has the best performance. By properly choosing a subspace, we guarantee that the optimal blind reduced-rank MMSE detector is obtained. An adaptive blind reduced-rank MMSE detector, based on a subspace tracking algorithm, is developed. The adaptive blind reduced-rank MMSE detector exhibits superior steady-state performance and fast convergence speed.

This paper investigates low complexity detection for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with co-channel interference (CCI). We firstly derive minimum mean square error (MMSE) detection based on sorted QR decomposition (SQRD) and modified MMSE SQRD detection for MIMO-OFDM systems with CCI. Although better performance can be achieved by the new detectors than liner MMSE (LMMSE) detection, the computational complexity is still high due to the required matrix inversion operation. In order to overcome such an issue and design low complexity detection method for MIMO-OFDM systems with CCI, then, we propose an improved MMSE SQRD detector by utilizing a regularization method. The simplification of the regularization parameter calculation in the proposed method is then discussed. Simulation results show that the error performance of the proposed method approaches modified MMSE SQRD detection in presence of CCI, while keeping a much lower complexity.

The receiver in a wireless communication system has the task of computing good estimates for the data symbols that have been transmitted. The best (optimum) detector is the Maximum Likelihood (ML) detector. However, it requires a high computational complexity. This work aims to efficiently detect the transmitted symbols with a reduced complexity. In order to produce a near optimum receiver, two methods are presented. These methods are obtained by convex optimization relaxations which yield global optimum solutions. The relaxations are combined with the idea of using the structure of the channel matrix to reduce the computational complexity. The channel matrix exhibits a banded Toeplitz structure. In each case, the dual problem of the convex optimization relaxation is solved to estimate the noise power. Gradient descent algorithm is used to solve the dual problem in the first relaxation while the bisection method is applied for the second relaxation. In both cases, the result is a Generalized Minimum Mean Squared Error (GMMSE) detector which has a form similar to the Minimum Mean Square Error (MMSE) detector and a performance almost the same as the MMSE detector, but it is not require the knowledge of the noise power. The GMMSE detectors can be used in scenarios where adapted or blind adaptive detection is not suitable, for instance when the channel is rapidly changing. Using a circular approximation of banded Toeplitz matrix the Fast Fourier Transform (FFT) can be applied to reduce the computational complexity of the detectors. Finally, the local search method is applied to enhance the performance of the proposed GMMSE detector. The proposed detector is a near optimum detector with low computational complexity.

Spatial Modulation (SM) is a recently proposed single-RF multiple-input-multiple-output (MIMO) technique, which is capable of outperforming many conventional MIMO transmission schemes with low implementation and computational complexity. Recently, there have been some attempts in understanding the performance of SM in multi-user environments. However, most of the work has been oriented towards uplink multi-access scenarios. Also, conventional downlink/broadcast MIMO precoding techniques such as Zero Forcing (ZF) or Minimum Mean Square Error (MMSE) cannot be used in Multi-User SM (MU-SM), as part of the data in SM is also encoded into the Channel Impulse Responses (CIRs). In this paper, a novel precoding scheme for single-cell downlink MU-SM systems is proposed with a two-fold objective: i) the precoder needs to be able to completely eliminate the Multi-User Interference (MUI) by taking advantage of the Channel State Information (CSI) at the transmitter and ii) it needs to allow the users to use a single-user Maximum Likelihood (ML) optimum detector while achieving the same performance as interference-free point-to-point SM transmission. Finally, we also develop an interference-aware multi-user detection scheme, which does not require any CSI at the transmitter, and compare its performance with that of single-user detection schemes based on precoding.

In this paper, we investigate link adaption in massive Multiple-Input and Multiple-Output(MIMO) system, where the base station is equipped with a large number of antennas. Specifically for the linear minimum mean square error (MMSE) receiver at the base station, the achievable ergodic rate is used to calculate channel quality indicator (CQI) for each user equipment (UE). We propose a rate calculation method based on the free deterministic equivalent, which relies on the statistical channel state information (CSI). The proposed method has much lower computational complexity than the conventional link adaption method such as exponential effective signal to interference plus noise ratio (SINR) mapping (EESM). Simulation results show that the the spectral efficiency obtained by the proposed method can approach almost the same level as EESM, while much lower computational complexity is needed.

Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007

Interference from unknown devices makes time-of-arrival (ToA) estimation using conventional signal processing methods unreliable. In this paper, we propose new ToA estimation techniques based on Bayesian compressive sensing (BCS) to improve the accuracy of the ToA estimation under the interference scenario. Our proposed BCS based ToA estimation schemes maximize the posterior probability of the channel impulse response (CIR) with given frequency domain received signals. Simulation results show that proposed BCS based ToA estimations exhibit significantly improved ToA detection accuracy and mean-squared error performance in interference scenarios. We also demonstrate a practical example of the ToA estimation using real measured indoor channels.

As the number of antennas increases in multi-input and multi-output (MIMO) systems, even linear detection methods suffer from sharply increasing complexity. This paper proposes a learning-based multi-layer perception (MLP), named dynamic stochastic multi-layer perception (DsMLP), which is implemented by dynamic stochastic computing (DSC). We first establish a similar form between the MLP structure and minimum mean square error (MMSE) matrix operations. Consequently, DsMLP transforms the complex computation problem into an optimization problem of MLP training. Due to the specific design of MLP structure, e.g., same input/output dimension and single layer without activation function, the mathematical representation of DsMLP is identical to the MMSE matrix operations. Therefore, DsMLP guarantees sound model explainability in mathematics, fast convergence in training, and low complexity in computation. Furthermore, we transform the MLP training process to the DSC domain and propose a hardware-efficient scheme for DsMLP. Compared with other state-of-the-art MIMO detectors, DsMLP achieves 1.2× energy efficiency and 1.74× area efficiency.

Currently, most of the researches in molecular communication (MC) domain focus on the static MC scenarios. However, some envisioned important MC applications require mobile MC system. The investigation on mobile MC, especially the signal detection of mobile MC is limited. This work considers the problem of signal detection for mobile MC scenarios where the receiver nano-machine performs random movement. Due to the random movement of the receiver, the channel impulse response (CIR) changes over time which makes the received signal stochastic and complicated. This further complicates the signal detection in mobile MC and leads to that the state-of-the-art signal detection schemes for static MC scenarios fail for the mobile MC scenarios. To solve this issue, an adaptive detection scheme has been proposed by our group previously, based on dynamic estimation of the stochastically varying distance between the transmitter and receiver and the reconstruction of CIR in each interval. However, its computational complexity is high. Limited capability of current nano-machines desire low-complexity detection algorithm. In this work, we further propose an adaptive detection scheme for mobile MC with a low computational complexity by utilizing the local convex property of the CIR. With on-off keying (OOK) modulation, the signal of symbol "1" presents local convex property while that of symbol "0" presents local concave property. The convexity extent varies with the stochastic distance. A simple indicator, local maximum convexity is proposed which adapts to the stochastic distance. By comparing the adaptive indicator with an adaptive threshold within each symbol interval, the signal is detected without the need to estimate the stochastically changing distance or to reconstruct the CIR. Therefore, the computational load is effectively reduced. Numerical simulations are performed to evaluate the proposed scheme. The results show that the proposed scheme achieves good detection accuracy with low computational complexity and it could be a promising detection scheme for mobile MC scenarios.

This paper discusses a cyclic prefixed single carrier frequency-domain equalization (SC-FDE) scheme with two types of transmit diversity. Firstly, we propose a SC-FDE system with space-frequency block coding (SFBC). The transmit sequence of the proposed system is designed to have spatial and frequency diversities, which is equivalent to the SFBC. The corresponding combining receiver is derived under a minimum mean square error (MMSE) criterion. It is shown that the proposed system significantly outperforms the SC-FDE system with space-time block coding (STBC) over fast fading channels, while providing lower computational complexity than orthogonal frequency division multiplexing (OFDM) combined with SFBC. We verify the performance of two-branch transmit diversity systems including the proposed one through bit error rate (BER) analysis. Secondly, as a scheme that combines STBC and SFBC, a space-time-frequency block code (STFBC) SC-FDE system is presented. Computer simulation results show that the proposed STFBC SC-FDE system has better immunity to the distortion caused by both fast fading and severe frequency selective fading, compared to the SC-FDE system with the STBC or the SFBC scheme. Complexity analysis is also conducted to compare their computational loads of the transceiver. It is shown that the proposed STFBC SC-FDE system has lower computational complexity than the STFBC OFDM system.