This paper investigates the constellation/codebook design of a promising uplink multiple access technique, sparse code multiple access (SCMA), proposed for the fifth generation mobile networks. The application of bit-interleaved coded modulation with iterative multiuser detection is considered for uplink SCMA over fading channels. Extrinsic information transfer chart is used to aid the analysis and the design of multidimensional constellations, and the design criteria for multidimensional constellations and labelings optimization are thus established. Furthermore, a new and simple approach of multi-stage optimization for the multidimensional constellation design is proposed for SCMA, to improve the bit-error rate performance and alleviate the complexity of turbo multiuser detection. Numerical and simulation results are also provided to demonstrate the performance and verify the efficiency of the proposed scheme, compared with the state of the art.

This paper investigates the asymptotic performance of bit-interleaved coded modulation (BICM) with iterative multiuser detection and decoding in uplink sparse code multiple access (SCMA) systems. The extrinsic information transfer (EXIT) characteristics analysis of the joint multiuser detector for SCMA is provided, and shows that the average detection reliability for multiple users converges to the single-user case, if ideal feedback from the decoder is available to the detector. We develop a tight analytical bound on the convolutionally encoded bit-error rate (BER) for independent Rayleigh fadings, based on the single-user bound with arbitrary multidimensional constellations. Moreover, we analyze the achievable coding and diversity gains of the SCMA-BICM system with iterative receiver. Simulations are carried out to verify the effectiveness of the analysis.

We investigate the error performance of multidimensional constellations in the multiple access and broadcast channels. More specifically, we provide closed-form expressions for the pairwise error probability (PEP) of the joint maximum likelihood detection, for multiuser signaling in the presence of additive white Gaussian noise and Rayleigh fading. Arbitrary numbers of users and multidimensional signal sets are assumed, while the provided formula for the PEP is a function of the dimension-wise distances of the multidimensional constellation. Furthermore, a useful upper bound on the average symbol error probability is also obtained through the union bound. The analysis is applied to the sparse code multiple access systems. The analytical results are validated successfully through simulations, and show their importance in the multidimensional constellation design.

In this paper, we investigate the application of spherical codes in a sparse code multiple access (SCMA) system. We use spherical codes to build multidimensional mother constellations for SCMA codebooks, to lower peak to average power ratio (PAPR) as well as to improve the overall spectrum efficiency. Furthermore, we introduce four approaches to construct good spherical codes. These codes are easy and have large coding gains. We make extensions to some of these spherical codes such that they are suitable for usage in SCMA systems. The performance of the constructed codebooks are compared to known codebooks through simulations, and the numerical results show that spherical codes based codebooks can effectively improve the system performance.

This paper investigates error performance of sparse code multiple access (SCMA) networks with multiple access channels (MAC) and broadcast channels (BC).We give the closed-form expression for the pairwise error probability (PEP) of joint maximum likelihood (ML) detection for multiuser signals over additive white Gaussian noise (AWGN) and Rayleigh fading channels with an arbitrary number of users and multidimensional codebooks. An upper bound for the average symbol error rate (SER) is calculated. The bound is tight in both AWGN channel and Rayleigh fading channels for high SNR regions. The analytical bounds are compared with simulations, and the results confirm the effectiveness of the analysis for both AWGN and Rayleigh fading channels.

Although Hadoop MapReduce provides good programming abstractions and horizontal scalability, it is often blamed for its poor single node performance. In the meantime, MapReduce has already achieved a large install base, thus any performance improvement should keep the compatibility. In this paper, we address the challenges via several approaches guided by low-level performance analysis. And we materialize the approaches via NativeTask, a high-performance, fully compatible MapReduce execution engine. We evaluate its performance with representative HiBench workloads. The results show that the speedup NativeTask achieves ranges from 10% to 160%, and it paves the way for a better MapReduce that excels on both single node performance and scalability. In the future, hardware acceleration can also be applied to further improve the system's efficiency.

A novel image steganography algorithm in wavelet domain is presented using the iterative blending method. Using this algorithm, we can hide a secret image with 256 gray levels into another carrier image. By taking full advantage of the masking characteristics of the human visual system, a JND (just noticeable difference) threshold matrix is given pixel by pixel in the image subbands taking into account the texture and the luminance content of carrier image. The secret image is divided into two matrices to make the gray level no more than 16. Then the matrices are adaptively embedded into the wavelet coefficients of the carrier image by iterative blending. The carrier image and the blending parameter can act as the private keys. The experimental results show that the proposed algorithm provides good transparency and is robust to some extent. The technique also can be used in digital watermarking and other digital application areas.

A new light-weight approach, based on the cross-correlation of system call sequences, is presented to identify normal or intrusive program behavior. The program behavior is represented by the cross-correlation value which can be used to indicate the similarity between two sequences. If two sequences are same, the cross-correlation between them will achieve the maximum value. This method of characterizing program behavior by using cross-correlation offers significant computational advantages over HMM (hidden Markov model) or NN (neural network) methods due to the absence of unnecessary training process. Our experiments using UNM (University of New Mexico) audit data show that the cross-correlation based method can effectively detect intrusive attacks and achieve a low false positive rate.

A novel Kalman location estimator is proposed to perform wireless position location in cellular networks based on both angle-of-arrival (AOA) and time-of-arrival (TOA) measurements. Cartesian coordinate rotation is performed to reduce dimensions of the Kalman filter. Simulation results show that this approach simplifies iteration process and has almost the same performance as the standard extended Kalman filter. Handoffs between base stations are considered and effects of base station position errors and the scattering radius of macro-cells on subscribers' position location are analyzed and simulated. Simulation results show that the accuracy of the algorithm can meet the requirements of E-911.