Journal on Communications ›› 2018, Vol. 39 ›› Issue (2): 149-163.doi: 10.11959/j.issn.1000-436x.2018033
• Comprehensive Reviews • Previous Articles Next Articles
Xianzhong XIE,Ying LUO,Ke YAN,Jiujiu CHEN
Revised:
2018-01-18
Online:
2018-02-01
Published:
2018-03-28
Supported by:
CLC Number:
Xianzhong XIE,Ying LUO,Ke YAN,Jiujiu CHEN. Recent advances and future challenges of four key resources cooperation in cognitive radio network[J]. Journal on Communications, 2018, 39(2): 149-163.
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技术结合 | 优势 | 主要参考文献 |
1) 能量收集、协作中继(EH+IC+SS) | 次用户同时从主用户信号收集能量(EH)、帮助主用户中继其信号(IC),并获得自己的传输机会(SS)和能量补偿;同时主用户还可从次用户中继传输阶段收集能量(EH) | 主用户信号收集能量:文献[31,32] |
三维资源协作利用:频谱协作、干扰收集能量、中继协作传输信息 | 其他RF信号收集能量:文献[33~36] | |
2) 能量收集、不协作中继(EH+SS) | 开始次用户进行频谱检测,若主用户传输信息,则次用户从主用户信号收集能量(EH);若主用户空闲,则次用户传输信息(SS),这时主用户也可以从次用户信号收集能量(EH) | 主用户信号收集能量:文献[37~55] |
其他RF信号收集能量:文献[56~77] | ||
二维资源协作利用:频谱协作、干扰收集能量 | 2种以上供能(能量收集的能源和传统电网/电池的能源):文献[78~80] | |
3) 能量协作、能量收集(EC+EH+ SS) | 在CR/SS网络中,能量收集(EH)受多种因素影响和随机变化,通过主次用户之间能量传输,实现收集能量的协作/共享(EC),进一步提高能量利用率三维资源协作利用:频谱共享协作、干扰收集能量、能量共享协作 | 一个频率协作/共享:文献[81~88] |
2个频率协作/共享:文献[89] | ||
4) 能量收集、能量协作、协作中继(EC+EH+IC+SS) | 在能量收集(EH)和协作中继(IC)结合优势的基础上,进行主次用户间能量协作(EC),进一步提高能量效率,实现绿色通信 | 文献[90~93] |
四维资源协作利用:频谱共享协作、干扰收集能量、中继协作传输信息、能量共享协作 |
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文献 | 优化目标 | 主要模型与方法 | 能量收集类型 | 能量供应方式 |
文献[37~39] | 频谱检测—能量收集(存储)—数据传输3个阶段处理,最大化次用户吞吐量或系统吞吐量 | 部分可观测马尔可夫决策过程,折中收集时间、感知时间、传输时间 | 主用户信号收集能量(主用户信号外的RF能量收集对讨论没有大影响) | 单一能量供应,节点整体能量消耗不超过收集的能量 |
文献[40~42] | 若主用户没有信号传输,则次用户传输分组;否则,从主用户信号中收集能量;最大化次用户吞吐量 | 信道状态的排队模型,机器学习算法,最优信道接入策略 | (同上) | (同上) |
文献[43~45] | 设计适合的随机接入策略(接入概率),最大化平均业务速率 | 多分组接收模型(MPR),分析能量到达率、传输迟延、MPR 能力对接入性能和业务速率的影响 | (同上) | (同上) |
文献[46~50] | 在能量约束下和主用户检测约束下,最大化次用户可用吞吐量 | 蜂窝网络中认知 D2D 用户模型,随机几何方法,最优信道接入策略 | (同上) | (同上) |
文献[51~55] | 在主用户 QoS 约束下,最大化收集能量 | 随机几何方法,优化能量收集、吞吐量、检测时间、截断概率之间的关系 | (同上) | (同上) |
文献[56~61] | 最大化系统吞吐量,平衡能量有效性和频谱有效性 | 马尔可夫决策过程(MDP),设计帧结构和次用户频谱接入方案 | 以其他RF信号收集能量为主 | 单一能量供应,节点整体能量消耗不超过收集的能量 |
文献[62~68] | 频谱检测—能量收集(存储)—数据传输3个阶段处理,最大化次用户吞吐量或系统吞吐量 | 过去和现在观测信息代替能量收集的预测值,非线性整数方法,优化能量到达率、能量存储率、检测概率 | (同上) | (同上) |
文献[69~73] | 次用户传输端以时分方式处于等待模式和忙模式,保证主用户 QoS 下最大化吞吐量 | 隐输入马尔可夫模型,优化信道模式选择和接入策略 | (同上) | (同上) |
文献[74~77] | 针对认知无线电传感网络,考虑能量状态变化和能量消耗概率,优化能量管理、频谱管理和资源分配 | 马尔可夫电池模型,基于李雅普诺夫优化将效用优化模型分解为能量管理、频谱管理和资源分配3个子问题 | (同上) | (同上) |
文献[78~80] | 整体能量消耗不能超过 2 种能量总和,在截断概率约束下最大化加权和速率 | 随机几何模型和独立同分布的泊松点过程,优化信道分配、传输时间、传输功率 | 主用户信号及其他RF信号收集能量 | 2 种以上供能,包括能量收集的能源和传统电网/电池的能源 |
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文献 | 能量协作方式 | 能量收集类型 | 模型与优化方法 |
文献[81] | 一个频率协作 | 多个天线,功率分流与时间交换收集能量 | 一个次用户对,2 个阶段能量协作和信息协作,和速率优化与波束成形的相应算法 |
文献[82~84] | — | 多个天线,功率分流收集能量 | 多个次用户对,3个阶段能量协作和信息协作,和速率优化与波束成形相应算法,分析次用户接入策略 |
文献[85,86] | — | 主用户信号及其他RF信号收集能量 | 一个次用户对,2种能量共享方案,在主用户吞吐量和次用户能量收集约束下最大化容量 |
文献[87,88] | — | 主用户信号及其他RF信号收集能量 | Underlay认知网络,次用户同时传递能量和信息,优化功率传递策略和截断概率 |
文献[89] | 2个频率(正交)协作 | 主用户信号及其他RF信号收集能量 | 结合比例公平性,基于总费用最小给出了同时频谱和能量协作方案 |
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