Singular Value Decomposition Rank-Deficient-Based Estimators in TD-SCDMA Systems

This paper presents a new joint channel estimation method for Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) systems based on a Singular Value Decomposition (SVD) reduced-rank technique. The system capacity is increased by increasing the highest number of users in one time slot. The additional channel estimation processing required for the increasing number of users is solved by adopting the reduced-rank technique, which estimates a limited number of parameters that are needed to describe the channel matrix and reduce the dimensionality of this matrix. Simulation results prove the validity of the proposed reduced-rank technique for channel estimation accuracy enhancing. Additionally, it is shown that the detectors based on the reduced-rank estimators outperform traditional channel estimators, contributing to 7.8 and 6.9 dB BER performance improvements for indoor and vehicular channels, respectively.     

Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems

In time division-synchronous code division multiple access systems, the channel estimation for multiple subscribers requires the computation of very complicated algorithms through short training sequences. This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. Simulation results of the normalized mean square error for the above mentioned estimators showed the superiority of reduced rank estimators. Multi-user joint data detectors based linear equalizers are used to suppress inter-symbol interference and mitigate intra-cell multiple access interference. The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. The results of bit error rate simulation have shown that reduced rank-JCE based detectors have an improvement by 5 dB lower than other traditional full rank-JCE based detectors.     

Reduced-rank technique for joint channel estimation in TD-SCDMA systems

In time division-synchronous code division multiple access systems, increasing the system capacity by exploiting the inserting of the largest number of users in one time slot (TS) requires adding more estimation processes to estimate the joint channel matrix for the whole system. The increase in the number of channel parameters due the increase in the number of users in one TS directly affects the precision of the estimator's performance. This article presents a novel channel estimation with low complexity, which relies on reducing the rank order of the total channel matrix H. The proposed method exploits the rank deficiency of H to reduce the number of parameters that characterise this matrix. The adopted reduced-rank technique is based on truncated singular value decomposition algorithm. The algorithms for reduced-rank joint channel estimation (JCE) are derived and compared against traditional full-rank JCEs: least squares (LS) or Steiner and enhanced (LS or MMSE) algorithms. Simulation results of the normalised mean square error showed the superiority of reduced-rank estimators. In addition, the channel impulse responses founded by reduced-rank estimator for all active users offers considerable performance improvement over the conventional estimator along the channel window length.     

一种基于最小均方误差准则的联合多小区信道估计算法

信道估计的准确程度直接影响到联合检测算法的性能。传统的信道估计算法将其他小区用户的信号均作为白噪声来处理,因此影响了信道估计的准确性。该文提出基于最小均方误差准则的联合多小区信道估计算法,由于改变了信道估计矩阵的结构,将邻小区强干扰用户也作为可以检测的用户信号来处理,降低了信道估计中噪声功率。该算法不仅适用于多小区联合检测,也可用于单小区联合检测。与传统的Steiner信道估计算法相比,新算法在存在邻小区同频干扰的情况下,能够很大程度提高信道估计的精度,进而大幅提升TD-SCDMA系统的性能。     

Joint Estimation of Doubly Selective Channels and Carrier Frequency Offsets in High Mobility MIMO-OFDMA Uplink

In this paper, we address the joint estimation of doubly selective channels (DSCs) and carrier frequency offsets (CFOs) in multiple input multiple output orthogonal frequency division multiple access uplink with highly mobile users. Since the channel coefficients are rapidly varying over time and the base station has to perform the estimation task from the received composite signal, the exact solution to this joint estimation problem requires multidimensional search which is computationally intensive. We propose an iterative technique for the joint estimation of DSCs and CFOs based on space alternating generalized expectation maximization algorithm which will decompose the multidimensional optimization to many one dimensional searches. The proposed method works even in the presence of residual timing offsets and it does not require the knowledge of channel statistics at the receiver. Convergence properties of the proposed algorithm in terms of rate matrix is studied and analytically proved that the proposed joint estimation algorithm converges. Simulation studies illustrate that the proposed technique offers good performance even at very high mobile speeds.

     

Asymptotically near-optimal blind estimation of multipath CDMA channels

In this paper, correlation matching techniques are applied to estimate multipath code division multiple access (CDMA) channels. We arrange unknown multipath parameters for each of J active users in a vector. Then, the output correlation matrix is parameterized by J unknown rank one matrices, with each one formulated from the corresponding channel vector. This correlation matrix is further compared with its sample average. The resulting error can be first minimized to obtain unbiased estimates of J unknown rank one matrices in closed forms. Thus, our estimator for each channel vector is derived by singular value decomposition (SVD) on the associated rank one matrix within a scalar ambiguity. It turns out that the performance of our estimator can be improved by introducing an asymptotically optimal weighting matrix in our cost function. This weighting matrix can be estimated directly from data samples only with a small penalty on the asymptotic performance. The asymptotic covariance of our estimator is also derived and can be compared with the Cramer-Rao lower bound, both in closed forms. Simulation results show the applicability of the proposed methods and consistency with our theoretical analysis     

Two-Stage Channel Estimation Algorithm for TD-SCDMA System Employing Multi-Cell Joint Detection

The conventional Steiner channel estimator is inefficient for TD-SCDMA systems employing multi-cell joint detection because of its low estimation accuracy. A novel two-stage channel estimation algorithm was presented by re-defining the channel estimation matrix to mitigate the noise in the channel estimation. It is based on matched filter and minimum mean square error channel estimation results and it refines the initial channel estimation using inter-symbol interference and multiple access interference elimination. Simulation results prove the validity of the proposed algorithm for estimation accuracy upgrade, contributing to 10.2 dB and 6.8 dB BER performance improvement for the outdoor-to-indoor A channel and Vehicular A channel respectively.     

Two-phase downlink subcarrier allocation for multicell OFDMA systems

To increase spectrum efficiency, the radio resource management with frequency reuse factor = 1 is usually adopted in multi-cell orthogonal frequency division multiple access systems. Such a reuse-one strategy results in severe co-channel interference, especially penalizing mobile users near the cell border. This paper presents an effective subcarrier-assignment algorithm to mitigate the co-channel interference for multi-cell orthogonal frequency division multiple access downlink systems. The proposed algorithm consists of an initial assignment phase and a compensation phase. In the first phase, each subcarrier is assigned to mobile users with higher channel gains and lower mutual co-channel interferences. The second phase further compensates mobile users who do not get adequate resources to meet the requirement of quality of service in the first phase. System simulation results reveal that the proposed algorithm can significantly improve the number of QoS-satisfied users compared with previous used scheme.

     

Bandwidth and region division for broadband multi-cell networks

A cell planning technique termed BRD (bandwidth and region division) is presented for overcoming interference, maintaining QoS (quality of service) and improving channel capacity over OFDM (orthogonal frequency division multiplexing)-based broadband cellular networks. Through an optimal combination of sectorization and zero padding, bandwidth and region division is achieved that minimizes the outage probability for forward-link cell planning. In order to verify the effectiveness of the proposed algorithm, a Monte Carlo simulation is performed over multi-cell environments.     

高速移动通信系统中OTFS信道估计算法研究

针对高速移动环境中双色散信道会出现信道估计可靠性下降的问题,该文在正交时频空(OTFS)调制系统的输入-输出模型中提出一种基于压缩感知的信道估计算法。该算法利用信道中最大多普勒频移和最大时延确定导频发送矩阵的大小,相比传统的正交匹配追踪(OMP)信道估计算法,能够在保证相似信道估计准确度的情况下节省导频资源;并在此基础上,对OTFS调制符号做相位旋转,增加差分矩阵的秩,理论分析和仿真结果表明,该方案能够提升OTFS系统的分集阶数进而降低噪声的干扰。     

双信道解复用长周期光纤光栅的实验研究

长周期光纤光栅是近几年出现的一种波长选择滤波器件。利用其波长选择损耗特性,提出将之用于1310nm/1550nm波分复用系统的解复用。采用电弧熔融刻槽的方法,制备了长周期光纤光栅。并通过控制电弧放电过程和光栅的周期长短及周期数,得到了较为理想的谱特性。结果显示,其通道插入损耗能够小于0.5dB,20dB损耗阻带带宽可达15nm,信道隔离度估计约25dB。     

基于奇异值分解的MIMO-OFDM系统角域MAP信道估计算法

最大后验概率信道估计算法应用于多输入多输出-正交频分复用(MIMOOFDM)系统时需要大规模的矩阵求逆和乘积运算,且系统数据传输效率随发送天线数的增加明显降低.为克服这些问题,提出了一种基于奇异值分解的角域最大后验概率信道估计算法.该算法通过期望最大化把(MIMO)信道估计问题简化为一系列独立的单输入单输出(SISO)问题,并使用奇异值分解避免了大规模矩阵求逆和乘积运算;通过多个OFDM符号联合估计信道提高了系统数据传输效率及算法的估计性能.仿真实验验证了此算法的有效性.     

Hierarchical modulation based cooperative relaying over a multi-cell OFDMA network

The relay-assisted cooperative technique is a promising solution for guaranteeing quality of service and improvement in channel capacity. This paper proposes a hierarchical modulation based cooperative relaying method via a fixed relay station (FRS) to improve the performance of cell edge users for orthogonal frequency division multiple access (OFDMA) systems over a multi-cell environment. The grafting of both FRS and hierarchical modulation onto an OFDMA based cooperative system provides opportunities to reduce the interferences, i.e. inter-cell and inter-relay interferences, and to achieve cooperative diversity in a multi-cell environment, simultaneously. Under conditions of severe inter cell interference caused by high carrier collisions, the proposed scheme leads to an improvement in both channel capacity and bit error rate for cell boundary users.     

Blind Channel Identification for Cyclic-Prefixed MIMO-OFDM Systems with Virtual Carriers

This paper applies the repetition index scheme(RIS)to the channel identification of cyclic prefixed(CP)multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)systems with virtual carriers(VCs)in the environment of the number of receive antennas being no less than that of transmit antennas.The VCs will cause a rank deficiency problem in computing the subspace information.With the subcarrier mapping matrix,the received signal is simplified to remove the rank deficiency.We use the RIS scheme to generate many times of equivalent symbols so the channel identification can converge with few received OFDM blocks.The RIS scheme will convert the white noise into non-white noise.With the Cholesky factorization,a noise whitening technique is developed to turn the non-white noise back to white noise.We further analyze the necessary conditions of identifiability of channel estimation.Simulations are performed to show the superiority of the proposed method.     

Analysis of LDPC with optimum combining

Low density parity check (LDPC) codes have shown exceptionally good performance for single antenna systems over a wide class of channels. LDPC when implemented with a single input multiple output system with maximum ratio combining is optimum from the standpoint of maximising signal-to-noise ratio at combiner output without the presence of interferer. Optimum combining outperforms maximal ratio combining (MRC) in the presence of interferer(s). In this article, the performance of the LDPC codes with multiple receiver antennas with optimum combining in the presence of single interferer is investigated. The simulation results showed that LDPC codes of irregular construction are able to give high coding and diversity gain with optimum combining. The proposed LDPC optimum combined (LDPC–OC) system in Rayleigh fading channel in the presence of a single interferer improves the signal to interferer plus noise ratio by 2.62 dB with four receiver antennas and by 1.98 dB when the number of receiver antennas is three.     

联合波束域分解和SVD的多用户大规模MIMO系统信道估计

针对TDD(Time Division Duplex)模式下的多用户大规模MIMO(Multiple-Input Multiple-Output)系统,本文研究了将波束域分解和SVD(Singular Value Decomposition)同时用于该系统的信道估计。当基站天线数目较多时,信道估计误差、导频开销、信道估计算法的复杂度等问题将成为影响大规模MIMO系统性能的关键因素。运用波束域分解理论,将多用户的大规模MIMO系统分解成多个单用户的大规模MIMO系统,同时从波束域对信道建模,该方法降低导频开销的同时也减小了信道估计误差。另外运用SVD对信道自相关矩阵优化,可以进一步降低信道估计算法的复杂度。基于以上两点,本文提出了一种联合波束域分解和SVD的大规模MIMO信道估计方案,并推导出了估计误差协方差矩阵的闭式表达式。仿真结果表明,与同类方案相比,本文提出的方案具有更好的信道估计性能。      

User mobility profile prediction: An adaptive fuzzy inference approach

Predicting the probabilities that a mobile user will be active in other cells at future moments poses a significant technical challenge to network resource management in multimedia wireless communications. The probability information can be used to assist base stations to maintain a balance between guaranteeing quality of service (QoS) to mobile users and achieving maximum resource utilization. This paper proposes a novel adaptive fuzzy logic inference system to estimate and predict the probability information for direct sequence code division multiple access (DS/CDMA) wireless communications networks. The estimation is based on measured pilot signal strengths at the mobile user from a number of nearby base stations, and the prediction is obtained using the recursive least square (RLS) algorithm. Numerical results are presented to demonstrate the performance of the proposed technique under various path loss and channel shadowing conditions. This revised version was published online in July 2006 with corrections to the Cover Date.     

Reduced-rank channel estimation for time-slotted mobile communication systems

In time-slotted mobile communication systems with antenna array at the receiver, the space-time channel matrix is conventionally estimated by transmitting pilot symbols within each data packet (or block). This work is focused on reduced rank (RR) estimation methods that exploit the low-rank property of the space-time channel matrix to estimate single or multiple user channels from the observation of single or multiple training blocks. The proposed RR methods allow to improve the estimate accuracy by reducing the set of unknown parameters (rank reduction) and extending the training set (multiblock processing). The maximum likelihood RR estimate is obtained as the projection of the prewhitened full-rank (FR) estimate onto the spatial or temporal signal subspace. The paper shows that, even for time varying channels, these subspaces can be considered to be slowly varying, and therefore, they can be estimated with increased accuracy by properly exploiting training signals from several blocks. The analytical and numerical performance in terms of mean square error for the RR estimate shows that the main advantage of the proposed method with respect to the conventional FR one can be ascribed to the reduced complexity of the channel parameterization.     

Experimental evaluation of combined effect of coherent RAKEcombining and SIR-based fast transmit power control for reverse link ofDS-CDMA mobile radio

The combined effect of coherent RAKE combining using the weighted multislot averaging (WMSA) channel estimation filter and closed-loop fast transmit power control (TPC) in the 4.096 Mchip/s direct sequence code division multiple access (DS-CDMA) mobile radio reverse link is experimentally evaluated. The WMSA channel estimation filter utilizes periodically transmitted pilot symbols (four pilot symbols are time-multiplexed in each 40-symbol time slot). Its observation period is extended to 2-K slots in order to improve the accuracy of the channel estimation. The fast TPC is based on the measurement of signal-to-interference plus background noise ratio (SIR) using pilot symbols. Laboratory experiments show that the use of the K=2 WMSA channel estimation filter reduces the required E_b/I₀ at the average BER of 10^-3 by approximately 0.5 dB compared to use of the linear interpolation filter, and that the required E_b/I₀ is minimized when the SIR measurement interval is M=10 symbols (one slot TPC delay). It was also clarified that SIR-based TPC works satisfactorily when two users with different information data rates, i.e., SF, independently employ fast TPC. Field experimental results obtained in an area nearby Tokyo showed that the average BER of 10^-3 is achieved at the target E_b/I₀ per antenna of approximately 2.5 dB by using four-finger branch RAKE and two-branch antenna diversity. Although the target E_b/I₀ to achieve same BER, when there is one interfering user with a fourfold greater transmit power than that of the desired user that independently employs fast TPC, is almost the same as that in the single-user case, the mobile transmit power is increased by 1.0-2.0 dB due to the increased MAI. These results indicate that the combination of coherent RAKE combining and fast TPC works well in practical multipath fading channels     

Iterative Joint Channel Estimation and Multi-User Detection for Multiple-Antenna Aided OFDM Systems

Multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to single-input-single-output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell layered space-time architecture (BLAST) or space division multiple access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a "rank-deficient" scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new genetic algorithm (GA) assisted iterative joint channel estimation and multi-user detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the forward error correction (FEC) or channel decoder, which inevitably limits the system's achievable performance. By contrast, our proposed GA is capable of providing "soft" outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme.