Desheng Wang

Cross-layer design for LTE system with jointly AMC and ARQ on fading channel

A cross-layer design is developed for error-sensitive and latency-tolerated traffic over LTE system. Two adaptive techniques, automatic repeat request (ARQ) protocol at radio link control (RLC) sublayer and medium access control (MAC) sub layer and adaptive modulation and coding (AMC) scheme at physical (PHY) layer are combined to improve the average spectral efficiency of the system. The segmentation mechanism and the in-sequence delivery procedure are both considered. Closed-form expressions for performance metrics such as average service data unit (SDU) error rate and average in-sequence delivery SDU delay at RLC sub layer are derived. Using these expressions, an optimization problem is formulated to maximize the average spectral efficiency when the quality of service (QoS) achieves certain requirement. Simulation results reveal that we can further improve the average spectral efficiency by dynamically adjusting the adaptive parameters of the ARQ and AMC module, compared to the previous LTE system.

On the Degrees of Freedom region of general MIMO Broadcast Channel with mixed CSIT

The two-user multiple-input multiple-output (MIMO) Gaussian Broadcast Channel (BC) with mixed CSIT (i.e., delayed CSIT plus estimated current CSIT) under general antenna configuration is considered in this paper. Unlike the MISO scenario, obtaining tight characterization of the Degrees of Freedom (DoF) region seems difficult for the general MIMO BC settings. Despite that, the inner bound we provide in this paper is believed to be the best achievable bound so far. One novel ingredient of our scheme is the rate-splitting of the interference-encoded symbols, which provides the possible benefit of DoF gain by accommodating the transmission to the asymmetric receivers. Moreover, the outer bound of DoF region is also presented, which coincides our proposed inner bound in some cases.

Performance Analysis for Cooperative Relay Communication

Cooperative transmission is an efficient solution to combat against wireless channel fading at low power, and has attracted much attention for the future broadband communication. In this paper, we consider the cluster relay model for cooperative transmission and analyze the symbol error rate, outage probability and outage capacity accordingly. We achieve the closed-form expressions for the average symbol error rate in Rayleigh fading channel by using the moment generating function. Moreover, outage probability and outage capacity are derived. Monte-Carlo simulation shows the consistency between the theoretical derivations and the simulation results.

Joint user association power control and beamforming in HetNets via distributed SOCP

We consider in this paper an uplink coordinated beamforming problem for multi-cell heterogeneous networks (HetNets) whereby base stations are densely and co-channel deployed. A joint user-base station association, power control and beamforming scheme is presented for HetNets to minimize the power consumption. Such joint optimization is formulated as a mixed-integer second-order conic programming (MI-SOCP). To cope with this intractable problem, we develop two polynomial-time distributed methods. The first method is a two-stage solution, while the second method is a customized distributed solution by dual decomposition. The optimal tradeoff between data link gain and control link consumption using coordinated beamforming is able to be achieved by the two presented algorithms. Numerical results also show that, these two algorithms are efficient, and low complexity that consume much less run time comparing to the standard mixed-integer solver Gurobi.

Compressive Channel Feedback Schemes Based on Redundant Dictionary in MIMO Communication Systems

In the paper a sparse approximation based compressive channel feedback scheme is proposed in multiple input multiple output (MIMO) communication system. The redundant dictionary is applied for the channel sparse approximation. In order to reduce feedback resource consumption, a split compression is used for the sparse vector approximation. The impacts of codebook, codeword selection, measurement matrix and approximation error on capacity are analyzed. Simulations show that Grassmanian codebook/dictionary is more preferable for the channel approximation. In the point of capacity, the compressive digital and analog feedback outperform the random vector quantization feedback scheme with the same feedback resource consumption for large antenna array. Since the proposed compressive feedback scheme is not related to the antenna number, it is useful especially for the larger antenna array such as massive MIMO.

Compressed sensing in spatial MIMO channels

Many wireless channels exhibit sparse multipath feature in practice. In this paper, we analyze the sparsity of sparse MIMO channel and the leakage effect with fixed Fourier basis in the spatial/angular domain. In order to enhance the sparsity of the MIMO angular channels we propose an optimized overcomplete Fourier basis dictionary, which is obtained by a sparsity criterion, to represent the signals with the best basis. By converting the compressed sensing from multiple measurement vectors to a single measurement vector, the reconstruction of the MIMO channel is simplified and makes better use of the sparsity of the MIMO angular channels. Simulations show that with the optimized basis dictionary the leakage effect is reduced and the orthogonal matching pursuit algorithm can reconstruct the MIMO channel effectively with the optimized Fourier basis.

Performance analysis of compressed sensing with uniform scalar quantisation

In compressed sensing, the sampling rate can be greatly reduced based on the sparsity of the original signal; however, quantisation is one key aspect in signal acquirement. This article studies the scalar quantisation and its impacts on the compressed sensing. We consider the case in which both the original and the measurement signals are quantised or discrete, which widely exists in the practical applications such as the finite precision signals in the computer and the finite-set original signal in communication systems. We derive the recovery probability bound and the necessary measurement number bound for compressed sensing with scalar quantisation and simulate three modified compressed sensing recovery algorithms. Simulations show that coarse quantisation can be applied in compressed sensing for discrete or quantised sparse signal with sampling and storage efficiency.

Distributed precoder design for inter-cell interference suppressing in multi-cell MU-MIMO systems

In this paper, we propose a distributed precoder design algorithm for suppressing the inter-cell interference(ICI) and maximizing the average throughput of a multi-cell multiuser multi-input multi-output(MU-MIMO) system. Motivated by the recent results of the distributed signal-to-leakage-plus-noise ratio(SLNR) model for ICI coordination(ICIC), we design a joint optimization algorithm to achieve the pareto-optimal average system throughput. Existed SLNR-based algorithms only consider downlink optimization problem of one optimized factor, which will bring a restriction to the further improvement of the system performance. In our proposed algorithm, the SLNR-based downlink precoder and the transmitting power factor will be designed from a joint optimization problem, and the closed-form pareto-optimal solutions of both optimized factors can be obtained through matrix analysis and decomposition techniques. Simulation results show that the proposed distributed joint precoder design algorithm can significantly increase the average cell throughput and improve the resource efficiency while effectively reducing the system overhead.

Capacity Performance of Polarized Distributed MIMO System on Rician Channel

The analytical upper bound and lower bound on the ergodic capacity of polarized distributed antenna system and their relation with antenna polarization on Rician channel are deduced by applying properties of complex non-central Wishart matrices and matrix-variate non-central quadratic forms. Compared to the related studies, our analysis is extended to account for the polarized distributed system with Rician fading where a line-of-sight component exists and both ends are affected by spatial correlation. The antenna polarization has some impacts on the capacity bounds according to the expressions of capacity bounds. Both the transmitter and the receiver are equipped with multiple polarization antennas, and the transmitters are of linear layout. A power allocation scheme based on the path loss fading is presented by maximizing the capacity upper bound. The power allocation scheme is feedback efficient compared with those power allocation schemes based on statistical parameters of the channel which need a large amount of feedback. In the simulations, the ergodic capacity of polarized distributed MIMO is analyzed. Comparisons are taken on the effects of angle spread, Rician factor and power on the ergodic capacity. The proposed power allocation scheme is superior to the equal power allocation scheme and has very close performance to the optimal power allocation scheme.

Compressed Sensing via Dimension Spread in Dimension-Restricted Systems

Compressed sensing (CS) is applied to capture signals at sub-Nyquist rate when the sensing matrix satisfies the restricted isometry property (RIP). When in a dimension-restricted system which has small row dimension and not so good coherence, the RIP and measurement bound will not be satisfied, and compressed sensing can not be applied directly. In this letter, we propose the dimension spread CS to the dimension-restricted system by directed dimension spread and diversity dimension spread, which make the compressed sensing applicable. The spread dimension bounds for the proposed algorithms are deduced to guarantee exact recovery which are also proved by simulations. Meanwhile, the experimental comparisons for the directed dimension spread CS and diversity dimension spread CS are given and different CS recovery algorithms are carried out to show the effectiveness of the proposed algorithms in the dimension-restricted system. The diversity dimension spread CS outperforms the directed dimension spread CS for its effective dimension spread and diversity. The proposed algorithms can be directly applied in channel estimation and multiuser detection in overload system.