Huisheng Zhang

A Fast Algorithm for Nonnegative Matrix Factorization and Its Convergence

Nonnegative matrix factorization (NMF) has recently become a very popular unsupervised learning method because of its representational properties of factors and simple multiplicative update algorithms for solving the NMF. However, for the common NMF approach of minimizing the Euclidean distance between approximate and true values, the convergence of multiplicative update algorithms has not been well resolved. This paper first discusses the convergence of existing multiplicative update algorithms. We then propose a new multiplicative update algorithm for minimizing the Euclidean distance between approximate and true values. Based on the optimization principle and the auxiliary function method, we prove that our new algorithm not only converges to a stationary point, but also does faster than existing ones. To verify our theoretical results, the experiments on three data sets have been conducted by comparing our proposed algorithm with other existing methods.

Denoise-and-Forward Two-Path Successive Relaying With DBPSK Modulation

To recover the spectral efficiency (SE) loss caused by the half-duplex mode, this letter proposes a denoise-and-forward two-path successive relaying (DNF-TPSR) scheme, in which channel state information is not required. With differential binary phase-shift keying (DBPSK) modulation, the mixed signals received at the relay are mapped into a denoised symbol, and the destination uses the denoised symbol received in the previous time slot to cancel the inter-relay interference in the current time slot. We derive the end-to-end bit error rate (BER) and the diversity gain, which are validated by the simulation results. Although DNF-TPSR could not achieve the BER of half-duplex relay selection scheme, the SE is significantly improved by our proposed DNF-TPSR. Moreover, the BER and the SE of DNF-TPSR outperform that of direct transmission and full-duplex relaying with residual self-interference exceeding a certain level.

Two-way relaying with differential MPSK modulation in virtual full duplexing system

Two-way relaying (TWR) transmission achieves virtual full duplexing, which has attracted much attention in recent years for its high spectral efficiency. In a TWR system, two source nodes exchange information with each other simultaneously via a relay node. This paper proposes a decode-and-forward two-way relaying (DF-TWR) scheme and a denoise-and-forward two-way relaying (DNF-TWR) scheme using non-coherent multiple differential phase-shift keying (M-DPSK) modulation, in which channel state information (CSI) is not required. Firstly, we design the relay decoder in DF-TWR scheme, the relay denoising mapping function in DNF-TWR scheme, and the same source decoder in the two schemes using maximum likelihood (ML) principle. Then we analyse the end-to-end symbol error rate (SER) of DNF-TWR scheme with M-DPSK modulation. The simulation results show that the BER performance of DF-TWR scheme and DNF-TWR scheme are similar. The BER performance of the two schemes with 2DPSK modulation are good, and the BER performance with M-DPSK modulation are getting worse with the increase of modulation order M.

Two-way relaying with non-coherent differential MPSK modulation

This paper focuses on two-way relaying (TWR) system, where two source nodes exchange information with each other simultaneously via the relay node. We proposes a denoise-and-forward two-way relaying (DNF-TWR) scheme using non-coherent multiple differential phase-shift keying (M-DPSK) modulation when the channel state information (CSI) is unknown. Firstly, we design the denoising mapping function at the relay and the decoder at the source using maximum likelihood (ML) principle. Then we take DNF-TWR with differential binary phase-shift keying (2DPSK) modulation as an example to derive the closed-form end-to-end bit error rate (BER). The analytical results are verified through simulations. The simulation results show that DNF-TWR scheme with 2DPSK modulation works well, and the BER of DNF-TWR with M-DPSK modulation becomes larger as the modulation order M increases.

The improved Turbo-decoding Message-passing algorithm and corresponding decoder for LDPC based on LTE

The Turbo-decoding Message-passing (TDMP) algorithm of Low-Density Parity-Check (LDPC) codes has a faster convergence speed, lower hardware implementation complexity, and less storage units than the Belief-Passing (BP) algorithms. However, because of the integer quantization operations for initial information, restriction of storage units will cause the problem of decoding information overflowing. This paper gives the reason of overflow errors, proposes the improved decoding algorithm which can partially eliminate overflow errors, and designs the corresponding decoder which only requires some extra subtractors and shift operations. We analyze the computation complexity and compute decoder throughput. Finally, we simulate the error performances of the LDPC codes over the LTE channel, and simulation results show that the proposed algorithm effectively suppresses the overflow errors with a low decoder complexity and a high throughput.

Efficient Coded Cooperative Networks With Energy Harvesting and Transferring

In this paper, a multi-user multi-relay network with integrated energy harvesting and transferring (IEHT) strategy is studied. In our system, a simultaneous two-level cooperation, i.e., information- and energy-level cooperation is conducted for uplink data transmissions (from the users to a destination). Specifically, network coding is employed at the relays to facilitate the information-level cooperation; meanwhile, ET is adopted to share the harvested energy among the users for the energy-level cooperation. For generality purposes, the Nakagami-

Full-duplex denoise-and-forward two-way relaying with DBPSK modulation

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Efficient network-coded relaying systems with energy harvesting and transferring

fading channels that are independent but not necessarily identically distributed (i.n.i.d.) are considered. The problem of energy efficiency maximization under constraints of the energy causality and a predefined outage probability threshold is formulated and shown to be non-convex. By exploiting fractional and geometric programming, a convex form-based iterative algorithm is developed to solve the problem efficiently. Close-to-optimal power allocation and energy cooperation policies across consecutive transmissions are found. Moreover, the effects of relay locations, wireless energy transmission efficiency, battery capacity as well as the existence of direct links are investigated. The performance comparison with the current state of solutions demonstrates that the proposed policies can manage the harvested energy more efficiently.

Performances analysis of polar codes decoding algorithms over variant binary-input channels

In this paper, we propose a full-duplex denoise-and-forward two-way relaying (FDNF-TWR) scheme with differential binary phase-shift keying (DBPSK) modulation, which do not need instantaneous channel state information. In the proposed scheme, two full-duplex source nodes exchange their information with the help of one full-duplex relay node. A non-coherent relay decoder takes the residual self-interference (RSI) into consideration and maps the received mixed signals into a denoised symbol. A non-coherent source decoder takes the RSI into consideration and obtains the symbol from the relay. The simulation results show that the proposed FDNF-TWR scheme can achieve the bit error rate performance of the half-duplex denoise-and-forward two-way relaying (HDNF-TWR) scheme when the self-interference is cancelled well.

A Near-Far Effect Mitigation Method of Pseudolites Based on Array Signal

In this paper, a multi-user multi-relay network with wireless energy harvesting (EH) and transferring (ET) is studied. In our system, a simultaneous two-level cooperation, i.e., information-level and energy-level cooperation is conducted for uplink data transmissions (from the users to a destination). Specifically, network coding is employed at the relays to facilitate the information-level cooperation; meanwhile, ET is adopted to share the harvested energy among the users for the energy-level cooperation. The energy minimization problem that takes into account the energy causality and outage probability constraints is formulated. However, the optimization problem is non-convex and hard to be solved directly. Alternatively, an approximation technique is adopted to convert it into a convex one. By solving the convex problem, efficient power allocation and ET policies are designed. Numerical results show that the proposed algorithm is able to achieve a near-optimal performance and outperforms the state of arts.