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Yong Liang Guan

Publications and source records attributed to Yong Liang Guan.

At least 145 records · Page 8Linked to original sources

Transmit Optimization with Improper Gaussian Signaling for Interference Channels

This paper studies the achievable rates of Gaussian interference channels with additive white Gaussian noise (AWGN), when improper or circularly asymmetric complex Gaussian signaling is applied. For the Gaussian multiple-input multiple-output interference channel (MIMO-IC) with the interference treated as Gaussian noise, we show that the user's achievable rate can be expressed as a summation of the rate achievable by the conventional proper or circularly symmetric complex Gaussian signaling in terms of the users' transmit covariance matrices, and an additional term, which is a function of both the users' transmit covariance and pseudo-covariance matrices. The additional degrees of freedom in the pseudo-covariance matrix, which is conventionally set to be zero for the case of proper Gaussian signaling, provide an opportunity to further improve the achievable rates of Gaussian MIMO-ICs by employing improper Gaussian signaling. To this end, this paper proposes widely linear precoding, which efficiently maps proper information-bearing signals to improper transmitted signals at each transmitter for any given pair of transmit covariance and pseudo-covariance matrices. In particular, for the case of two-user Gaussian single-input single-output interference channel (SISO-IC), we propose a joint covariance and pseudo-covariance optimization algorithm with improper Gaussian signaling to achieve the Pareto-optimal rates. By utilizing the separable structure of the achievable rate expression, an alternative algorithm with separate covariance and pseudo-covariance optimization is also proposed, which guarantees the rate improvement over conventional proper Gaussian signaling.

cs.IT↗

Cluster-based Transform Domain Communication Systems for High Spectrum Efficiency

This paper presents a cluster-based transform domain communication system (TDCS) to improve spectrum efficiency. Unlike the utilities of clusters in orthogonal frequency division multiplex (OFDM) systems, the cluster-based TDCS framework divides entire unoccupied spectrum bins into $L$ clusters, where each one represents a data steam independently, to achieve $L$ times of spectrum efficiency compared to that of the traditional one. Among various schemes of spectrum bin spacing and allocation, the TDCS with random allocation scheme appears to be an ideal candidate to significantly improve spectrum efficiency without seriously degrading power efficiency. In multipath fading channel, the coded TDCS with random allocation scheme achieves robust BER performance due to a large degree of frequency diversity. Furthermore, our study shows that the smaller spectrum bin spacing should be configured for the cluster-based TDCS to achieve higher spectrum efficiency and more robust BER performance.

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Wireless Compressive Sensing for Energy Harvesting Sensor Nodes

We consider the scenario in which multiple sensors send spatially correlated data to a fusion center (FC) via independent Rayleigh-fading channels with additive noise. Assuming that the sensor data is sparse in some basis, we show that the recovery of this sparse signal can be formulated as a compressive sensing (CS) problem. To model the scenario in which the sensors operate with intermittently available energy that is harvested from the environment, we propose that each sensor transmits independently with some probability, and adapts the transmit power to its harvested energy. Due to the probabilistic transmissions, the elements of the equivalent sensing matrix are not Gaussian. Besides, since the sensors have different energy harvesting rates and different sensor-to-FC distances, the FC has different receive signal-to-noise ratios (SNRs) for each sensor. This is referred to as the inhomogeneity of SNRs. Thus, the elements of the sensing matrix are also not identically distributed. For this unconventional setting, we provide theoretical guarantees on the number of measurements for reliable and computationally efficient recovery, by showing that the sensing matrix satisfies the restricted isometry property (RIP), under reasonable conditions. We then compute an achievable system delay under an allowable mean-squared-error (MSE). Furthermore, using techniques from large deviations theory, we analyze the impact of inhomogeneity of SNRs on the so-called k-restricted eigenvalues, which governs the number of measurements required for the RIP to hold. We conclude that the number of measurements required for the RIP is not sensitive to the inhomogeneity of SNRs, when the number of sensors n is large and the sparsity of the sensor data (signal) k grows slower than the square root of n. Our analysis is corroborated by extensive numerical results.

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Performance Analysis of Two-Step Bi-Directional Relaying with Multiple Antennas

In this paper we study decode-and-forward multi-antenna relay systems that achieve bi-directional communication in two time slots. We investigate different downlink broadcast schemes which employ binary or analog network coding at the relay. We also analyze and compare their performances in terms of diversity order and symbol error probability. It is shown that if exact downlink channel state information is available at the relay, using analog network coding in the form of multi-antenna maximal-ratio transmit beamforming to precode the information vectors at the relay gives the best performance. Then, we propose a Max-Min antenna selection with binary network coding scheme that can approach this performance with only partial channel state information.

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Detailed Steps of the Fourier-Motzkin Elimination

This file provide the detailed steps for obtaining the bounds on $R_1$, $R_2$ via the obtained results on $(R_{1c},R_{1p},R_{2c},R_{2p})$. It is subplementary material for the paper titled "On the Capacity Region of Two-User Linear Deterministic Interference Channel and Its Application to Multi-Session Network Coding"

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On the Capacity Region of Two-User Linear Deterministic Interference Channel and Its Application to Multi-Session Network Coding

In this paper, we study the capacity of the two-user multiple-input multiple-output (MIMO) linear deterministic interference channel (IC), with possible correlations within/between the channel matrices. The capacity region is characterized in terms of the rank of the channel matrices. It is shown that \emph{linear precoding} with Han-Kobayashi type of rate-splitting, i.e., splitting the information-bearing symbols of each user into common and private parts, is sufficient to achieve all the rate pairs in the derived capacity region. The capacity result is applied to obtain an achievable rate region for the double-unicast networks with random network coding at the intermediate nodes, which can be modeled by the two-user MIMO linear deterministic IC studied. It is shown that the newly proposed achievable region is strictly larger than the existing regions in the literature.

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Improving Achievable Rate for the Two-User SISO Interference Channel with Improper Gaussian Signaling

This paper studies the achievable rate region of the two-user single-input-single-output (SISO) Gaussian interference channel, when the improper Gaussian signaling is applied. Under the assumption that the interference is treated as additive Gaussian noise, we show that the user's achievable rate can be expressed as a summation of the rate achievable by the conventional proper Gaussian signaling, which depends on the users' input covariances only, and an additional term, which is a function of both the users' covariances and pseudo-covariances. The additional degree of freedom given by the pseudo-covariance, which is conventionally set to be zero for the case of proper Gaussian signaling, provides an opportunity to improve the achievable rate by employing the improper Gaussian signaling. Since finding the optimal solution for the joint covariance and pseudo-covariance optimization is difficult, we propose a sub-optimal but efficient algorithm by separately optimizing these two sets of parameters. Numerical results show that the proposed algorithm provides a close-to-optimal performance as compared to the exhaustive search method, and significantly outperforms the optimal proper Gaussian signaling and other existing improper Gaussian signaling schemes.

cs.IT↗

Reduced Functional Dependence Graph and Its Applications

Functional dependence graph (FDG) is an important class of directed graph that captures the dominance relationship among a set of variables. FDG is frequently used in calculating network coding capacity bounds. However, the order of FDG is usually much larger than the original network and the computational complexity of many bounds grows exponentially with the order of FDG. In this paper, we introduce the concept of reduced FDG, which is obtained from the original FDG by keeping only those "essential" edges. It is proved that the reduced FDG gives the same capacity region/bounds with the original FDG, but requiring much less computation. The applications of reduced FDG in the algebraic formulation of scalar linear network coding is also discussed.

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Improved Linear Precoding over Block Diagonalization in Multi-cell Cooperative Networks

In downlink multiuser multiple-input multiple-output (MIMO) systems, block diagonalization (BD) is a practical linear precoding scheme which achieves the same degrees of freedom (DoF) as the optimal linear/nonlinear precoding schemes. However, its sum-rate performance is rather poor in the practical SNR regime due to the transmit power boost problem. In this paper, we propose an improved linear precoding scheme over BD with a so-called "effective-SNR-enhancement" technique. The transmit covariance matrices are obtained by firstly solving a power minimization problem subject to the minimum rate constraint achieved by BD, and then properly scaling the solution to satisfy the power constraints. It is proved that such approach equivalently enhances the system SNR, and hence compensates the transmit power boost problem associated with BD. The power minimization problem is in general non-convex. We therefore propose an efficient algorithm that solves the problem heuristically. Simulation results show significant sum rate gains over the optimal BD and the existing minimum mean square error (MMSE) based precoding schemes.

cs.IT↗

Block-Orthogonal Space-Time Code Structure and Its Impact on QRDM Decoding Complexity Reduction

Full-rate space time codes (STC) with rate = number of transmit antennas have high multiplexing gain, but high decoding complexity even when decoded using reduced-complexity decoders such as sphere or QRDM decoders. In this paper, we introduce a new code property of STC called block-orthogonal property, which can be exploited by QR-decomposition-based decoders to achieve significant decoding complexity reduction without performance loss. We show that such complexity reduction principle can benefit the existing algebraic codes such as Perfect and DjABBA codes due to their inherent (but previously undiscovered) block-orthogonal property. In addition, we construct and optimize new full-rate BOSTC (Block-Orthogonal STC) that further maximize the QRDM complexity reduction potential. Simulation results of bit error rate (BER) performance against decoding complexity show that the new BOSTC outperforms all previously known codes as long as the QRDM decoder operates in reduced-complexity mode, and the code exhibits a desirable complexity saturation property.

cs.IT↗

Optimization of Fast-Decodable Full-Rate STBC with Non-Vanishing Determinants

Full-rate STBC (space-time block codes) with non-vanishing determinants achieve the optimal diversity-multiplexing tradeoff but incur high decoding complexity. To permit fast decoding, Sezginer, Sari and Biglieri proposed an STBC structure with special QR decomposition characteristics. In this paper, we adopt a simplified form of this fast-decodable code structure and present a new way to optimize the code analytically. We show that the signal constellation topology (such as QAM, APSK, or PSK) has a critical impact on the existence of non-vanishing determinants of the full-rate STBC. In particular, we show for the first time that, in order for APSK-STBC to achieve non-vanishing determinant, an APSK constellation topology with constellation points lying on square grid and ring radius $\sqrt{m^2+n^2} (m,n\emph{\emph{integers}})$ needs to be used. For signal constellations with vanishing determinants, we present a methodology to analytically optimize the full-rate STBC at specific constellation dimension.

cs.IT↗

Group-Decodable Space-Time Block Codes with Code Rate > 1

High-rate space-time block codes (STBC with code rate > 1) in multi-input multi-output (MIMO) systems are able to provide both spatial multiplexing gain and diversity gain, but have high maximum likelihood (ML) decoding complexity. Since group-decodable (quasi-orthogonal) code structure can reduce the decoding complexity, we present in this paper systematic methods to construct group-decodable high-rate STBC with full symbol-wise diversity gain for arbitrary transmit antenna number and code length. We show that the proposed group-decodable STBC can achieve high code rate that increases almost linearly with the transmit antenna number, and the slope of this near-linear dependence increases with the code length. Comparisons with existing low-rate and high-rate codes (such as orthogonal STBC and algebraic STBC) are conducted to show the decoding complexity reduction and good code performance achieved by the proposed codes.

cs.IT↗

Multi-User SISO Precoding based on Generalized Multi-Unitary Decomposition for Single-carrier Transmission in Frequency Selective Channel

In this paper, we propose to exploit the richly scattered multi-path nature of a frequency selective channel to provide additional degrees of freedom for desigining effective precoding schemes for multi-user communications. We design the precoding matrix for multi-user communications based on the Generalized Multi-Unitary Decomposition (GMUD), where the channel matrix H is transformed into P_i*R_r*Q_i^H. An advantage of GMUD is that multiple pairs of unitary matrices P_i and Q_i can be obtained with one single R_r. Since the column of Q_i can be used as the transmission beam of a particular user, multiple solutions of Q_i provide a large selection of transmission beams, which can be exploited to achieve high degrees of orthogonality between the multipaths, as well as between the interfering users. Hence the proposed precoding technique based on GMUD achieves better performance than precoding based on singular value decomposition.

cs.IT↗

Bi-Directional Multi-Antenna Relay Communications with Wireless Network Coding

In this paper, we consider a two-way or bidirectional communications system with a relay equipped with multiple antennas. We show that when the downlink channel state information is not known at the relay, the benefit of having additional antennas at the relay can only be obtained by using decode and forward (DF) but not amplify and forward (AF). The gain becomes significant when we employ transmit diversity together with wireless network coding. We also demonstrate how the performance of such system can be improved by performing antenna selection at the relay. Our results show that if downlink channel state information is known at the relay, network coding may not provide additional gain than simple antenna selection scheme.

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Differential Transmit Diversity Based on Quasi-Orthogonal Space-Time Block Code

By using joint modulation and customized constellation set, we show that Quasi-Orthogonal Space-Time Block Code (QO-STBC) can be used to form a new differential space-time modulation (DSTM) scheme to provide full transmit diversity with non-coherent detection. Our new scheme can provide higher code rate than existing DSTM schemes based on Orthogonal STBC. It also has a lower decoding complexity than the other DSTM schemes, such as those based on Group Codes, because it only requires a joint detection of two complex symbols. We derive the design criteria for the customized constellation set and use them to construct a constellation set that provides a wide range of spectral efficiency with full diversity and maximum coding gain.

cs.IT↗

Unitary Differential Space-Time Modulation with Joint Modulation

We develop two new designs of unitary differential space-time modulation (DSTM) with low decoding complexity. Their decoder can be separated into a few parallel decoders, each of which has a decoding search space of less than sqrt(N) if the DSTM codebook contains N codewords. Both designs are based on the concept of joint modulation, which means that several information symbols are jointly modulated, unlike the conventional symbol-by-symbol modulation. The first design is based on Orthogonal Space-Time Block Code (O-STBC) with joint constellation constructed from spherical codes. The second design is based on Quasi-Orthogonal Space-Time Block Code (QO-STBC) with specially designed pair-wise constellation sets. Both the proposed unitary DSTM schemes have considerably lower decoding complexity than many prior DSTM schemes, including those based on Group Codes and Sp(2) which generally have a decoding search space of N for a codebook size of N codewords, and much better decoding performance than the existing O-STBC DSTM scheme. Between two designs, the proposed DSTM based on O-STBC generally has better decoding performance, while the proposed DSTM based on QO-STBC has lower decoding complexity when 8 transmit antennas.

cs.IT↗

Power-Balanced Orthogonal Space-Time Block Code

In this paper, we propose two new systematic ways to construct amicable orthogonal designs (AOD), with an aim to facilitate the construction of power-balanced orthogonal spacetime block codes (O-STBC) with favorable practical attributes. We also show that an AOD can be constructed from an Amicable Family (AF), and such a construction is crucial for achieving a power-balanced O-STBC. In addition, we develop design guidelines on how to select the "type" parameter of an AOD so that the resultant O-STBC will have better power-distribution and code-coefficient attributes. Among the new O-STBCs obtained, one is shown to be optimal in terms of power distribution attributes. In addition, one of the proposed construction methods is shown to generalize some other construction methods proposed in the literature.

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Optimizing Quasi-Orthogonal STBC Through Group-Constrained Linear Transformation

In this paper, we first derive the generic algebraic structure of a Quasi-Orthogonal STBC (QO-STBC). Next we propose Group-Constrained Linear Transformation (GCLT) as a means to optimize the diversity and coding gains of a QO-STBC with square or rectangular QAM constellations. Compared with QO-STBC with constellation rotation (CR), we show that QO-STBC with GCLT requires only half the number of symbols for joint detection, hence lower maximum-likelihood decoding complexity. We also derive analytically the optimum GCLT parameters for QO-STBC with square QAM constellation. The optimized QO-STBCs with GCLT are able to achieve full transmit diversity, and have negligible performance loss compared with QO-STBCs with CR at the same code rate.

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