摘要
由于无线频谱资源的稀缺,无线通信业务和应用的快速发展受到了极大的限制。这给无线通信系统频谱效率的提升带来了重要的影响。正交频分复用(OFDM)技术作为减轻频率选择性衰落和码间干扰的一个有效手段被广泛的应用先进的无线通信系统中。它也为不同用户间的子载波分配提供了更加灵活的方式。OFDM系统中的资源调度算法的研究也得到了广泛的关注。
基于OFDM的认知无线电(CR)网络被认为是解决频谱稀少问题的有效的候选方案。而高级长期演进(LTE-A)系统也必将是未来通信系统的大势。作为LTE-A系统的四大关键技术之一,协作式多点传输(CoMP)通过把其他基站发射的干扰信号转变成有用信号的方式,极大了减轻了小区间的干扰和改善了边缘小区用户的体验性能。
首先,在CR网络中,根据凸优化理论提出了拉格朗日对偶的方法,以此来最优化子载波调度和功率分配的问题。为了进一步简化计算,通过把线性整数优化问题扩展成连续的凸优化问题,我们提出来一个支持多业务的最大效用(CR-MUMS)的低复杂度的联合子载波调度算法。
其次,在以上调度算法给系统带了良好增益的情况下,进一步·在基于OFDM的LTE-A系统中引入了单用户多输入多输出(SU-MIMO)的CoMP模式。在动态的扇区选择机制下,不同用户终端间的无线资源块的竞争转化成了传输速率的竞争。与大多数研究设定的满缓存数据模型不同,我们加入了具体的业务模型。为了进一步优化协作方案,我们在协作模式的判定过程中也增加了业务的服务质量(QoS)要求。
最后的仿真结果表明,提出来的低复杂度的联合调度算法比传统的改进的最大加权时延和比例公平算法显示了更有优势的系统性能,包括系统的总吞吐量和用户的平均数据传输速率。引进CoMP机制后,小区的平均吞吐量和边缘用户的传输速率得到了进一步的提升。
Due to the scarcity of spectrum resources, the rapid development of wireless services and applications is severely limited, which exerts a great influence on major increases in achievable spectral efficiency. Orthogonal Frequency Division Multiplexing (OFDM) technology is an effective method to alleviate the frequency selective fading and inter-symbol interference and is widely used in advanced wireless telecommunications. Due to the flexibility to assign subcarriers between different users, OFDM access method has been suggested as a candidate for wireless communication systems. The problem of resource allocation for homogeneous services in OFDM-based spectrum sharing systems has been widely studied.
OFDM based cognitive radio (CR) has been viewed as a promising technique to solve spectrum scarcity problem of the future wireless communication system. While long term evolution advanced(LTE-A) wireless system will be widely used in the future. As one of the key technology, coordinated multi-point (CoMP) transmission/reception strategy was proposed to mitigate inter-cell interference (ICI) by applying the signals transmitted from other cells to assist the transmission instead of acting as interference.
Firstly, in CR networks, the Lagrangian dual method is proposed according to convex optimization theory,, in which the joint subcarrier assignment and power allocation are performed to achieve the optimal solution. To simplify the computation complexity, a low complexity dynamic subcarrier allocation algorithm, named Max Utility for Multiple Services on Cognitive Radio (CR-MUMS), is formulated to extend the non-linear integer optimization to a continuous convex optimization.
Then based on these good performance of attribution algorithm, I further introduce the CoMP mode for single-user multi-input multi-output (CoMP-SU-MIMO) scenario in Long Term Evolution Advanced (LTE-A) system. With the CoMP mechanism the resource block (RB) competition of different users is transformed into transmission rate competition. Service model is introduced in LTE-A system-level simulation platform instead of full-buffer model. To better the solution, the quality of service (QoS) property is added into the judgment of CoMP mode to achieve the optimal performance of sector throughput and cell-edge users (UEs) rates.
Final simulation results illustrate that the proposed algorithm with low computational complexity provides better optimal performance than Modified Largest Weighted Delay First (M-LWDF) and Proportional Fair (PF) algorithms. After introducing CoMP mechanism in LTE-A system, both the average sector throughput and cell-edge users'transmission rate have been greatly improved.
引文
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