Yuexing Peng

10 Gb/s hetsnets with millimeter-wave communications: access and networking - challenges and protocols

Heterogeneous and small cell networks (Het- SNets) increase spectral efficiency and throughput via hierarchical deployments. In order to meet the increasing requirements in capacity for future 5G wireless networks, millimeter-wave (mmWave) communications with unprecedented spectral resources have been suggested for 5G HetSNets. While the mmWave physical layer is well understood, major challenges remain for its effective and efficient implementation in Het- SNets from an access and networking point of view. Toward this end, we introduce a novel but 3GPP backwards-compatible frame structure, based on time-division duplex, which facilitates both high-capacity access and backhaul links. We then discuss networking issues arising from the multihop nature of the mmWave backhauling mesh. Finally, system-level simulations evaluate the performance of HetSNets with mmWave communications and corroborate the possibility of having capacities of tens of gigabits per second in emerging 5G systems.

An Enhanced Channel Estimation Method for Millimeter Wave Systems With Massive Antenna Arrays

In this letter, we focus on the efficient channel estimation problem for millimeter wave (MMW) systems with massive antenna arrays and RF constraints, aiming at achieving a fast and high resolution angle-of-arrival/angle-of-departure (AoA/AoD) estimation. We first propose a presentation of antenna array with virtual elements (AAVE) by appending additional virtual antenna elements into the original antenna array. On the basis of the AAVE structure, we explore the channel sparsity in the angular domain and develop an efficient angle estimation algorithm by using compressive sensing theories. We then proposed a training design and prove that the sensing matrix in the proposed training can guarantee the accurate detection of angles with a high probability. Both the analytical and simulation results show that, without changing the physical antenna arrays, the proposed approach can achieve not only a lower overhead, but also a significantly higher resolution in angles estimation, compared to the existing algorithms.

A secret key generation method based on CSI in OFDM-FDD system

Channel reciprocity is an inherent feature of time division duplex (TDD) system while in frequency division duplex (FDD) system it is limited due to different frequencies being used for the uplink and the downlink. As a consequence, channel reciprocity-based secret generating methods used in TDD systems cannot be applied directly to FDD systems. In this paper, we present a novel secret key generation method for FDD system, for which the communication pair estimate the channel state information (CSI) of the same time in the uplink by a specially designed forwarding strategy and generate the secret key from the CSI estimates. Numerical simulations are implemented to verify the effectiveness of the proposed method.

Cooperative Network Coding with Soft Information Relaying in Two-way Relay Cchannels

Network coding in wireless network can improve network throughput by exploiting the broadcast nature of the wireless network. Taking into consideration the error prone nature of wireless networks, we investigate the design of network coding implemented in physical layer, and propose a cooperative network coding scheme with soft information forwarding (SIR), which combines soft network coding and distributed turbo coding scheme in two-way relay channels (TWRC) in this paper. In order to mitigate the error propagation effect due to the imperfect decoding at the relay, soft network coding is deployed in the proposed scheme, where soft-input soft-output (SISO) encoder and decoder for recursive systematic convolutional (RSC) codes are implemented. Moreover, the soft information of both systematic bits and redundancy parity bits are forwarded at the relay by using higher-order constellations to achieve diversity gain. Aided by distance spectrum of turbo codes, concept of uniform interleaver, and Gaussian approximation of soft decoding information, union bound on the error performance of our scheme is analyzed. Both the analysis and simulation confirm that the proposed scheme achieves significant gain over conventional network coding in quasi-static fading channels.

Non-Uniform Linear Antenna Array Design and Optimization for Millimeter-Wave Communications

In this paper, we investigate the optimization of non-uniform linear antenna arrays (NULAs) for millimeterwave (mmWave) line-of-sight (LoS) multiple-input multipleoutput (MIMO) channels. Our focus is on the maximization of the system effective multiplexing gain (EMG), by optimizing the individual antenna positions in the transmit/receive NULAs. Here, the EMG is defined as the number of signal streams that are practically supported by the channel at a finite signal-to-noise ratio. We first derive analytical expressions for the asymptotic channel eigenvalues with arbitrarily deployed NULAs when, asymptotically, the end-to-end distance is sufficiently large compared with the aperture sizes of the transmit/receive NULAs. Based on the derived expressions, we prove that the asymptotically optimal NULA deployment that maximizes the achievable EMG should follow the groupwise Fekete-point distribution. Specifically, the antennas should be physically grouped into K separate ULAs with the minimum feasible antenna spacing within each ULA, where K is the target EMG to be achieved; in addition, the centers of these K ULAs follow the Fekete-point distribution. We numerically verify the asymptotic optimality of such an NULA deployment and extend it to a groupwise projected arch-type NULA deployment, which provides a more practical option for mmWave LoS MIMO systems with realistic nonasymptotic configurations. Numerical examples are provided to demonstrate a significant capacity gain of the optimized NULAs over traditional ULAs.

An Off-Grid Turbo Channel Estimation Algorithm for Millimeter Wave Communications

The bandwidth shortage has motivated the exploration of the millimeter wave (mmWave) frequency spectrum for future communication networks. To compensate for the severe propagation attenuation in the mmWave band, massive antenna arrays can be adopted at both the transmitter and receiver to provide large array gains via directional beamforming. To achieve such array gains, channel estimation (CE) with high resolution and low latency is of great importance for mmWave communications. However, classic super-resolution subspace CE methods such as multiple signal classification (MUSIC) and estimation of signal parameters via rotation invariant technique (ESPRIT) cannot be applied here due to RF chain constraints. In this paper, an enhanced CE algorithm is developed for the off-grid problem when quantizing the angles of mmWave channel in the spatial domain where off-grid problem refers to the scenario that angles do not lie on the quantization grids with high probability, and it results in power leakage and severe reduction of the CE performance. A new model is first proposed to formulate the off-grid problem. The new model divides the continuously-distributed angle into a quantized discrete grid part, referred to as the integral grid angle, and an offset part, termed fractional off-grid angle. Accordingly, an iterative off-grid turbo CE (IOTCE) algorithm is proposed to renew and upgrade the CE between the integral grid part and the fractional off-grid part under the Turbo principle. By fully exploiting the sparse structure of mmWave channels, the integral grid part is estimated by a soft-decoding based compressed sensing (CS) method called improved turbo compressed channel sensing (ITCCS). It iteratively updates the soft information between the linear minimum mean square error (LMMSE) estimator and the sparsity combiner. Monte Carlo simulations are presented to evaluate the performance of the proposed method, and the results show that it enhances the angle detection resolution greatly.

An energy-efficient clustered distributed coding for large-scale wireless sensor networks

A wireless sensor network (WSN) usually consists of a large number of battery-powered low-cost sensors with limited data collection and processing capacity. In order to prolong the lifetime of the WSN with a target error performance, a novel clustered distributed coding framework, referred to as distributed multiple-sensor cooperative turbo coding (DMSCTC), is developed for a large-scale WSN with sensor grouped in cooperative cluster. In the proposed DMSCTC scheme, a simple forward error correction is employed at each sensor and a simple multi-sensor joint coding is adopted at the cluster head, while complicated joint iterative decoding is implemented only at the data collector. The proposed DMSCTC scheme achieves extra distributed coding gain and cooperative spatial diversity without introducing extra complexity burden on the sensors by transferring the complicated joint decoding process to the data collector. With the proposed scheme, the WSN can achieve the target error performance with less power consumption, thus prolonging its lifetime. The error performance and energy efficiency of the proposed DMSCTC scheme are analyzed, and followed by Monte Carlo simulations. Both analytical and simulation results show that the DMSCTC can substantially improve the energy efficiency of the clustered WSN.

A Real-time Two-way Authentication Method Based on Instantaneous Channel State Information for Wireless Communication Systems

Traditional solutions handle security at the application layer, which causes huge signaling overhead and long delay if authentication is implemented for every signal to enhance the security of wireless communication systems. In this paper, a realtime and two-way authentication method is proposed, which is based on the characteristics of radio channel including randomness and privacy. For the proposed method, the unique instant channel state information (CSI) can be used to authenticate the transmitter. In frequency- and time-selective fading channels, the current estimated CSI is compared with the predicted CSI, which is implemented at the previous frame, in order to authenticate the validation of the received signal. Both the hypothesis testing and mutual information measure methods are used for authentication determination, and the Mont Carlo simulation results verify the efficiency of the proposed method.

Secret Key Generation Based on Estimated Channel State Information for TDD-OFDM Systems Over Fading Channels

One of the fundamental problems in cryptography is the generation of a common secret key between two legitimate parties to prevent eavesdropping. In this paper, we propose an information-theoretic secret key generation (SKG) method for time division duplexing (TDD)-based orthogonal frequency-division multiplexing (OFDM) systems over multipath fading channels. By exploring physical layer properties of the wireless medium, i.e., the reciprocity, randomness, and privacy features of the radio channel, an SKG method is proposed to maximize the number of secret bits given a target secret key disagreement ratio (SKDR). In the proposed SKG method, the phase information of the estimated channel state information (CSI) is distilled for SKG, and a special guard band (GB) scheme is designed to achieve the target SKDR with a small phase information loss. The proposed GB consists of both the amplitude GB (AGB) and phase GB (PGB), where the AGB is determined by the average signal-to-interference plus noise ratio (SINR), whereas the PGB adapts itself to the instantaneous SINR and thus incurs a smaller phase information loss in the higher SINR region. Analyses show that this GB scheme trades off a small loss of channel phase information for a better SKDR performance, and achieves a much larger number of quantization levels for a given SKDR due to the fact that the PGB decreases quickly as the SINR increases. Based on the performance analysis on the SKDR, the average secret key length, the phase information loss percentage (PILP), and the optimal GB and quantization level of the adaptive quantizor are derived for a given target SKDR. Both analytical and simulation results are presented to demonstrate the superiority of the proposed scheme for TDD-OFDM systems over frequency-selective fading channels.

Turbo compressed channel sensing for millimeter wave communications with massive antenna arrays and RF chain constraints

With the abundant frequency spectrum available at millimeter wave (MMW) frequency bands, MMW communications can easily achieve multi-gigabit wireless transmission. One key challenge for MMW system is the design of an efficient and fast channel estimation algorithm with limited RF chains to facilitate the beamforming and coherent detection, in compensation for the severe propagation attenuation. In this paper, an efficient channel estimation algorithm is developed for MMW systems with massive antenna arrays and RF chain constrains to achieve: i) a significant reduction of the time slot consumption; ii) a great enhancement of the estimation reliability in the low signal-to-noise ratio (SNR) region. By fully exploiting the sparse structure of channel in MMW frequency bands, an efficient training method is designed to achieve the fast and reliable channel estimation based on the compressed sensing (CS) methods. An iterative soft decoding method, termed turbo compressed channel sensing (TCCS), is developed to estimate the channel state information (CSI) by iteratively updating the soft information between the linear minimum mean square error (LMMSE) estimator and the sparsity combiner, which refines the estimation by exploiting the sparsity of CSI. Simulation results show that the proposed approach greatly outperforms existing approaches.