本文選題：認(rèn)知無線電 + 動態(tài)頻譜接入�。� 參考：《哈爾濱工業(yè)大學(xué)》2014年博士論文

【摘要】：認(rèn)知無線電概念是現(xiàn)代通信發(fā)展歷程上的一個革命性觀點，在過去十年中一直受到廣泛的關(guān)注。通過軟件定義無線電，認(rèn)知無線電可以察覺信道狀態(tài)、能源效率、帶寬可用性、地理位置、頻譜使用、網(wǎng)絡(luò)連接性等等。并且，通過與無線環(huán)境和其他用戶的交互作用，認(rèn)知無線電可以自適應(yīng)地改變其操作參數(shù)從而達(dá)到最佳的頻譜使用率。此外，認(rèn)知無線電概念還被引入到下一代無線和移動計算系統(tǒng)中用來提高頻譜的使用效率。 動態(tài)頻譜接入是認(rèn)知無線電的關(guān)鍵技術(shù)，采用該技術(shù)認(rèn)知無線電用戶可以伺機接入無線電頻譜。認(rèn)知用戶在接入無線電頻譜過程對其他用戶產(chǎn)生的干擾是一個值得研究的問題。該問題可以從三個方面進行研究。一、授權(quán)用戶可以制定規(guī)則來指導(dǎo)認(rèn)知用戶的頻譜接入，減少來自認(rèn)知用戶的干擾；二、認(rèn)知用戶通過頻譜感知避免對授權(quán)用戶或其他認(rèn)知用戶造成干擾；三、認(rèn)知用戶之間通過頻譜競爭或合作來共享頻譜資源。本文從上述三個方面研究了認(rèn)知用戶頻譜競爭與干擾避免的問題，并根據(jù)博弈理論和優(yōu)化算法，提出了解決的方案。 首先，從授權(quán)用戶角度出發(fā)，針對認(rèn)知用戶與授權(quán)用戶頻譜共享中的干擾問題，提出基于干擾補償定價的認(rèn)知周期優(yōu)化算法和基于定價機制的混合頻譜接入管理算法。針對認(rèn)知用戶在授權(quán)用戶隨機出現(xiàn)情況下無法及時退出所導(dǎo)致的干擾問題，傳統(tǒng)的認(rèn)知周期優(yōu)化算法以最大化認(rèn)知用戶的平均吞吐量為目標(biāo)，忽略授權(quán)用戶的體驗。基于干擾補償定價的認(rèn)知周期優(yōu)化算法使授權(quán)用戶參與制定認(rèn)知周期，根據(jù)授權(quán)用戶的頻譜利用率調(diào)整認(rèn)知周期時長，并且平衡認(rèn)知用戶的干擾概率和信道空閑率。基于定價機制的混合頻譜接入管理算法針對認(rèn)知用戶混合頻譜接入時頻譜接入方式對授權(quán)用戶造成的不同影響。該算法可以根據(jù)授權(quán)用戶頻譜利用率調(diào)整認(rèn)知用戶選擇頻譜Overlay模式和選擇頻譜Underlay模式的頻譜接入價格，通過頻譜接入價格影響認(rèn)知用戶對這兩種頻譜接入方式的選擇。 其次，從認(rèn)知用戶角度出發(fā)，針對認(rèn)知用戶對授權(quán)用戶的干擾以及認(rèn)知用戶之間的干擾問題，提出了時間加權(quán)頻譜感知優(yōu)化算法，建立頻譜感知博弈模型并以此為基礎(chǔ)提出非對稱碰撞規(guī)避策略。時間加權(quán)頻譜感知優(yōu)化算法針對授權(quán)用戶在認(rèn)知用戶頻譜感知環(huán)節(jié)突然回歸當(dāng)前信道的現(xiàn)象，通過對采樣信號分組并按照時間順序進行線性加權(quán)來提高對授權(quán)用戶的檢測概率。算法分析對比了數(shù)據(jù)融合準(zhǔn)則和決策融合準(zhǔn)則下的時間加權(quán)優(yōu)化算法。結(jié)果表明，采用決策融合時間加權(quán)優(yōu)化算法，在相同分組數(shù)量的情況下的檢測性能較好。同時針對授權(quán)用戶隨機出現(xiàn)的場景，時間加權(quán)優(yōu)化算法會明顯的提高檢測概率。頻譜感知博弈模型模擬了認(rèn)知用戶吞吐量競爭的自私行為以及干擾。基于頻譜感知博弈模型，本文提出非對稱碰撞規(guī)避策略。該策略在保證自私用戶的minmax收益基礎(chǔ)上，最大化非自私用戶的頻譜接入概率，使得非自私用戶與自私用戶可以共享信道。 最后，針對獨立的認(rèn)知用戶之間頻譜共享時的干擾問題，提出了競爭退出策略和非對稱主動合作策略。在獨立的認(rèn)知用戶頻譜共享模型中，兩個認(rèn)知用戶頻譜競爭的均衡結(jié)果是認(rèn)知用戶將各自的功率擴展到整個頻譜。針對均衡時認(rèn)知用戶之間的相互干擾問題，本文提出了基于頻譜移動功能的競爭退出策略。該策略以最大化認(rèn)知用戶的長期收益為目標(biāo)，為不同的感知結(jié)果指定了一個競爭退出時間。通過與“干擾-立即退出”方案相對比，基于競爭退出策略均衡時的方案，認(rèn)知用戶明顯的減少了信道切換次數(shù)，有利于提高網(wǎng)絡(luò)穩(wěn)定性。此外，，本文提出了基于頻譜接入功能的非對稱主動合作策略。認(rèn)知用戶以最大化長期收益問目標(biāo)，通過認(rèn)知用戶可以單方面采取合作行為，另一個認(rèn)知用戶響應(yīng)合作行為的方式來建立合作。非對稱主動合作是一種隱式的共謀策略，為彼此獨立的認(rèn)知用戶提供了一種優(yōu)化頻譜共享策略。
[Abstract]:Cognitive radio (cognitive radio), a revolutionary concept in the development of modern communications, has attracted wide attention over the past ten years. Through software defined radio, cognitive radio can detect channel state, energy efficiency, bandwidth availability, geographic location, spectrum use, network connectivity and so on. And, through wireless environment and wireless environment, The interaction of other users, cognitive radio can adaptively change its operating parameters to achieve the best frequency utilization. In addition, the concept of cognitive radio is also introduced to the next generation wireless and mobile computing system to improve the efficiency of spectrum.
Dynamic spectrum access is the key technology of cognitive radio. This technology is used to recognize radio users to access radio spectrum. Cognitive users' interference with other users in the radio spectrum process is a problem worthy of study. This problem can be studied from three sides. First, authorized users can make rules. To guide the spectrum access of cognitive users and reduce interference from cognitive users; two, cognitive users avoid interference with authorized users or other cognitive users through spectrum sensing; three, cognitive users share spectrum resources through spectrum competition or cooperation. This paper studies cognitive user spectrum competition from the above three aspects. And the problem of interference avoidance. Based on game theory and optimization algorithm, a solution is proposed.
First, from the point of view of authorized users, this paper proposes a cognitive cycle optimization algorithm based on interference compensation pricing and a hybrid spectrum access management algorithm based on pricing mechanism, aiming at the interference problem in the spectrum sharing between the cognitive users and the authorized users. The traditional cognitive cycle optimization algorithm aims at maximizing the average throughput of the cognitive users and neglects the experience of the authorized users. The cognitive cycle optimization algorithm based on the interference compensation pricing makes the authorized users participate in the cognitive cycle, adjusts the cognitive cycle according to the spectrum utilization rate of the authorized users and balances the cognitive users. The interference probability and the channel idle rate. The hybrid spectrum access management algorithm based on the pricing mechanism has different effects on the authorized users when the cognitive users are mixed with the spectrum access. This algorithm can adjust the frequency spectrum Overlay mode and the spectrum Underlay mode of the cognitive users according to the spectrum utilization of the authorized user. The price of spectrum access affects users' choice of these two spectrum access modes through the spectrum access price.
Secondly, from the perspective of cognitive users, this paper proposes a time weighted spectrum sensing optimization algorithm, based on the interference of cognitive users to authorized users and the interference between cognitive users, and establishes a spectrum sensing game model and proposes an asymmetric collision avoidance strategy based on it. Time weighted spectrum sensing optimization algorithm is aimed at authorized users. The phenomenon of the sudden return of the spectrum perception link to the current channel, the detection probability of the authorized users is improved by grouping the sampled signals and weighted to the time sequence. The algorithm analysis compares the data fusion criterion and the time weighted optimization algorithm under the decision fusion criterion. The results show that the decision fusion is adopted. The inter weighted optimization algorithm has better detection performance in the case of the same number of groups. At the same time, the time weighted optimization algorithm will obviously improve the detection probability for the random scene of the authorized users. The spectrum sensing game model simulates the selfish behavior of the cognitive user throughput competition and the interference. In this paper, an asymmetric collision avoidance strategy is proposed, which maximizes the spectrum access probability of unselfish users on the basis of guaranteeing the minmax revenue of selfish users, making the unselfish users share the channel with the selfish users.
Finally, a competitive exit strategy and an asymmetric active cooperative strategy are proposed for the interference problem of spectrum sharing among independent cognitive users. In an independent cognitive user spectrum sharing model, the equilibrium results of the two cognitive users' spectrum competition are that the cognitive users extend their respective power to the entire spectrum. In this paper, a competitive exit strategy based on spectrum mobility is proposed in this paper. This strategy aims at maximizing the long-term income of cognitive users, and specifies a competitive exit time for different perceived results. By comparing with the "interference immediate exit" scheme, the strategy is based on the equilibrium of the competitive exit strategy. In the case, cognitive users obviously reduce the number of channel switching and improve the network stability. In addition, this paper proposes an asymmetric active cooperative strategy based on the spectrum access function. The cognitive users can maximize the long-term returns to the goal, and the cognitive users can take cooperative behavior unilaterally, and another cognitive user responds to the cooperative behavior. In order to establish cooperation, asymmetric active cooperation is an implicit collusion strategy, which provides an optimized spectrum sharing strategy for independent cognitive users.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN925

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