Shouyin Liu

A study of joint tracking algorithms of carrier frequency offset and sampling clock offset for OFDM-based WLANs

We present three joint tracking algorithms of carrier frequency and sampling clock offsets for OFDM-based WLAN systems, such as IEEE 802.11a standard. In such systems, one symbol usually contains a few pilots so that the estimation accuracy and robustness of conventional methods do not satisfy the system requirement. In this paper, three joint tracking algorithms for accurate frequency and sampling estimation are presented. The first method is performed by a one-dimensional least square estimation and averaging over L symbols. The second algorithm compares the phase difference of the current symbol with the subsequent D-th symbol and gives better performance, especially when the SNR or synchronization offset is smaller. The third method uses two-dimensional linear least square estimation within the frequency and time domains. Simulations using these algorithms have been performed with 16-QAM modulation schemes. Simulation results show that the three algorithms can improve the estimation accuracy and robustness.

The MMSE Channel Estimation Based on DFT for OFDM System

The minimum mean-square error (MMSE) channel estimation has well performance but higher complexity than least-square (LS) channel estimation, specially it requires the channel statistical properties including the channel autocorrelation matrix and the noise variance. However, it is difficult to obtain the channel statistical properties in practice. In this paper, through the DFT based estimator, in time domain, the noise variance can be estimated, and the channel autocorrelation matrix is also obtained by using the noise suppressed channel impulse response. Then the MMSE channel estimation for OFDM system is realized. Simulation results demonstrate that the performance is better than the DFT based estimator and closed to the ideal MMSE estimator.

Exact BER Expression for Alamouti Scheme with Joint Transmit and Receive Antenna Selection

In this paper, we propose a simple joint transmit and receive antenna selection algorithm based on maximizing the instantaneous signal to noise ratio (SNR) over uncorrelated Rayleigh fading channels in multi-input multi-output (MIMO) systems. For a special case that two transmit antennas and one receive antenna are selected, while Alamouti scheme is employed, the exact bit error rate (BER) expression for binary phase shift keying (BPSK) is derived. The analytical results are exactly verified by the simulations.

Improved Localization Algorithms Based on Reference Selection of Linear Least Squares in LOS and NLOS Environments

Linear Least Squares (LLS) estimation is a low complexity but sub-optimum method for estimating the location of a mobile terminal (MT) from some measured distances. It requires selecting one of the known fixed terminals (FTs) as a reference FT for obtaining a linear set of expressions. In this paper, the choosing of the reference FT is investigated. By analyzing the objective function of LLS algorithm, a new method for selecting the reference FT is proposed, which selects the reference FT based on the minimum residual (denoted as MR-RS) rather than the smallest measured distance and improves the localization accuracy significantly in Line of sight (LOS) environment. In Non-line of sight (NLOS) environment, we combine MR-RS algorithm with two other existing algorithms (residual weighting algorithm and three-stage algorithm) to form new algorithms, which also improve the localization accuracy comparing with the two algorithms. Moreover, the time complexity of the proposed algorithms is analyzed. Simulation results show that the proposed methods are always better than the existing methods for arbitrary geometry position of the MT and the LOS/NLOS conditions.

A Novel Dynamic Full Frequency Reuse Scheme in OFDMA Cellular Relay Networks

In this paper, a novel dynamic full frequency reuse scheme is proposed to improve the spectral efficiency in orthogonal frequency division multiple access (OFDMA) cellular relay networks. Different from the conventional full frequency reuse scheme which only allows the base station (BS) reusing the subcarriers in the specific regions, we proposed an improved full frequency reuse scheme to allow the BS reusing all the subcarriers in the whole BS coverage region to exploit more multiuser diversity gain. In order to dynamically reuse the frequency resource among the BS and relay stations (RSs) to further improve the spectral efficiency, the adaptive subcarrier scheduling is introduced into the improved full frequency reuse scheme, which forms the proposed novel dynamic full frequency reuse scheme. Simulation results show that the proposed scheme can obtain high spectral efficiency, fine fairness and low outage probability.

Channel Estimation for OFDM Systems Based on RLS and Superimposed Training Sequences

The recursive least squares (RLS) algorithm and the superimposed training sequences are applied to the orthogonal frequency division multiplexing (OFDM) systems to estimate channel state information (CSI). In order to reduce the interference caused by the unknown information data that is added with the superimposed training sequences, we present the following method: first, the information data are detected using the CSI of the previous one block, and then subtracted them from the current received signals. Second, the remainder signals mainly including the training sequence are used to estimate CSI. For decreasing the computation complexity, we use the same training sequence in all OFDM blocks. The computation complexity and the mean square error (MSE) performance of our proposed RLS method are compared with the original RLS method.

Improved design criterion for space-frequency trellis codes in MIMO-OFDM systems

In this paper, the design problem and the robustness of space-frequency trellis codes for MIMO-OFDM systems are studied. We find that the channel constructed by the consecutive subcarriers of an OFDM block is a correlated fading channel with regular correlation function of the number and time delay of the multipaths. We decompose the correlated fading channel into two independent components: slow fading channel and fast fading channel. Therefore the design problem of space-frequency trellis codes is converted into the problem that we jointly design the space-time trellis code both in slow fading channel and in fast fading channel. We also show that the space-frequency trellis codes designed according to our criterion are robust against the time delay of multipaths. Simulation results are provided to confirm our theoretic analysis.

Weighted Linear Least Square Localization Algorithms for Received Signal Strength

Localization based on the received signal strength (RSS) is by far the cheapest and simplest option. By constructing the appropriate path-loss model, the RSS information can be converted to the distance estimates which can determine the position of the target node with Linear Least Square (LLS) algorithm. In this paper, the LLS algorithm can be directly applied by subtracting a reference node equation from the remaining ones rather than defining a new variable, which selects the reference node with the maximal RSS among all the RSS measurements. Furthermore, based on the latest research results about the estimates of the squared distance, we investigate the unbiased and linear minimum mean square error (MMSE) estimates of the squared distance, and the covariance matrixes about the two estimates with the proposed LLS algorithm are derived, respectively. Then the weighted LLS localization algorithms are presented by utilizing the covariance matrixes. Simulation results demonstrate that the localization accuracy of the linear MMSE estimate with the proposed LLS algorithm is superior to the unbiased estimate. Moreover, the proposed weighted LLS algorithms outperform the traditional LLS localization algorithms in terms of localization accuracy.

Improved and Extended Range Scale Algorithm for Wireless Cellular Location

The range scale algorithm (RSA) proposed in 2004 is a constrained optimization problem with only three base stations (BSs). In this letter, by introducing a new variable to replace the square term, the quadratic objective function of the constrained optimization problem in RSA is turned into a linear objective function. Then the computational complexity is reduced and the performance is improved. Moreover, when the number of BSs is larger than three, we construct a new objective function and give the corresponding constraints. So the RSA is extended for more BSs and the performance of positioning is improved significantly. Simulation results demonstrate that our proposed algorithms improve the location accuracy over traditional algorithms in different Non-line-of-sight (NLOS) environments.

Cooperative Spectrum Sensing with Double Threshold Detection Based on Reputation in Cognitive Radio

Cooperative spectrum sensing can mitigate the effects of shadowing and fading. However, when the number of cognitive users is very large, the bandwidth for reporting their sensing results will be insufficient. In order to eliminate the fail sensing problem for a cognitive radio system with double threshold detector, a new cooperative spectrum sensing algorithm is presented based on reputation in this paper. In particular, the closed forms for the normalized average number of sensing bits, the probabilities of the detection and the false-alarm are derived. Simulation results show that the average number of sensing bits decreases greatly without failing sensing, and the sensing performance is improved comparing with the conventional double threshold detection and the conventional single threshold detection.