本文選題：多小區(qū)OFDMA + 資源分配　； 參考：《華南理工大學(xué)》2014年博士論文

【摘要】：隨著無線通信應(yīng)用的豐富和發(fā)展，服務(wù)質(zhì)量(QoS)需求與無線通信資源有限的矛盾日益尖銳。為緩解這一矛盾，必須從無線通信系統(tǒng)的各個層面展開研究。在物理層，正交頻分復(fù)用(OFDM)是一種非常適合于寬帶無線系統(tǒng)的技術(shù);在鏈路層，采用資源分配和調(diào)度可以顯著改善通信系統(tǒng)的頻譜效率和吞吐量。另外，OFDMA技術(shù)的獨特優(yōu)勢，為資源分配提供了靈活的自由度，因此，OFDMA系統(tǒng)中的資源分配算法得到了廣泛的關(guān)注。 正交頻分多址(OFDMA)是將正交頻分復(fù)用(OFDM)技術(shù)和頻分多址(FDMA)技術(shù)相結(jié)合的多址方案，是第四代移動通信系統(tǒng)(4G)的關(guān)鍵技術(shù)之一。OFDMA以O(shè)FDM調(diào)制為基礎(chǔ)，通過給不同用戶獨立地分配子載波來實現(xiàn)多用戶接入，在多用戶同時接入的情況下，OFDMA系統(tǒng)基于無線信道的狀態(tài)、服務(wù)質(zhì)量(QoS)要求等參數(shù)動態(tài)地制定資源配置方案，從而實現(xiàn)資源的自適應(yīng)最優(yōu)配置。這樣，系統(tǒng)既能獲得更高的頻譜利用率，又可以更好地滿足QoS要求。自適應(yīng)資源配置是當(dāng)前一個重要的研究課題，，也是OFDMA系統(tǒng)急需解決的核心問題之一。 針對這個研究方向，本文在深入研究多小區(qū)OFDMA自適應(yīng)資源配置過程中提出了一種基于罰函數(shù)的資源分配算法和一種低復(fù)雜度資源分配算法，同時研究了系統(tǒng)中信道噪聲的估計，提出了一種基于最大似然法的聯(lián)合測量干擾和噪聲功率水平的非數(shù)據(jù)輔助算法。全文系統(tǒng)地分析和研究了在多小區(qū)OFDMA系統(tǒng)進(jìn)行自適應(yīng)資源配置需要解決的問題，具體主要有如下三個方面的工作和創(chuàng)新: (1)基于罰函數(shù)的模擬退火資源分配算法，在多小區(qū)OFDMA系統(tǒng)中，基于集中式資源管理，考慮本小區(qū)對其他小區(qū)的干擾情況，對各個小區(qū)的子載波和功率分配進(jìn)行調(diào)整，從而達(dá)到最小化總功率的目的。通過功率離散化來建立多小區(qū)OFDMA問題模型，使用罰函數(shù)法來簡化問題模型，并采用改進(jìn)的模擬退火算法進(jìn)行求解。本文提出的罰函數(shù)SA（Penalty-Simulation Annealing）資源分配算法，簡化了問題模型，從而降低了模型求解復(fù)雜度。理論分析和仿真結(jié)果表明，離散功率個數(shù)的選擇在一定范圍內(nèi)具有隨機性。文章提出的算法獲得了更好的系統(tǒng)吞吐量，同時有效降低了求解復(fù)雜度，且對整體性能不會產(chǎn)生不良影響；與多分配算法相比，單位功率吞吐量有顯著提高。 (2)提出了一種低復(fù)雜度資源分配算法，通過對一組線性方程組的求解，在最小化傳輸功率的同時滿足了用戶最大傳輸需求。該算法把子載波和功率分配分別實施，即把資源分配過程分成子載波分配和功率分配兩個獨立的步驟進(jìn)行，在子載波分配時，假設(shè)頻效率固定簡化了分配復(fù)雜度，在固定頻率效率的情況下，功率分配可以通過一組線性方程組求得，當(dāng)方程組的解出現(xiàn)負(fù)值時，通過調(diào)整算法對負(fù)值的解進(jìn)行處理實現(xiàn)正確的分配結(jié)果，仿真結(jié)果表明該算法在系統(tǒng)吞吐量、功率效率、算法復(fù)雜度等方面，取得了一個介于最優(yōu)算法和多分配算法之間的折衷。 (3)提出了一個基于最大似然法的平坦信道估計算法，該算法是一種聯(lián)合測量干擾和噪聲功率水平的非數(shù)據(jù)輔助算法。針對確定性未知高斯白噪聲干擾的有限狀態(tài)離散信號，該算法首先假設(shè)在特定條件下，得到一個近似的閉形式解，然后以些解為初始值，采用迭代的方法，以最大似然準(zhǔn)則為基礎(chǔ)，得到完善的估計結(jié)果。仿真結(jié)果表明該方法具有收斂速度快，準(zhǔn)確性高等特性。
[Abstract]:With the enrichment and development of wireless communication applications, the contradiction between the quality of service (QoS) demand and the limited wireless communication resources is becoming increasingly acute. In order to alleviate this contradiction, it is necessary to study from the various levels of the wireless communication system. In the physical layer, orthogonal frequency division multiplexing (OFDM) is a technology that is not often suitable for broadband wireless systems; in the link layer, in the link layer, Resource allocation and scheduling can significantly improve the spectrum efficiency and throughput of the communication system. In addition, the unique advantage of OFDMA technology provides a flexible degree of freedom for resource allocation. Therefore, the resource allocation algorithm in the OFDMA system has been widely concerned.
Orthogonal frequency division multiple access (OFDMA) is a multiple access scheme combining orthogonal frequency division multiplexing (OFDM) technology and frequency division multiple access (FDMA) technology. It is one of the key technologies of the fourth generation mobile communication system (4G)..OFDMA is based on OFDM modulation. By assigning subcarriers to different users independently, multi user access is realized and the situation of simultaneous access to multi users is achieved. The OFDMA system is based on the state of the wireless channel, the quality of service (QoS) and other parameters to dynamically formulate the resource allocation scheme, thus realizing the optimal allocation of resources. In this way, the system can obtain higher spectrum utilization and better meet the requirements of QoS. Adaptive resource allocation is an important research topic at present. It is also one of the core problems needed to be solved urgently in the OFDMA system.
Aiming at this research direction, a resource allocation algorithm based on penalty function and a low complexity resource allocation algorithm are proposed in this paper. At the same time, the estimation of channel noise in the system is studied. A joint measurement of interference and noise power based on maximum likelihood method is proposed. The paper systematically analyzes and studies the problems that need to be solved in the self-adaptive resource allocation in multi cell OFDMA system, including the following three aspects: work and innovation.
(1) based on the penalty function based simulated annealing resource allocation algorithm, in the multi cell OFDMA system, based on centralized resource management, considering the interference of the community to other communities, the subcarrier and power allocation of each cell is adjusted to minimize the total power, and the multi cell OFDMA problem is established by power discretization. The penalty function method is used to simplify the problem model, and the improved simulated annealing algorithm is used to solve the problem. The penalty function SA (Penalty-Simulation Annealing) resource allocation algorithm is proposed in this paper, which simplifies the problem model and reduces the complexity of the model. The theoretical analysis and simulation results show that the selection of the discrete power number is in the first place. The proposed algorithm achieves better system throughput, reduces the complexity effectively, and does not have a bad effect on the overall performance. Compared with the multi allocation algorithm, the unit power throughput is significantly improved.
(2) a low complexity resource allocation algorithm is proposed. By solving a set of linear equations, the maximum transmission demand is met while the transmission power is minimized. The algorithm carries out the sub carrier and power allocation separately, which is divided into two independent steps, which are subcarrier allocation and power allocation. When the carrier distribution is distributed, it is assumed that the frequency efficiency is fixed and the allocation complexity is simplified. In the case of fixed frequency efficiency, the power allocation can be obtained by a set of linear equations. When the solution of the equations appears negative, the correct allocation results are processed by the adjustment algorithm to deal with the negative value. The simulation results show that the algorithm is used in the system throughput. In terms of quantity, power efficiency and algorithm complexity, a trade-off between optimal algorithm and multi allocation algorithm is obtained.
(3) a flat channel estimation algorithm based on maximum likelihood method is proposed. This algorithm is a non data auxiliary algorithm combined to measure the level of interference and noise power. According to the finite state discrete signal with uncertain Gauss white noise interference, the algorithm first assumes an approximate closed form solution under the definite condition. This method is based on the maximum likelihood criterion by using some solutions as the initial value. The simulation results show that the method has fast convergence speed and high accuracy.

【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN929.5

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