Designing cost-effective network-on-chip by dual-channel access mechanism

A dual-channel access mechanism to overcome the drawback of traditional single-channel access mechanism for network-on-chip （NoC） is proposed. In traditional single-channel access mechanism, every Internet protocol （IP） has only one chan- nel to access the on-chip network. When the network is relatively idle, the injection rate is too small to make good use of the network resource. When the network is relatively busy, the ejection rate is so small that the packets in the network cannot leave immediately, and thus the probability of congestion is increased. In the dual-channel access mechanism, the injection rate of IP and the ejection rate of the network are increased by using two optional channels in network interface （NI） and local port of routers. Therefore, the communication performance is improved. Experimental results show that compared with traditional single-channel access mechanism, the proposed scheme greatly increases the throughput and cuts down the average latency with reasonable area increase.

Hybrid Channel Access Mechanism Based on Coexistence Scenario of NR-Unlicensed

With the rapid development of 5G NR(New Radio),the explosive increment of traffic amount is calling the utilization of unlicensed band.3GPP has proposed LAA(Licensed Assisted Access)to use LTE in unlicensed band and pointed out that NR-U(NR-Unlicensed)can reuse most designs of it.However,the existing channel access mechanism of LAA is conservative under the coexistence scenario of NR-U,which leads to the waste of time resource.To address the problem this paper proposes a hybrid channel access mechanism to take advantage of the LBT(Listen-Before-Talk)mechanism of LAA when channel is quite busy and transmit directly with reduced power when it is relatively idle.The channel busy degree is judged by a series of periodically updated adaptive thresholds.System-level simulation verifies that under the coexistence scenario of NR-U the proposed mechanism can achieve higher UPT(User Perceived Throughput)and lower delay than other channel access mechanisms.

Cross-Layer Framework for Fine-Grained Channel Access in Next Generation High-Density Wi Fi Networks

Densely deployed Wi Fi networks will play a crucial role in providing the capacity for next generation mobile internet. However, due to increasing interference, overlapped channels in Wi Fi networks and throughput efficiency degradation, densely deployed Wi Fi networks is not a guarantee to obtain higher throughput. An emergent challenge is how to effi ciently utilize scarce spectrum resources, by matching physical layer resources to traffi c demand. In this aspect, access control allocation strategies play a pivotal role but remain too coarse-grained. As a solution, this research proposes a flexible framework for fine-grained channel width adaptation and multi-channel access in Wi Fi networks. This approach, named SFCA(Subcarrier Fine-grained Channel Access), adopts DOFDM(Discontinuous Orthogonal Frequency Division Multiplexing) at the PHY layer. It allocates the frequency resource with a subcarrier granularity, which facilitates the channel width adaptation for multi-channel access and thus brings more fl exibility and higher frequency efficiency. The MAC layer uses a frequencytime domain backoff scheme, which combines the popular time-domain BEB scheme with a frequency-domain backoff to decrease access collision, resulting in higher access probability for the contending nodes. SFCA is compared with FICA(an established access scheme)showing significant outperformance. Finally we present results for next generation 802.11 ac Wi Fi networks.

Web services interface to EPICS channel access

Web services is used in Experimental Physics and Industrial Control System (EPICS).Combined with EPICS Channel Access protocol,Web services' high usability,platform independence and language independence can be used to design a fully transparent and uniform software interface layer,which helps us complete channel data acquisition,modification and monitoring functions.This software interface layer,a cross-platform of cross-language, has good interopcrability and reusability.

Network-Load Aware Adaptive Channel Access Control for WLAN

Wireless local area network (WLAN) brings us a low cost and high bandwidth experience and thus plays a critically important role in current/future networks to support high-rate transmissions. To better provide quality-of-service (QoS) for WLAN users, we in this paper propose an improved scheme called “A-EDCA”(adaptive EDCA), based on enhanced distributed channel access (EDCA) of IEEE 802.11e under the infrastructure mode. Our proposed scheme aims at efficiently adapting the transmission over WLAN to the time-varying network conditions and mitigating the competition ability unfairness between access point (AP) and non-AP stations (STAs). Specifically, all non-AP STAs adaptive-ly modify the contention window based on the network condition. Moreover, AP skips the backoff phase by setting its backoff counter as zero when non-AP STA completes transmission successfully to relieve the unfairness. At last, simulation results demonstrate the effectiveness of the proposed approach.

A Deep Reinforcement Learning-Based Technique for Optimal Power Allocation in Multiple Access Communications

Formany years,researchers have explored power allocation(PA)algorithms driven bymodels in wireless networks where multiple-user communications with interference are present.Nowadays,data-driven machine learning methods have become quite popular in analyzing wireless communication systems,which among them deep reinforcement learning(DRL)has a significant role in solving optimization issues under certain constraints.To this purpose,in this paper,we investigate the PA problem in a k-user multiple access channels(MAC),where k transmitters(e.g.,mobile users)aim to send an independent message to a common receiver(e.g.,base station)through wireless channels.To this end,we first train the deep Q network(DQN)with a deep Q learning(DQL)algorithm over the simulation environment,utilizing offline learning.Then,the DQN will be used with the real data in the online training method for the PA issue by maximizing the sumrate subjected to the source power.Finally,the simulation results indicate that our proposedDQNmethod provides better performance in terms of the sumrate compared with the available DQL training approaches such as fractional programming(FP)and weighted minimum mean squared error(WMMSE).Additionally,by considering different user densities,we show that our proposed DQN outperforms benchmark algorithms,thereby,a good generalization ability is verified over wireless multi-user communication systems.

Channel Estimation for Full-Duplex Relay Transmission in Cloud Radio Access Networks

Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information(CSI). In this paper,the channel estimation issue in FD amplify-andforward relay networks is considered,where the training-based estimation technique is adopted. Firstly,the least square(LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination(SRD) channel and relay loop-interference(LI) channel in order to assist destination in performing data detection. Secondly,both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally,simulation results demonstrate the effectiveness of both composite and individual channel estimation,and the presented ML method can achieve lower MSEs than LS solution.

New strategies for collision resolution of multi-access channel

The truncated binary exponential back-off algorithm is one of the most effective methods applied in collision resolution process of random multi-access channel.In this study,two new strategies are presented to improve the capability of the truncated binary exponential back-off algorithm.In the new strategies,the sizes of the initial window size or the operating window sizes are adjusted dynamically,which always bring a significant improvement for the self-adaptability of the original algorithm.A series of experiments are simulated and the results verify that the new strategies can make the implementation more stable and effective than the original algorithm.

Joint Design of Coalition Formation and Semi-Blind Channel Estimation in Fog Radio Access Networks

Coordinated signal processing can obtain a huge transmission gain for Fog Radio Access Networks(F-RANs).However,integrating into large scale,it will lead to high computation complexity in channel estimation and spectral efficiency loss in transmission performance.Thus,a joint cluster formation and channel estimation scheme is proposed in this paper.Considering research remote radio heads(RRHs)centred serving scheme,a coalition game is formulated in order to maximize the spectral efficiency of cooperative RRHs under the conditions of balancing the data rate and the cost of channel estimation.As the cost influences to the necessary consumption of training length and estimation error.Particularly,an iterative semi-blind channel estimation and symbol detection approach is designed by expectation maximization algorithm,where the channel estimation process is initialized by subspace method with lower pilot length.Finally,the simulation results show that a stable cluster formation is established by our proposed coalition game method and it outperforms compared with full coordinated schemes.

MULTI-CHANNEL TRANSMISSION STRATEGY FOR DYNAMIC SPECTRUM ACCESS

Cognitive radio is a promising technology that deals with the scarcity of radio spectrum. In this paper, we propose a new multi-channel transmission strategy for dynamic spectrum access in cognitive radio network. Starting with the model of spectrum activities, we present the multi-channel transmission strategy which has primary user's protection mechanism to improve the spectrum efficiency and study its performance under perfect and imperfect sensing. Numerical example results reveal that the performance of the proposed strategy has the superiority with respect to capacity performance of cognitive users and the protection of primary users.

基于近似消息传递的NOMA系统信道和脉冲噪声联合估计方法

针对非高斯脉冲噪声背景下的非正交多址接入(non-orthogonal multiple access,NOMA)系统的信道估计问题,利用信道和脉冲噪声的稀疏特性,提出一种基于近似消息传递的信道和脉冲噪声联合估计方法。首先构建全子载波的压缩感知方程,然后基于稀疏贝叶斯学习理论提出一种信道、脉冲噪声和数据符号的联合估计优化问题。为解决这一超参量非线性非凸问题,设计了一种基于高斯广义近似消息传递和稀疏贝叶斯学习理论的期望最大化实现算法。仿真结果表明,与基于期望最大化的稀疏贝叶斯学习方法相比,所提算法在信道和脉冲噪声估计的均方误差、误码率等方面性能虽略有下降,但算法复杂度降低了1个数量级。

彩超定位下经皮肾镜取石术通道丢失后再次建立的临床分析

为评价经皮肾镜取石术(PCNL)在彩超定位穿刺通道丢失后借助X线引导再次建立通道的手术安全性和可行性,收集莆田学院附属医院自2020年7月至2023年12月行彩超定位下PCNL患者情况,比较彩超定位下建立经皮肾通道且术中无通道丢失、彩超定位下建立经皮肾通道失败或术中通道丢失后在X线引导下重建经皮肾通道这两类患者的结石清除率、手术及住院时间、术后并发症发生率等。结果发现:两类患者在结石清除率和术后出血行介入栓塞、脓毒血症发生率方面差异无统计学意义(P>0.05),在手术时间、住院时间和术后发热、肾周积液发生率方面差异有统计学意义(P<0.05)。得出如下结论:行彩超定位下PCNL通道丢失后,利用X线引导可有效再次建立通道,结石清除率高,无严重手术并发症,是重建经皮肾通道的可靠选择。

基于空中计算CoMAC架构的不同计算场景叠加符号判决算法

本文研究不同场景下基于空中计算的多址信道计算(CoMAC)架构的覆盖符号决策算法。首先,从理论上分析了XOR、ADD、MOD三种场景中加性高斯白噪声(AWGN)多址接入信道下叠加符号的概率密度分布,提出了一种基于先验概率的最优门限判决策略。其次,推导了系统最优门限及对应误码率的理论表达式。最后,通过仿真验证了不同信噪比、传感器节点个数及先验概率对于该门限判决方案的鲁棒性和可靠性的影响。与通信计算相分离的传统方案相比,空中计算判决方案具有更好的检测性能,为多址接入信道下的信号识别提供了新的参考方案。

论循环买卖中的通道方责任

循环买卖被认定为名为买卖实为借贷后,通道方是否应该对资金提供方承担赔偿责任在实践中存在较大分歧。在名义上的买卖关系和实际上的借贷关系中,通道方具有多种法律地位;在不同交易结构中,通道方又可以分为多种类型。通道方在一定范围内对资金提供方承担赔偿责任有助于遏制循环买卖的发生,有助于贯彻金融强监管和国资委关于禁止融资性贸易的要求。借贷关系无效时通道方构成第三人缔约过失责任;借贷关系有效时,直接与资金提供方订立买卖合同的通道方应当按照过错程度在一定范围内就买卖合同无效承担缔约过失责任,未直接与资金提供方订立买卖合同的通道方应当就买卖合同无效承担第三人缔约过失责任。向资金提供方作出还款承诺的下游通道方,构成借贷关系的债务加入人,应当与资金需求方共同向资金提供方承担连带责任。

NOMA增强型D2D组的鲁棒资源分配算法

为提高非正交多址接入(non-orthogonal multiple access,NOMA)增强型设备到设备(device-to-device,D2D)组链路的鲁棒性和能效,考虑非理想信道状态信息(channel station information,CSI),提出一种能效优化的鲁棒资源分配算法.首先,在保证子信道分配、蜂窝用户和D2D组最小速率以及D2D组最大传输功率约束下,建立最大最小鲁棒能效模型;其次,考虑最坏情况法将信道不确定性建模为有界信道估计误差,并用泰勒级数展开式、凸松弛、变量转换法将原多变量耦合问题转化为凸优化问题;最后,用拉格朗日对偶理论求解.仿真结果表明,所提出的算法将传输速率控制在最低速率阈值以上,具有良好的鲁棒性,与其他算法相比能效提高了8.3%.

基于硬件损伤和非完美CSI的IRS辅助NOMA网络鲁棒传输算法

为提升非正交多址接入(NOMA,non-orthogonal multiple access)网络的鲁棒性并减少其能量消耗,考虑了收发器的硬件损伤(HWI,hardware impairment)和非完美的信道状态信息(CSI,channel state information),提出了智能反射面(IRS,intelligent reflecting surface)辅助的NOMA网络传输功率最小化算法。考虑了用户服务质量(QoS,quality of service)约束、串行干扰消除约束以及IRS的反射相移约束,基于HWI和非完美CSI建立了基站主动波束成形和IRS被动波束成形联合优化问题模型。为求解该非凸优化问题,首先利用线性近似和S-Procedure方法对QoS约束进行转换,然后将优化问题分解为两个子问题,并且利用逐次凸逼近(SCA,successive convex approximation)方法求解主动波束成形子问题,利用惩罚凸凹过程算法求解被动波束成形子问题,最后利用交替优化将子问题交替迭代得到最终解。仿真结果表明,在传输功率方面,所提算法比正交多址鲁棒算法降低了17.05%;在系统鲁棒性方面,所提算法相较于HWI鲁棒算法和CSI鲁棒算法,分别提升了20.69%和31.14%。

基于可靠性分析的避震疏散通道通达性评价

城市避震疏散通道的震后通达性直接关系到能否在第一时间安全转移受灾群众及顺利开展救灾工作。以济南市杆石桥街道为研究对象,考虑到震中沿街建筑的倒塌影响,借助空间句法进行道路系统的抗震可靠性和通达性评价,并提出优化建议。经分析,杆石桥街道建筑密度较高,高层建筑多布局于道路交叉口,均对街区道路的避震疏散功能有一定威胁,且老城区本身避震疏散网络规划不足、存在较多救灾“死角”。随着城市的发展和更新,大多中心城区的规划年代久远,原有避震疏散网络已不能满足需求,近年来自然灾害频发,中心城区的避震疏散通道亟待进行整体评价及优化。

空间信息网的Ka频段非正交多址接入中继系统

针对深空通信的系统信息传输效率低,时延长的问题,文中设计一种空间信息网的Ka频段非正交多址接入中继系统,推导出中继卫星配备单天线情况下的中断概率和遍历系统容量等关键指标的解析表达式,提出的非正交多址接入中继系统在节约一半传输时间条件下,达到与正交多址接入系统相同遍历系统容量时所需的功率分配方案。通过仿真,验证了该方案的可行性。

工业5G的非授权频段多优先级动态接入方法

为实现工业5G在非授权频段的高实时、高可靠无线通信,提出了一种多优先级的动态信道接入方法,以满足异构工业任务的按需通信。该方法通过对多种无线网络共享的非授权频段进行实时信道监听,可以根据信道占用率动态切换信道接入方式,包括随机接入和确定性接入。其中,根据异构工业任务的实时性要求,定义了多种接入优先级,并确定合适的竞争和退避时间窗口。仿真结果表明,在工业多设备接入场景下,所提方法的信道传输可靠性达到99.99%,并且实时性比WiFi的载波侦听多路接入/碰撞避免机制(Carrier Sense Multiple Access with Collision Avoidance,CSMA/CA)和授权辅助接入(Licensed Assisted Access,LAA)的先听后说(Listen before Talk,LBT)机制分别提升了24.7%和46.3%。