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.

Dynamic Random Access Channel Allocation Scheme Based on the Pseudo-Bayesian Algorithm in OFDMA System

Random Access Channel (RACH) is an uplink contention-based transport channel usually used for initial channel access, bandwidth request, etc. How to use RACH resources effectively is very important in wireless communication system. In this paper, a dynamical RACH allocation scheme is proposed for Orthogonal Frequency-Division Multiple Access (OFDMA) systems. Based on the Pseudo-Bayesian algorithm, this mechanism predicts the number of RACHs for the next frame according to the current load. A new dynamic RACH assignment algorithm and an adaptive access probability method are adopted by the proposed scheme to improve the utilization ratio of RACH resources and increase the successful access rate. Numerical simulation shows that the proposed strategy achieves both improvement in the utilization ratio of RACHs and reduction in the access delay compared with other RACH allocation schemes.

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.

An Achievable Rate Region for the Asynchronous Multiple Access Channel with Feedback

An achievable rate region for the asynchronous multiple access channel with feedback is established through the use of superposition coding, list decoding and time sharing. The calculation results demonstrate that lack of synchronization does not affect the achievable rate region when the code block length tends to infinity, and that if the length of the code word is finite, especially not sufficiently larger than a fixed maximal delay, the asynchronization will cause a loss of the rate region. The amount of such a loss with its explanation for the reason is given, and the difference between the losses for the asynchronous multiple access channel with and without feedback is also discussed in this paper.

Cooperative multiple access channels: Achievable rates and optimal resource allocation

We investigate the multiple access channels （MAC） where sources can cooperate via half-duplex relaying and refer to it as cooperative MAC channels （CMAC）. Assuming perfect channel state information （CSI） at the transmitters and the receivers, we determine the bounds on the achievable rate region of a Gaussian CMAC channel and an inner bound on the outage capacity region of a fading CMAC channel. Based on superposition modulation, a half-duplex cooperative relay scheme with optimal resource allocation is proposed to achieve the bounds of capacity region. Analytical results and simulation results show that the achievable rate region of a Gaussian CMAC channel is larger than that of a Gaussian MAC channel with direct transmission （DT） schemes. But they have the same achievable sum rate. Moreover, the proposed scheme can provide higher outage capacity region than DT schemes in a fading MAC channel due to the fact that sources can share the resources with each other to reduce outages.

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.

Semi-Blind Pilot-Aided Channel Estimation in Uplink Cloud Radio Access Networks

In this paper,a quasi-Newton method for semi-blind estimation is derived for channel estimation in uplink cloud radio access networks(C-RANs).Different from traditional pilot-aided estimation,semi-blind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel.An initial channel state information(CSI) obtained by least-squared(LS) estimation is needed in semi-blind estimation.BFGS(Brayben,Fletcher,Goldfarb and Shanno) algorithm,which employs data as well as pilot symbols,estimates the CSI though solving the problem provided by maximum-likelihood(ML) principle.In addition,mean-square-error(MSE) used to evaluate the estimation performance can be further minimized with an optimal pilot design.Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols,which demonstrates the estimation accuracy and spectral efficiency are both improved by semiblind estimation for C-RANs.

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.

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.

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.

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.

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.

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%。

双语者的词语理解认知机制研究

该研究旨在为双语者的研究提供一个更全面的视角来理解其词语理解认知机制。以双语者心理词库表征模型、双语者的语言神经机制、双语者的语言表征理论三方面为切入点,采用对比法和归纳法,对近年来关于双语者语言认知神经机制的研究进行了全面的综述,揭示了双语者大脑在语言处理方面的独特性;对双语者心理词库三大模型和语言表征相关理论进行了详细全面梳理,双语者心理词库表征模型主要分为语音中介假设理论、直接通达假设理论、双通道假设理论。双语者的语言表征相关理论包括共同存贮理论、独立存贮理论、词汇连接模型、概念调节模型及神经生物学模型。通过对比和分析,发现双语者较单语者具有独特的语言认知机制。

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。

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。