一种基于自适应天线的OFDM自适应比特分配算法

本文提出了一种利用自适应天线阵列实现自适应OFDM系统的方案。该方案利用抽样矩阵求逆(SMI)算法对天线阵列进行最优权值的估计,并根据天线权值计算出的信噪比(SNR)。在各个子载波上进行自适应的比特分配。仿真结果表明。与传统的OFDM系统相比,利用此方案实现的自适应OFDM系统,误码率性能可以得到有效的改善。     

一种基子自适应天线的OFDM自适应比特分配算法

本文提出了一种利用自适应天线阵列实现自适应OFDM系统的方案.该方案利用抽样矩阵求逆(SMI)算法对天线阵列进行最优权值的估计,并根据天线权值计算出的信噪比(SNR),在各个子载波上进行目适应的比特分配.仿真结果表明,与传统的OFDM系统相比,利用此方案实现的自适应OFDM系统,误码率性能可以得到有效的改善.     

OFDM系统中的自适应比特功率分配算法

正交频分复用(OFDM)系统各子信道具有不同的衰落特性,如果采用相同的调制方式,则不能更好地利用系统资源。在系统容量受限和误比特率一定的条件下,文章提出了一种高效的OFDM自适应比特功率分配算法。在要求误比特率BER<10-3时,该算法与Chow算法相比,发射总功率减小了2.5 dB;与Hughes-Hartogs算法相比,系统消耗的总时间也明显缩短。仿真结果验证了算法的有效性。     

OFDM系统中自适应比特分配算法分析

对单用户OFDM系统的3种自适应比特加载算法:Hugehes-Hartogs比特功率梯度分配算法、Chow算法和简单分块加载(SBLA)算法进行了仿真,分析比较了3种算法的复杂度和抗噪声性能。仿真结果表明:每种算法各有其优缺点和适用情况,可以根据不同的工程需求选择不同的算法。Hugehes-Hartogs算法能使系统发射总功率达到最低;Chow算法具有较好的抗噪声性能;SBLA算法的性能介于上述2种算法之间,并且具有较低的复杂度。     

MIMO-OFDM自适应比特分配算法研究

针对当前OFDM系统中的比特分配算法复杂度比较高,不适合运用于自适应调制系统中,提出改进的自适应比特分配调整算法,采用变步长调整的思想,进一步简化比特分配的复杂度。在此基础上,将OFDM和MIMO技术结合,进行MIMO-OFDM系统的相关参数仿真并进行分析。通过仿真说明本文介绍的算法计算复杂度小,成本较低,适用多用户,能够很好的应用到实际中。     

MC-CDMA系统中的自适应比特和功率分配算法

在研究MC-CDMA系统和自适应比特分配技术的基础上,提出了一种适合MC-CDMA系统的自适应比特和功率分配算法。本算法以扩频支路为单位,根据系统中各子载波的不同信道增益,动态地分配数据比特和发射功率。仿真结果表明,使用该算法可以大大减小发射功率,提高系统性能。     

MIMO-OFDM系统下的自适应迭代比特分配算法

针对多输入多输出正交频分复用（MIMO—OFDM）系统提出了一种自适应迭代的调制方案。考虑实际通信系统的要求，在通信上层传输速率和误码率要求一定的情况下，以最小化发射功率为目标，在发射端采用自适应迭代的方法给每个空间子信道分配传输比特、发射功率。在满足用户要求的同时，获得了好的频谱效率，节省了发射功率。并且，采用迭代的方法解决了因发射比特必须取整引起的误差。相比与同类算法，可大大降低计算复杂度。计算机仿真表明提出的方法可以用低的发射功率达到用户要求。     

OFDM系统中自适应比特分配算法的研究

在研究OFDM系统和自适应分配技术的基础上,对几种重要的自适应分配算法进行详细分析,并通过仿真比较了它们的性能和复杂度.仿真结果表明,使用自适应分配算法的OFDM系统可以减小发射功率,提高系统性能.     

多用户光OFDM系统自适应子载波与比特分配算法

光OFDM能够方便地应用于现有基于PON的接入网,随着用户业务需求的增加和多样化,在用户间合理地分配资源能够提供更优质的服务。在此,阐述了一种优化的误码率最小化自适应资源分配算法。仿真结果显示,在对系统误码率影响不大的情况下,该算法在原算法的基础上降低了复杂度。     

空间调制系统低复杂度的天线选择算法

空间调制(Spatial Modulation,SM)是一种特殊的多天线传输技术,利用发送天线索引和发送的符号共同传递信息.为了获得发送分集增益,人们将天线选择技术应用到SM系统中,提高SM系统解调性能.在天线选择技术中,最大-最小欧式距离(Euclidean Distance Antenna Selection,EDAS)准则应用较为广泛,但是它的全搜索求解方法复杂度高,限制了其应用.为此,本文利用空间调制系统和调制符号本身的特性,从2维量化解调的视角出发,给出了两种低复杂度的最优天线选择算法,并通过计算机仿真和复杂度分析,表明了该算法的有效性和最优性.     

一种低复杂度盖尔圆MIMO系统发射天线选择算法

该文在研究MIMO系统中相关信道下穷举搜索算法、盖尔圆算法等基础上,提出一种低复杂度盖尔圆算法。算法通过每次迭代中删除最小特征值所对应的列,来提高特征值的下界并减小天线间的相关性使得容量最大化或误码率最小化。理论分析和仿真结果表明,该算法在所选天线数目较多场合下具有较低的复杂度,同时其容量和误码性能优于基于范数最大的算法,接近最优穷举搜索算法。     

Joint User Scheduling and Antenna Selection in Distributed Massive MIMO Systems with Limited Backhaul Capacity

Massive MIMO systems offer a high spatial resolution that can drastically increase the spectral and/or energy efficiency by employing a large number of antennas at the base station（BS）.In a distributed massive MIMO system,the capacity of fiber backhaul that links base station and remote radio heads is usually limited,which becomes a bottleneck for realizing the potential performance gain of both downlink and uplink.To solve this problem,we propose a joint antenna selection and user scheduling which is able to achieve a large portion of the potential gain provided by the massive MIMO array with only limited backhaul capacity.Three sub-optimal iterative algorithms with the objective of sumrate maximization are proposed for the joint optimization of antenna selection and user scheduling,either based on greedy fashion or Frobenius-norm criteria.Convergence and complexity analysis are presented for the algorithms.The provided Monte Carlo simulations show that,one of our algorithms achieves a good tradeoff between complexity and performance and thus is especially fit for massive MIMO systems.     

Low Complexity Minimum Mean Square Error Channel Estimation for Adaptive Coding and Modulation Systems

Performance of the Adaptive Cod- ing and Modulation （ACM） strongly depends on the retrieved Channel State Information （CSI）, which can be obtained using the chan- nel estimation techniques relying on pilot sy- mbol transmission. Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little. In this paper, we investigate the performance of CSI prediction using the Minimum Mean Square Error （MMSE） channel estimator for an ACM system. To solve the two problems of MMSE： high compu- tational operations and oversimplified assum- ption, we then propose the Low-Complexity schemes （LC-MMSE and Recursion LC-MMSE （R-LC-MMSE））. Computational complexity and Mean Square Error （MSE） are presented to evaluate the efficiency of the proposed algo- rithm. Both analysis and numerical results sh- ow that LC-MMSE performs close to the well- known MMSE estimator with much lower com- plexity and R-LC-MMSE improves the appli- cation of MMSE estimation to specific cir- cumstances.     

Adaptive bit allocation scheme in multi-cell cooperative block diagonalization systems with delayed and limited feedback

In multi-cell cooperative multi-input multi-output(MIMO) systems,base station(BS) can exchange and utilize channel state information(CSI) of adjacent cell users to manage co-channel interference.Users quantize the CSIs of desired channel and interference channels using finite-rate feedback links,then BS can generate cooperative block diagonalization(BD) precoding matrices using the obtained quantized CSI at transmitter to supress co-channel interference.In this paper,a novel adaptive bit allocation scheme is proposed to minimize the rate loss due to imperfect CSI.We derive the closed-form expression of rate loss caused by both channel delay and limited feedback.Based on the derived rate loss expression,the proposed scheme can adaptively allocate more bits to quantize the better channels with smaller delays and fewer bits to worse channels with larger delays.Simulation results show that the proposed scheme yields higher performance than other allocation schemes.     

大规模MIMO系统中基于二对角矩阵分解的低复杂度检测算法

在大规模多输入多输出(MIMO)系统的上行链路检测算法中,最小均方误差(MMSE)算法是接近最优的,但算法涉及到大矩阵求逆运算,计算复杂度仍然较高。近年提出的基于诺依曼级数近似的检测算法降低了复杂度但性能有一定的损失。为了降低复杂度的同时逼近MMSE算法性能,该文提出基于二对角矩阵分解的诺依曼级数(Neumann Series)近似,即将大矩阵分解为以两条主对角线上元素组成的矩阵与空心矩阵之和。理论分析与仿真结果表明所提算法检测性能逼近MMSE检测算法,且其复杂度从O(K3)降低到O(K2),这里K是用户的数目。     

Adaptive Power and Bit Allocation in Multicarrier Systems

We present two adaptive power and bit allocation algorithms for multicarrier systems in a frequency selective fading environment. One algorithm allocstes bit based on maximizing the channel capacity, another allocates bit based on minimizing the bit-error-rate （BER）. Two algorithms allocate power based on minimizing the BER. Results show that the proposed algorithms are more effective than Fischer＇s algorithm at low average signal-to-noise ration （SNR）. This indicates that our algorithms can achieve high spectral efficiency and high communication reliability during bad channel state. Results also denote the bit and power allocation of each algorithm and effects of the number of subcarriers on the BER performance.     

A Low Complexity and Low Power SoC Design Architecture for Adaptive MAI Suppression in CDMA Systems

In this paper, we propose a reduced complexity and power efficient System-on-Chip (SoC) architecture for adaptive interference suppression in CDMA systems. The adaptive Parallel-Residue-Compensation architecture leads to significant performance gain over the conventional interference cancellation algorithms. The multi-code commonality is explored to avoid the direct Interference Cancellation (IC), which reduces the IC complexity from to . The physical meaning of the complete versus weighted IC is applied to clip the weights above a certain threshold so as to reduce the VLSI circuit activity rate. Novel scalable SoC architectures based on simple combinational logic are proposed to eliminate dedicated multipliers with at least saving in hardware resource. A Catapult C High Level Synthesis methodology is apply to explore the VLSI design space extensively and achieve at least speedup. Multi-stage Convergence-Masking-Vector combined with clock gating is proposed to reduce the VLSI dynamic power consumption by up to This paper was presented in part at IEEE ISCAS in Vancouver, Canada, May, 2004.     

一种用于MIMO系统的快速天线选择算法

在多径衰落环境中, MIMO系统的信道容量随天线数的增加呈线性增加,发射/接收天线选择方法能以很小的性能损失换取射频成本的大幅度降低,使MIMO系统不完全受射频成本的限制。为快速选择出使系统容量最优的发射/接收天线子集,该文提出一种快速天线选择算法的改进算法。该算法通过实时更新优化参数,大大降低计算复杂度。仿真结果表明,该算法在不影响系统容量的情况下大大减少了计算时间。     

MIMO广播系统中基于有限反馈的多用户选择新算法

在基于有限反馈多输入多输出(MIMO)广播系统的多用户选择研究中,目前已有的用户信噪干扰比(SINR)估计存在较大误差,这使得整个系统的性能受到制约。该文利用推导出的上下界来联合估计用户接收到的有用信号功率,得到了一种误差较小的SINR估计式,并基于该式给出了一种用户选择新算法。仿真结果表明,新的用户选择算法可以在低信噪比和高信噪比下同时达到较优性能,且复杂度较低。     

Adaptive precoding and power allocation in distributed antenna systems with limited feedback

This paper introduces the limited feedback precoding into the distributed antenna system and proposes to adapt the predetermined orthogonal space time block codes to the available channel state information at the transmitter. The optimal representation of precoding information, namely the precoder, with least bits therefore becomes the key problem. Inspired by the characteristics of the distributed antenna system, we focus our work on the precoder construction, adaptable in response to the large and small scale fading, such that the symbol error probability is significantly reduced over that of a fixed, non‐adaptive, independent and identically distributed precoder codebook design. Furthermore, a suboptimal power‐loading strategy is presented by minimizing the derived tight upper bound on the average pairwise error probability of the precoded orthogonal space time block codes, which approaches the optimal performance asymptotically without additional channel knowledge other than the available feedback information. We prove that the proposed precoded orthogonal space time transmission scheme can achieve full diversity order. In particular, the robustness of our proposed transmission scheme to channel estimation error and feedback delay is respectively investigated in some detail, and numerical results show that it obviously improves the link reliability and obtains substantial gains even with few bits of feedback in comparison with conventional antenna selection scheme. Copyright © 2013 John Wiley & Sons, Ltd.