With knowledge of statistical channel state information (CSI) at the base station (BS), one can reduce the pilot overhead and improve the channel estimation performance in massive multiple-input multiple-output (MIMO) systems by exploiting the non-orthogonal pilot sequences. However, due to the limited uplink (UL) training resources, it is challenging to acquire the high-accuracy statistical CSI in real-time. To tackle this problem, an emerging technique is to construct a channel knowledge map (CKM) based on the statistical CSI. In order to construct such a CKM, it is necessary to analyze the spatial and temporal correlations of statistical CSI. Specifically, this paper analyzes the spatial and temporal correlations of beam domain channel power matrices (BDCPMs), obtained from channel measurements in a massive MIMO testbed. Furthermore, to verify the effectiveness of the stored aged BDCPMs, we also simulate channel estimation performance using BDCPMs measured at different dates. Both measured and simulated results demonstrate the effectiveness of the CKM based on statistical CSI.

As a promising solution for global coverage, low-earth orbit (LEO) satellite communication networks can provide reliable communication and stable control for Internet of Things (IoT) mobile devices. Compared to terrestrial networks, the limited transmission resources, extended propagation delay, and severe signal loss in satellite systems make it challenging to achieve energy-efficient wireless control for satellite IoT applications. In this article, we consider a satellite-based wireless control system (WCS) and propose a control-aware energy-efficient transmission scheme. Different from traditional satellite communication, this scheme ensures the control stability of the satellite IoT systems and minimize the transmission energy consumption through the joint design of satellite beamforming, power allocation, and user scheduling. To reduce energy consumption while satisfying control stability, we first transform the constraint of the control stability into a communication reliability requirement. Then, we use a Lyapunov drift-plus-penalty optimization framework to convert the long-term resource allocation into a deterministic one-shot problem. Finally, we solve the transformed problem through alternating optimization in each time slot. Specifically, user scheduling scheme is designed by utilizing a semidefinite relaxation approach and beamforming and power allocation are carried out by applying a path-following approach. Simulation results illustrate that the proposed schemes can achieve control stability of satellite IoT systems and obtain the lower energy consumption compared to existing schemes.

Satellite communication stands as an emerging tech-nology pivotal in enabling the seamless global deployment of the Internet of Things (IoT). In this study, we investigate a control-oriented optimization problem in satellite IoT system, such as satellite-enabled automated control for drones and unmanned vehicles, etc. This approach stands as a distinct contrast to conventional studies that lean heavily on communication-oriented issues. Nevertheless, due to the limited power of satellite and the significant transmission distance between satellites and Earth, maintaining control stability poses substantial challenges for satellite control systems. Therefore, our focus is to address the optimization from the angle of minimizing the aggregate linear quadratic regulator (LQR) control cost by designing satellite beamforming. In detail, a developed path-following algorithm is capable of converging to a minimally optimal local solution. When compared with the conventional capacity-oriented optimization framework, the algorithm proposed in this paper has proven to yield a comparatively diminished LQR control cost.

While sequence-to-sequence (seq2seq) models on semantic parsing have demonstrated significant performance, the need for large amounts of labeled data still hinders the application of this technology to resource-poor domains. In this work, we work on alleviating data scarcity in semantic parsing. We propose a semi-supervised semantic parsing methods by exploiting unlabeled natural utterances in a novel multi-task learning framework. Two strategies are proposed. The first one takes entity sequences as training targets to improve the representations of encoder and reduce entity-mistakes in prediction. The second one extends Mean Teacher to seq2seq model and generates more target-side data to improve the generalizability of decoder network. Experiments demonstrate that our proposed methods significantly outperform the supervised baseline and achieve more impressive improvement than previous methods.

Multi-color visible light communication (MC-VLC) is able to achieve high date rate via multiple color channels. To separate different colors, optical filters have to be adopted. In conventional MC-VLC systems, the center wavelength (CWL) and bandwidth (BW) of optical filters is carefully designed for each transmitted color component at normal angles of incidence (AOIs). However, at non-normal AOIs, the CWL of optical filters shifts to shorter wavelength namely the filter CWL shift, leading to serious cross-color interference. In this paper, we propose a novel optical filter bank structure, which consists of a series of narrow-band optical filters, to address the issues caused by the CWL shift. We first establish the corresponding channel model for the VLC links based on optical filter bank, and then design the optimal combining receiver for different AOIs. Simulation results demonstrate that the proposed optical filter bank structure exhibits high and stable performance, and shows strong compatibility for different transmitter configurations.

In visible light communication (VLC), using multiple colors is an efficient way to enhance data rate, leading to multi-color VLC (MC-VLC). However, the performance of MC-VLC is jeopardized by the spectral overlaps of different colors. Thin-film optical filters, as the key component of MC-VLC systems, are usually adopted to separate colors. The passband bandwidth (BW) and center wavelength (CWL) of optical filters are critical to mitigate the crosstalk among colors and, thus, must be carefully designed. Moreover, due to the intrinsic wavelength shift of the CWL with the varying of the angle of incidence, it is challenging to support mobility for MC-VLC. In this paper, we consider a joint design of multiple optical filters for MC-VLC by properly selecting the BW and CWL of each filter. We first investigate the optical filter design for a fixed receiver location. Then, to support mobility, we propose two robust optical filter designs, namely, statistically and worst case robust designs, which do not rely on the exact receiver location. Efficient methods are developed to solve the corresponding design problems and obtain the optimized optical filters. Compared with the existing optical filters, the proposed optical filters exhibits much better performance in various scenarios.

For polar codes, both successive cancellation list (SCL) decoding and list sphere decoding (LSD) aim to balance performance and complexity. The same list structure but different decoding schedules of SCL and LSD can lead to a combination of both schemes. In this paper, an efficient joint list decoder with SCL and LSD (JLSCD) is proposed to reduce time complexity. We apply SCL and LSD schemes simultaneously but independently, then merge them at the middle point of the decoding. Numerical results have demonstrated JLSCD scheme's advantage in complexity. FPGA implementation of JLSCD decoder is also given in this paper.

With low-density parity-check (LDPC) code and polar code selected as the standard codes for 5G eMBB scenario, one challenge is how to improve the hardware efficiency when both decoders are required by one system. Since LDPC and polar codes can be decoded with belief propagation (BP) algorithms, this similarity allows us to design a reconfigurable decoder, which can decode both codes at the cost of only one decoder. Numerical and implementation results are also given in this paper to show that the proposed decoder achieves higher hardware efficiency than stand-alone LDPC or polar decoder, without harming the error performance.

Visible light communication (VLC) equipped with multiple light-emitting diodes (LEDs) can provide near ubiquitous indoor coverage for both communication and illumination. This paper introduces the concept of biased beamforming to explore the full potential of multicarrier multi-LED VLC systems. Biased beamforming includes two components to be jointly designed: a direct current (DC) bias on each LED and a beamforming vector on each subcarrier. We first analyze the impact on clipping in multi-LED VLC systems. Next, we consider the joint optimization of beamforming and biasing to maximize data rate. We find the optimal beamformer and analytically characterize its structure. We further optimize the bias on each LED and provide the globally optimal solution in closed form for flat channels, which leads to several critical insights that are helpful for practical systems. We also derive a simplified near-optimal solution for dispersive channels and develop an efficient method for biased beamforming. The performance of the proposed biased beamforming design outperforms existing solutions.

In multi-color visible light communications (MC-VLC), using multiple colors is an efficient way to enhance data rate, which is, however, jeopardized by the spectral overlaps of colors. Thin-film interference filters, as the key components of MC-VLC, are usually adopted to separate color channels. A careful design of center wavelength (CWL) and bandwidth of the filter passband is critical to mitigate crosstalk among colors, especially when the color number is greater than three. Moreover, due to the intrinsic short-wavelength shift of CWL with the increase of angle of incident (AoI), it is also challenging to support the mobility for MC-VLC employing thin-film interference filters. In this work, we investigate the thin-film interference filter design for two scenarios: the receiver is at a fixed and known position with perfect knowledge of AoI, and the receiver randomly locates with only a stochastic knowledge of AoI. To maximize the signal to interference plus noise ratio (SINR) for each color channel, an alternative optimization algorithm is proposed. Numerical simulations illustrate that, in both scenarios, our designed filters could achieve a higher SINR and a lower bit error rate than existing filters. Moreover, compared with the filter for fixed AoI, our filter for random AoI exhibits a balanced performance in mobile scenarios.

This paper proposes a novel concept of biased beamforming to explore the full potential of multicarrier visible light communication (VLC) systems equipped with multiple light-emitting diodes (LEDs). Biased beamforming requires joint optimization of both: a direct current bias on each LED and a beamforming vector on each subcarrier. We first analyze the impact of clipping in multi-LED multicarrier systems, before carrying out the joint optimization of beamforming and biasing. We derive the optimal biased beamforming in closed form, along with several critical insights that are helpful for practical systems. The proposed biased beamforming strategy outperforms existing solutions, as shown by our simulation results.

For the design, performance evaluation, and optimization of potential 3-D multiple input and multiple output (3-D MIMO) algorithms, an accurate stochastic channel model is indispensable. Simultaneously, it is desirable for the new 3-D MIMO channel model to be a further expansion of already well developed 2-D MIMO channel models to allow easy implementation and facilitate possible $3^{rd}$ generation partnership project standardization. This paper first shows our recent outfield channel measurement campaigns in urban macrocell scenarios with a planar antenna array and a crown-shaped antenna array installed on the base station and the user sides, respectively. A comprehensive methodology from the statistical analysis perspective to characterize the 3-D MIMO channel, particularly, in the elevation domain, is then elaborated upon. The framework of the new approach coincides with mainstream parametric stochastic models. Moreover, it is observed that, by recalculating the statistics of the large scale parameters as well as their cross-correlation matrix to rectify existent non-positive definite problem, adding distance dependent elevation angular spread and introducing a mixture of Von Mises Fisher distributions to describe the interdependence between azimuth and elevation, the accuracy of current standardized 3-D channel models can be improved upon. Finally, numerical results verify the validity of our proposal.

For polar codes, cyclic redundancy check (CRC)aided successive cancellation list (CA-SCL) decoder has attracted increasing attention from both academia and industry. In this paper, a hardware efficient and low-latency CA-SCL polar decoder based on distributed sorting is first proposed. For path metric (PM) sorting of each level, a distributed sorting (DS) algorithm is proposed to reduce the comparison complexity from (L2) to (L) (L denotes list size), together with the latency from kL2to kL (k is a coefficient independent of L). Employing folding technique, the N-bit folding polar decoder can be implemented based on the basic √N-bit polar decoder. In addition, pipelining technique is employed to refine the timing issue resulting from folding. The CRC is performed for 2L candidate paths serially to reduce hardware cost. According to demo of (1024, 512) code on Altera Stratix V FPGA, the proposed CA-SCL decoders with L = 2 and adjustable L = 2, 4 consume 9% and 50% board resources, respectively. Decoding latencies (in terms of clock cycles) are 2, 528 and 4, 064, respectively. For L = 2 and 4, we can achieve the frame error rate (FER) of 10-2at the signal noise ratio (SNR) of 2.36 dB and 2.06 dB, respectively. Compared with the floating point results, the performance degradation is negligible. Thus, the proposed design is suitable and adjustable for different real-life scenarios.

In this paper, the successive cancellation (SC) heap polar decoding scheme is firstly proposed to reduce the complexity. Unlike SC list decoder which keepsLsame length paths, SC heap decoding stores different length paths in a heap and always decodes the global optimal path in the root. It has been strictly proved that SC heap decoding is superior to SC stack decoding because the time complexity of inserting new paths is only related to the height of the heap. Proposed SC heap decoding is a dynamic decoding scheme with robustness in various scenarios. Numerical results with binary-input additive white Gaussian noise channel (BI-AWGNC) show that SC heap decoding reduces 63.53% decoding complexity compared with SC list decoding on the same performance at SNR of 2.5 dB. A low-complexity hardware architecture for proposed SC heap decoder is also designed.

This paper proposes a selective AF-OFDM (Amplify-and-Forward, Orthogonal Frequency Division Multiplexing) relaying protocol, in which selective relaying policy is adequately utilized to improve the spectrum efficiency of cooperative multi-carrier transmission, and addresses the power minimization problem subject to a target quality of service (QoS) constraint for corresponding battery-operated systems. By transforming the original power minimization issue into a two-stage problem, i.e., a power loading subproblem and a selective relaying policy decision subproblem, an energy efficient power control (PC) technique is proposed. Specifically, the binary selective relaying policies are determined for each subcarrier based upon channel state information (CSI), while power loading can be mathematically solved by employing standard Lagrange techniques, leading to analytical solutions for individual transmit powers at the source and the relay. In order to further improve the energy efficiency, an independent \emph{min-min} relay selection policy is investigated by making use of available diversity of the multiple-relay channel. Numerical results illustrate the superiority of the proposed selective AF-OFDM relaying protocol and validate the efficiency of our proposed algorithms. It is shown that with PC, the proposed selective AF-OFDM relaying can significantly reduce the system power consumption, and the \emph{min-min} relay selection policy is more appropriate than the conventional \emph{max-min} strategy for our transmission protocol.

This paper considers a visible light system that serves the dual purpose of illumination and communication. We maximize the joint offset and power optimization in direct-current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) for visible light communications (VLC). We take both the optical and electrical power constraints into account. We analytically characterize the optimal solutions along with new insights on setting the direct current (DC) offset and information-carrying power in DCO-OFDM systems. We also investigate the relationship and impact of the optical and electrical power constraints, along with numerical results.

This manuscript develops an improved AF-OFDM (Amplify-and-Forward, Orthogonal Frequency Division Multiplexing) scheme where selective relaying policy is fully utilized to promote the spectrum efficiency of cooperative transmission, and presents an achievable rate maximizing resource allocation strategy subject to a sum-power constraint. The high computational complexity for optimization necessitates our investigation of suboptimal approaches. The proposed centralized algorithms can be implemented in a step-by-step manner. Specifically, the binary selective relaying policies are first decided for each subcarrier according to instantaneous or statistical channel state information. Then, relay selection might be conducted by those subcarriers who would like to choose a relay to assist their data transmission from network achievable rate maximization perspective, and finally power loading can be mathematically solved by employing standard Lagrange techniques. Numerical results are shown to illustrate the benefits of the improved AF-OFDM cooperative protocol with optimized resource allocation.

Hybrid ARQ transmissions are effective means for on-demand error correction in wireless networks against unpredictable channel distortions and interferences. By requesting retransmission of failed data packets upon detecting packet errors, receivers can integrate original and retransmitted packet signals for more effective packet detection and error correction. Often, only a small fraction of the packet bits is in error. For channels with sufficiently high capacity such as in MIMO wireless systems, it is typically unnecessary to reuse the entire channel for hybrid-ARQ retransmissions in order to correct the few remaining errors. To improve the wireless channel utility, we propose and investigate a shared hybrid ARQ (SHARQ) mechanism in MIMO systems where failed data can piggyback on new data frames over the diversity MIMO channel. To guarantee certain quality of HARQ retransmission, we design a linear transmit precoder based on channel state information at the transmitter and receiver to achieve a predetermined {minimum} signal-to-noise ratio (SNR) gain for the SHARQ signals by minimizing the transmission power. Our proposed SHARQ system takes advantage of a simple successive interference cancellation receiver to facilitate a simpler and better transmitter.

Recent works have established that MIMO systems optimized for Gaussian source signals may suffer unexpected performance loss when practical inputs are in fact discrete QAM sources. There is a practical need in the optimization of MIMO related systems of various networking scenarios to specifically target source signals of finite QAM alphabet. In this work, we investigate the precoding optimization of wireless two-hop non-regenerative three-node MIMO relay networks driven by finite-alphabet inputs. Exploiting a known optimal structure for the precoder at relay and a special convexity property, we propose an iterative two-step numerical optimization algorithm. This algorithm is a general solution, not only for arbitrary source signals but also for cooperative networks with or without direct link. Simulation results demonstrate substantial performance improvement by the new precoder over precoders optimized under the Gaussian input assumption.

This work investigates the optimization of power allocation for hybrid-ARQ (H-ARQ) retransmissions of non-Gaussian inputs over a bank of independent parallel Gaussian channels. We establish a general solution for maximizing generic transceiver objective utility functions that are monotonically non-decreasing and concave function with respect to the accumulated signal to noise ratio (SNR). Specifically, we investigate optimized solutions under two performance metrics, namely, the mutual information (MI) and the union bound of symbol error rate (UBSER) under maximal ratio combining (MRC) reception. We establish that efficient utilization of parallel channels in H-ARQ retransmissions requires sequential updating of signal-channel pairing as well as optimizing power allocation. Applying geometric analysis of power loading for H-ARQ retransmission, we show that for i.i.d. inputs that are not necessarily Gaussian, the optimum pairing policy should match signals of the lowest cumulative signal-to-noise ratio with channels of the best quality in each transmission, which is consistent with a similar result of , for Gaussian input signals. We further propose a generalized mercury/waterfilling algorithm for the optimal power assignment problem in H-ARQ. Simulation results illustrate substantial improvements over designs based on Gaussian input assumptions.

Interference alignment has emerged as new tool for achieving high capacity in multi-user and multi-channel wireless interference channels. Based on maximizing a degree of freedom (DOF) metric defined for asymptotic signal to noise ratio (SNR), interference alignment encounters limitations in practical applications because of limited SNR. In addition, perfect interference alignment requires strict antenna-user number condition which may not always hold true as user number increases. In this work, we address these two practical issues in interference alignment. We propose a new definition of interference alignment metric designed to assess the effectiveness of non-ideal interference alignment. We apply the new interference alignment metric to investigate the "best effort" interference alignment in multi-user OFDM systems with limited SNR and limited dimension (subcarriers).