The Optimal Power Allocation for Sum Rate and Energy Efficiency of Full-Duplex Two-Way Communication Network

Full-duplex (FD) transmission holds a great potential of improving the sum data rate of wireless communication systems. However, the self-interference introduced by the full-duplex transmitter brings a big challenge to enhance the energy efficiency. This paper investigates the power allocation problem in a full-duplex two-way (FDTW) communication network over an OFDM channel, aiming at improving the sum data rate and energy efficiency. We first characterize the sum rate and energy efficiency achieved in a single-carrier FDTW system. The optimal transmit power that achieves the maximal sum data rate is presented. The energy efficiency maximization problem is solved by using fractional programming. Then we further formulate sum rate and energy efficiency maximization problem in a multi-subcarrier FDTW system. In particular, the sub-optimal transmit power allocation which achieves a decent sum rate improvement is found by using a proposed iterative algorithm. By combining the iterative algorithm and fractional programming, we further maximize the energy efficiency of the multi-subcarrier system. With our proposed algorithm, we can easily obtain an optimal transmit power that approximates the global optimal solution. Simulation results show that using the obtained optimal transmit power allocation algorithm can significantly improve the sum rate and energy efficiency in both single-carrier and multi-subcarrier systems.     

Energy-Efficient Optimization for Energy-Harvesting-Enabled mmWave-UAV Heterogeneous Networks

Energy Harvesting (EH) is a promising paradigm for 5G heterogeneous communication. EH-enabled Device-to-Device (D2D) communication can assist devices in overcoming the disadvantage of limited battery capacity and improving the Energy Efficiency (EE) by performing EH from ambient wireless signals. Although numerous research works have been conducted on EH-based D2D communication scenarios, the feature of EH-based D2D communication underlying Air-to-Ground (A2G) millimeter-Wave (mmWave) networks has not been fully studied. In this paper, we considered a scenario where multiple Unmanned Aerial Vehicles (UAVs) are deployed to provide energy for D2D Users (DUs) and data transmission for Cellular Users (CUs). We aimed to improve the network EE of EH-enabled D2D communications while reducing the time complexity of beam alignment for mmWave-enabled D2D Users (DUs). We considered a scenario where multiple EH-enabled DUs and CUs coexist, sharing the full mmWave frequency band and adopting high-directive beams for transmitting. To improve the network EE, we propose a joint beamwidth selection, power control, and EH time ratio optimization algorithm for DUs based on alternating optimization. We iteratively optimized one of the three variables, fixing the other two. During each iteration, we first used a game-theoretic approach to adjust the beamwidths of DUs to achieve the sub-optimal EE. Then, the problem with regard to power optimization was solved by the Dinkelbach method and Successive Convex Approximation (SCA). Finally, we performed the optimization of the EH time ratio using linear fractional programming to further increase the EE. By performing extensive simulation experiments, we validated the convergence and effectiveness of our algorithm. The results showed that our proposed algorithm outperformed the fixed beamwidth and fixed power strategy and could closely approach the performance of exhaustive search, particle swarm optimization, and the genetic algorithm, but with a much reduced time complexity.     

Multi-Model Communication and Data Assimilation for Mitigating Model Error and Improving Forecasts

Models for weather and climate prediction are complex, and each model typi-cally has at least a small number of phenomena that are poorly represented, such as perhaps the Madden-Julian Oscillation (MJO for short) or El Ni\~{n}o-Southern Oscillation (ENSO for short) or sea ice. Furthermore, it is often a very challenging task to modify and improve a complex model without creating new deficiencies. On the other hand, it is sometimes possible to design a low-dimensional model for a particular phenomenon, such as the MJO or ENSO, with significant skill, although the model may not represent the dynamics of the full weather-climate system. Here a strategy is proposed to mitigate these model errors by taking advantage of each model''s strengths. The strategy involves inter-model data assimilation, during a forecast simulation, whereby models can exchange information in order to obtain more faithful representations of the full weather-climate system. As an initial investigation, the method is examined here using a simplified scenario of linear models, involving a system of stochastic partial differential equations (SPDEs for short) as an imperfect tropical climate model and stochastic differential equations (SDEs for short) as a low-dimensional model for the MJO. It is shown that the MJO prediction skill of the imperfect climate model can be enhanced to equal the predictive skill of the low-dimensional model. Such an approach could provide a route to improving global model forecasts in a minimally invasive way, with modifications to the prediction system but without modifying the complex global physical model itself.     

体相位全息光栅式波分复用器的研究

利用体相位全息光栅的优良特性,研制光栅式密集型波分复用器(DWDM)。准直后的信道波长通过体相位全息光栅两次衍射,在焦面上实现信道波长的分复用。阐述了体相位全息光栅的独特结构特点,给出了体相位全息光栅式密集型光波分复用器件的原理图,计算出各个信道的位置及间隔,用Zemax仿真出设计模型。相比于薄膜滤光片式器件而言,具有许多独特的优良特性,能够实现更密集更多信道数量的分复用。     

差分相移键控色散管理孤子多扰动系统的相位抖动

差分相移键控(DPSK)调制方式和色散管理孤子传输方式的结合能抵制噪声和非线性损伤,在高速(40 Gbit/s以上)多信道系统中具有突出的优点。采用变分法分析了多波长信道的放大自发辐射(ASE)噪声、信号间的非线性串扰(ISI)等多种扰动因素引起差分相移键控色散管理孤子系统的均方根相位抖动,给出了扰动的作用区域以及各扰动的大小。研究发现,放大自发辐射引起的抖动与传输距离成三次方的关系,而交叉相位调制(XPM)引起的抖动与距离近似成线性关系。通过优化选择色散管理图强度范围1.5~3.5,各种扰动得到了抑制,而以放大自发辐射扰动抑制为最大,此时要远低于交叉相位调制引起的抖动,然后分别是交叉相位调制-放大自发辐射扰动和交叉相位调制,从而波分复用系统主要来自于增加信道数这一客观限制。     

自启动的非归零/归零码和光电时钟信号发生器及码型转换

采用双波长注入一包含伪随机码发生器与相位调制器的光电振荡器可以同时得到非归零(NRZ)码,归零(RZ)码以及光,电时钟信号输出。该方案使用了光域耦合的双环路结构,在不增加有源器件的条件下实现边模抑制。相位调制器用于反馈调制并同时实现占空比可调的非归零码到归零码的转换。双波长的注入排除了编码信号在振荡器中引入的非时钟频率成分。实验给出了10 Gb/s工作速率下的结果,得到了抖动为637 fs的光信号输出。转换得到的归零码信号占空比约为33%。输出电时钟信号的相位噪声在频偏10 kHz处为-109 dBc/Hz,边模抑制比为58 dB。     

光纤中高斯型伪随机序列码偏振度的理论分析和实验研究

推导了准单色光波情况下高斯脉冲伪随机序列偏振度的简洁数学表达式.理论分析结果表明,偏振度与差分群延迟之间的关系与线路啁啾和光纤色散无关,并且此关系可以由光信号频谱半宽度Δω和分光比γ唯一确定.用10 Gbit/s 7级m序列归零码进行的实验表明:实验结果与理论推导基本一致,从而验证了推导公式的正确性.     

四阶色散对飞秒高斯脉冲传输的影响

推导了考虑二、三、四阶色散的高斯脉冲传输方程;利用计算机数值模拟的方法,研究了四阶色散(FOD)对飞秒高斯脉冲在单模光纤中传输特性的影响.模拟结果显示：只有在入射脉冲宽度窄到飞秒量级时,即对应传输速率很高的情况下,FOD对脉冲的影响才明显;FOD导致脉冲形状发生了畸变,畸变特点不同于二、三阶色散;随着初始脉宽逐渐减小,FOD所致的飞秒高斯脉冲畸变经历了一个脉冲仅仅展宽,到展宽脉冲的两翼出现“底座”,到展宽脉冲的两翼出现具有微小振荡“底座”的变化过程.     

用于WDM光网络的一种低串扰无损耗光开关矩阵

提出了一种低串扰无损耗的光开关矩阵.该结构是在扩展Benes（DB）结构的基础上通过改进得到的称为改进的扩展Benes（IDB）结构,并通过进一步的改进得到各级改进的扩展Benes（GIDB）结构.理论分析了IDB结构和GIDB结构中串扰产生的机理和对信号的影响,比较了几种结构的信噪比和光交换容量之间的关系.发现随着光交换规模的扩大,GIDB结构相对于DB结构信噪比明显提高.实验研究了4×4的IDB、GIDB结构中串扰引起的误码率降低以及眼图的恶化情况.结果表明GIDB结构能有效减少串扰的影响.     

基于高阶累计量的大气光通信自适应信号处理

针对强湍流信道下信号衰落的特点,分析了对数正态分布模型与K分布模型的适用范围.基于K分布模型建立大气光通信接收信号模型,并给出了自适应最优门限检测方法.采用四阶和六阶累计量对强湍流信道参量进行估计,采用二阶累计量对其它高斯噪音进行估计,得到K分布参量及高斯噪音统计量的预测值,实现自适应门限更新.基于Monte Calro算法进行仿真,给出了门限更新算法对通信系统误码率的影响,同时分析了信号采样率对估计参量偏差的影响.计算表明,在强湍流情况下,大气光通信系统的误码率性能得到极大的改善,优于基于MLSD检测的接收机.