Low-complexity approximate iterative LMMSE detection for large-scale MIMO systems

This paper deals with iterative detection for uplink large-scale MIMO systems. The well-known iterative linear minimum mean squared error (LMMSE) detector requires quadratic complexity (per symbol per iteration) with the number of antennas, which may be a concern in large-scale MIMO. In this work, we develop approximate iterative LMMSE detectors based on transformed system models where the transformation matrices are obtained through channel matrix decompositions. It is shown that, with quasi-linear complexity (per symbol per iteration), the proposed detectors can achieve almost the same performance as the conventional LMMSE detector. It is worth mentioning that the linear transformations are also useful to reduce the complexity of downlink precoding, so the relevant computational complexity can be shared by both uplink and downlink.     

一种适用于 LTE 上行链路的低复杂度信道估计算法

提出了一种适用于3GPP长期演进（Long Term Evolution,LTE）系统上行链路的信道估计算法。为了降低抑制噪声过程中信道能量的损失,该算法对最小二乘（Least Square,LS）算法的时域结果采用从中间向两端搜索的方式进行能量检测。仿真结果表明,该算法与LS算法、传统的基于DFT的估计算法、线性最小均方误差（Linear Minimum Mean Square Error,LMMSE）算法及负指数LMMSE算法相比,性能良好,且易于实现,具有很好的实用性。     

Optimal precoding for full-duplex base stations under strongly correlated self-interference channels

We study the optimal precoding for a full-duplex (FD) system, where one FD multi-antenna base station (BS) respectively transmits to and receives from two half-duplex single-antenna mobile users (MUs) on the same time slot and frequency band. At the FD BS, the received signal from the desired MU is severely affected by the extremely strong self-interference (SI) from its transmit antennas to the receive antennas. In the presence of residual SI after imperfect SI cancellation, the downlink transmission rate maximization problem subject to a targeted uplink rate is formulated as a non-convex optimization problem to characterize the achievable rate region for the considered system. Considering the case in which the SI channel is strongly correlated, the above problem is transformed into a convex problem by exploiting the rank-one property of the SI channel, which can be solved efficiently. Finally, numerical results validate the effectiveness of the proposed scheme.     

TDD reciprocity calibration for multi-user massive MIMO systems with iterative coordinate descent多用户大规模MIMO时分双工系统迭代坐标下降互易性校准算法

For massive multiple-input multiple-output (MIMO) antenna systems, time division duplexing (TDD) is preferred since the downlink precoding matrix can be obtained through the uplink channel estimation, thanks to the channel reciprocity. However, the mismatches of the transceiver radio frequency (RF) circuits at both sides of the link make the whole communication channel non-symmetric. This paper extends the total least square (TLS) method to the case of self-calibration, where only the antennas of the access points (APs) are involved to exchange the calibration signals with each other and the feedback from the user equipments (UEs) is not required. Then, the proof of the equivalence between the TLS method and the least square (LS) method is presented. Furthermore, to avoid the eigenvalue decomposition required by these two methods to obtain the calibration coefficients, a novel algorithm named as iterative coordinate descent (ICD) method is proposed. Theoretical analysis and simulation results show that the ICD method significantly reduces the complexity and achieves almost the same performance of the LS method.     

基于信道估计的SC-FDMA自适应传输方案

由于SC-FDMA的峰均功率比（PAPR）比OFDMA低,因而被应用于3GPP LTE上行链路。论文分析了SC-FDMA传输系统的数学模型,介绍了基于导频的SC-FDMA系统最小二乘（LS）和线性最小均方误差（LMMSE）信道估计算法。在比较该系统集中式和分布式两种子载波映射方式在高低速不同移动环境下传输性能的基础上,提出了一种基于信道估计的SC-FDMA系统自适应传输方案。经仿真证实该方案比单纯采用一种子载波映射的方法性能更加优越,在相同的误码率情况下,能够节省大概3dB左右的信噪比。     

Achievable throughput enhancement based on modified carrier interferometry for MIMO/OFDM

In MIMO systems, channel estimation is important to distinguish the transmitted signals from multiple transmit antennas. When MIMO systems are introduced in cellular systems, we have to measure the received power from all the connectable base station (BS), as well as to distinguish all the channel state information (CSI) for the combination of transmitter and receiver antenna elements. One of the most typical channel estimation schemes for MIMO in a cellular system is to employ a code division multiplexing (CDM) scheme in which a unique spreading code is assigned to distinguish both BS and MS antenna elements. However, by increasing the number of transmit antenna elements, large spreading codes and pilot symbols are required to estimate an accurate CSI. To reduce this problem, in this paper, we propose a high time resolution carrier interferometry (HTRCI) for MIMO/OFDM to achieve an accurate CSI without increasing the number of pilot symbols.     

Joint DOA and channel estimation with data detection based on 2D unitary ESPRIT in massive MIMO systems

We propose a novel method for joint two-dimensional (2D) direction-of-arrival (DOA) and channel estimation with data detection for uniform rectangular arrays (URAs) for the massive multiple-input multiple-output (MIMO) systems. The conventional DOA estimation algorithms usually assume that the channel impulse responses are known exactly. However, the large number of antennas in a massive MIMO system can lead to a challenge in estimating accurate corresponding channel impulse responses. In contrast, a joint DOA and channel estimation scheme is proposed, which first estimates the channel impulse responses for the links between the transmitters and antenna elements using training sequences. After that, the DOAs of the waves are estimated based on a unitary ESPRIT algorithm using previous channel impulse response estimates instead of accurate channel impulse responses and then, the enhanced channel impulse response estimates can be obtained. The proposed estimator enjoys closed-form expressions, and thus it bypasses the search and pairing processes. In addition, a low-complexity approach toward data detection is presented by reducing the dimension of the inversion matrix in massive MIMO systems. Different cases for the proposed method are analyzed by changing the number of antennas. Experimental results demonstrate the validity of the proposed method.     

Performance of Dual-Polarized DSTTD-IDMA system over correlated frequency selective channels

In this correspondence, we present the performance of Dual-Polarized double space–time transmit diversity (DSTTD) aided multiple-input multiple-output (MIMO) interleave division multiple access (IDMA) scheme over correlated frequency-selective channels for downlink communication. DSTTD system is realized by employing two space–time block code units at the base station (BS). We employ two Dual-Polarized antennas both at the BS and mobile stations. We consider maximum-likelihood ratio detection algorithm at the receiver to detect the signals and to mitigate the effects of multiple access interference and multi stream interference. We implement iterative type turbo decoding algorithm to enhance bit error rate (BER) performance. We evaluate the performance of Dual-Polarized DSTTD-IDMA system based on Stanford University Interim channel models and Long-Term Evaluation channel model. Our simulation results reveal that DSTTD-IDMA system with Dual-Polarized antenna requires higher SNR than uni-polarized antennas. However, it provides the advantage of replacing two uni-polarized antennas by a single Dual-Polarized antenna.     

Multi-user rate and power analysis in a cognitive radio network with massive multi-input multi-output

This paper discusses transmission performance and power allocation strategies in an underlay cognitive radio (CR) network that contains relay and massive multi-input multi-output (MIMO). The downlink transmission performance of a relay-aided massive MIMO network without CR is derived. By using the power distribution criteria, the k^th user’s asymptotic signal to interference and noise ratio (SINR) is independent of fast fading. When the ratio between the base station (BS) antennas and the relay antennas becomes large enough, the transmission performance of the whole system is independent of BS-to-relay channel parameters and relates only to the relay-to-users stage. Then cognitive transmission performances of primary users (PUs) and secondary users (SUs) in an underlay CR network with massive MIMO are derived under perfect and imperfect channel state information (CSI), including the end-to-end SINR and achievable sum rate. When the numbers of primary base station (PBS) antennas, secondary base station (SBS) antennas, and relay antennas become infinite, the asymptotic SINR of the k^th PU and SU is independent of fast fading. The interference between the primary network and secondary network can be canceled asymptotically. Transmission performance does not include the interference temperature. The secondary network can use its peak power to transmit signals without causing any interference to the primary network. Interestingly, when the antenna ratio becomes large enough, the asymptotic sum rate equals half of the rate of a single-hop single-antenna K-user system without fast fading. Next, the PUs’ utility function is defined. The optimal relay power is derived to maximize the utility function. The numerical results verify our analysis. The relationships between the transmission rate and the antenna number, relay power, and antenna ratio are simulated. We show that the massive MIMO with linear pre-coding can mitigate asymptotically the interference in a multi-user underlay CR network. The primary and secondary networks can operate independently.     

Investigation on the spatial-polarizational correlation based on 3GPP spatial channel model

The correlation among signals arriving at diferent elements of the antenna array has a significant impact on the performance of multiple-input multiple-output(MIMO)system.To investigate the inter-element correlation when slant polarized antennas are used,a general approach for calculating the correlation coefcient is proposed based on a model that incorporates the antenna configuration,namely the antenna spacing and the slant angle,as well as the channel parameters,such as the power azimuth spectrum(PAS)and the crosspolarization discrimination(XPD).By applying this method to the 3rd generation partnership project(3GPP)spatial channel model(SCM),the expression of the inter-element correlation when the PAS follows the Laplacian distribution is obtained.The approximate expressions are also given for two special cases,i.e.,the case where the angular spread(AS)of the PAS is small,and the case where the AS is so large that the PAS can be approximated by the uniform distribution.Using these expressions,the impact of the antenna configuration and the channel parameters on the correlation is analyzed.Following that,the trend of inter-element correlation with the slant angle is investigated.Finally,the equivalent relation between the slant angle and the antenna spacing is studied.The results can provide guidelines for the antenna configuration under diferent propagation conditions.     

LTE下行信道估计方法的优化

信道估计技术是长期演进（LTE）核心技术之一。传统的LMMSE信道估计算法有着良好的系统性能,但其最显著的缺点就是自相关矩阵繁琐的求逆运算量大。针对这一问题,提出了基于相关带宽的两种不同的分块矩阵法。仿真结果表明,在不同的多普勒频移影响下,该算法与LS算法、SVD算法、理想LMMSE算法比较,误码率得到了较为理想的控制。     

Multi-channel power allocation based on market competitive equilibrium in cognitive radio networks

Cognitive radios such as intelligent phones and Bluetooth devices have been considered essential goods in next-generation communication systems.Such devices will have to share the same frequency band owing to the limited bandwidth resource.To improve spectrum efciency,we formulate multi-channel power allocation as a market competitive equilibrium(CE)problem,and prove that its solution exists and is unique under the condition of weak interference.We then propose two distributed power allocation algorithms achieving CE,namely the fast convergent power allocation algorithm(FCPAA)and the social-fairness-aware FCPAA(SFAF).Theoretical analysis and simulation results demonstrate that the proposed algorithms lead to better system performance in terms of the guaranteed interference temperature constraint using the price mechanism instead of a strategy based on the Nash equilibrium.Moreover,it is shown that the FCPAA maximizes total utility,and converges more quickly than the method addressed in prior research with the help of improved round-robin rules.However,the FCPAA cannot ensure the same social fairness among secondary users as the SFAF scheme in both the non-fading channel and Rayleigh fading channel;the SFAF balances the individual utility by adjusting each user’s budget at the expense of a small quantity of system total throughput.     

Resource allocation for pilot-assisted massive MIMO transmission

This paper is on the resource allocation problem for pilot-assisted multi-user massive multiple-input-multiple-output (MIMO) uplink with linear minimum mean-squared error (MMSE) channel estimation and detection. We utilize the angular domain channel representation for uniform linear antenna arrays, and adopt its equivalent independent and nonidentical distributed channel model. For a given coherence interval and total energy budget, we study the joint optimization of the training length and the training power to maximize the achievable sum-rate. For tractable analysis and low-complexity solution, a tight approximation on the achievable sum-rate is derived first. Then the training length optimization for fixed training power and the training power optimization for fixed training length with respect to the approximate sum-rate maximization are both shown to be concave. An alternative optimization that solves the training length and power iteratively is proposed for the joint resource allocation. In addition, for the special case that the training and data transmission powers are equal, we derive the optimal training lengths for both high and low signal-to-noise- ratio (SNR) regions. Numerical results show the tightness of the derived sum-rate approximation and also the significant performance advantage of the proposed resource allocation.     

基于功率控制的大规模MIMO系统能效优化算法

能效优化是5 G通信领域的一个研究热点.首先针对单小区多用户上行大规模MIMO通信系统,在满足用户QoS需求和系统可容忍的信道有效噪声条件下,建立关于发射功率、导频序列长度、基站天线数的能效优化模型;其次,不同于传统利用迭代算法求解使系统能效最佳的基站天线数,提出了采用Lambert W函数分析得到最佳基站天线数的闭式表达式;最后根据分式规划理论,采用迭代优化算法联合优化系统导频序列长度、发射功率、基站天线数.仿真结果表明,该算法较现有算法能效提高了11.2％,说明该算法能有效提高系统性能.     

Improved Kalman-based attitude estimation framework for UAVs via an antenna array

Accurate attitude estimation is crucial for Unmanned Aerial Vehicles (UAVs) in order to facilitate automated activities such as landing or trajectory tracking. Recently antenna array based communication systems have been installed in UAVs. This array structure can also be applied for attitude estimation by computing the line-of-sight (LOS) path between the base station and UAV. In this paper, we propose a complete framework for attitude estimation by exploiting 3D LOS vector obtained from the antenna array system. We present all the steps to incorporate the estimated LOS vector into the TRIaxial Attitude Determination (TRIAD), QUaternion ESTimator (QUEST) and Kalman algorithms. As an additional contribution, the error covariance matrix of the LOS vector is analytically calculated by first finding the phase shift mean squared error using the known perturbation model from Singular Value Decomposition and assuming that the antenna array measured data error can be modeled as a circularly symmetric white noise. We evaluate five array configurations via Monte Carlo simulations. We show that array configurations that provide orthogonal components of the LOS vector achieve a better performance. The usage of more than three pairs of antennas to improve the estimation of the LOS vector is also proposed for low and intermediate signal-to-noise ratio regimes.     

基于滑窗滤波和多项式拟合的时变信道估计方法

基于长期演进（LTE）的车辆到一切（LTE-V2X）标准沿用LTE标准的帧格式,并采用块状导频辅助的单载波频分多址（SC-FDMA）系统完成信道估计。然而,由于V2X信道的时变特性,接收机信道估计面对巨大的技术挑战。因此,设计了一种基于滑窗滤波和多项式拟合的时变信道估计方法。针对导频符号处的噪声问题,在最小二乘（LS）方法基础上,采用了自适应长度的滑动窗口滤波进行降噪处理,从而保证导频符号处的信道估计精度。另外,根据多普勒频移大小,设计了自适应阶次的多项式拟合方法来跟踪数据符号处的信道变化。仿真结果表明,所提方法在LS方法的基础上有良好的去噪效果,在低速移动情况下的估计精度介于LS方法和线性最小均方误差（LMMSE）方法之间,而该方法在高速移动条件下能更好地拟合信道的时变特性,且性能上超过了LMMSE方法结合线性插值的信道估计方法。以上结果说明,所提方法相对于对比方法具有更好的自适应性,适用于不同的信道噪声和终端移动速度下的LTE-V2X通信场景。     

面向URLLC业务的MIMO上行系统线性接收机性能分析

针对5G超可靠低时延通信（URLLC）业务的应用需求,研究多输入多输出（MIMO）上行系统中匹配滤波接收机和迫零接收机的解码性能。在URLLC系统下,推导多用户MIMO上行链路在有限块长传输时两种接收机速率和解码错误率的表达式。采用基于随机矩阵理论的渐近等价分析方法和信道色散系数的泰勒展开式,分别获得高低信噪比场景下两种接收机解码错误率的解析式,据此分析两种接收机在URLLC业务下的性能差异,发现随着信噪比增加,迫零接收机解码错误率接近于零,而匹配滤波接收机解码错误率受限于基站天线数和用户数的比值。采用蒙特卡罗方法对所得理论表达式进行仿真验证,结果表明,随着信噪比增加,两种接收机速率和解码错误率的解析式与蒙特卡罗仿真结果十分接近,在低信噪比场景下解码错误率均高于10^-5,在高信噪比场景下满足URLLC业务的可靠性指标,并且迫零接收机可靠性明显优于匹配滤波接收机。     

Multi-rate optimal state estimation

This article formulates a multi-rate linear minimum mean squared error (LMMSE) state estimation problem, which includes four rates as follows: the state updating rate in the model, the measurement sampling rate, the estimate updating rate and the estimate output rate. This formulation is unique in two ways. First, the rate ratio between state measurement and state estimate is more general (a rational number), instead of just an integer or its reciprocal as considered in the existing literature. Second, state estimates are produced in blocks, which have never been considered before in the multi-rate estimator design. The multi-rate LMMSE estimation problem is solved by examining several distinctive cases for single-rate state estimation, obtained through the lifting technique. Also, sufficient conditions are given for asymptotic stability of the proposed multi-rate LMMSE estimators. An example in tracking a manoeuvering target is given to illustrate the proposed multi-rate state estimators.     

采用GSSK调制的MISO系统容量研究

GSSK是空间位移键控(SSK)的一般性推广,通过发射天线索引的组合传输信息,可以极大地降低多天线系统的复杂度。为研究采用GSSK调制技术的MISO无线通信系统的容量特性,从信息论的基本理论出发,通过数学计算和计算机仿真的方法研究了采用GSSK调制的MISO系统的容量。分别对瑞利衰落信道和莱斯衰落信道下的系统容量进行研究,并且比较了独立衰落信道和具有信道相关性的衰落信道在容量方面的不同。结果表明,采用的方法可以有效地计算系统容量。GSSK的系统容量与SNR和发射天线组合的数量密切相关。LOS分量及信道相关系性均会使GSSK的容量降低。     

Enhanced handoff scheme based on efficient uplink quality estimation in LTE-Advanced system

Asymmetric traffics cause downlink–uplink asymmetric interference. It can lead to a critical unbalance between a downlink and an uplink channel qualities in cell edge areas. This paper proposes an enhanced handoff scheme including an efficient uplink channel estimation method. The proposed handoff scheme determines an appropriate handoff-timing and handoff-direction according to an estimated uplink channel quality and a measured downlink channel quality. In the proposed scheme, an uplink or downlink, whose quality dominantly affects a link failure, becomes the main handoff-criterion. An efficient uplink channel estimation method is also proposed to exploit an uplink channel quality in handoff. The proposed method estimates an uplink signal strength from the measured downlink signal strength and predicts an uplink interference based on the interference-level information from neighbor base stations. We propose two different uplink estimation modes such as the simple and the precise modes. The simple estimation mode calculates the uplink channel quality for the overall bandwidth for a general handoff process. The precise estimation mode finds the best uplink band for the handoff user who wants an elaborate handoff process. In the elaborate handoff, a target base station allocates the best uplink band to a handoff user to provide the better uplink channel quality. Simulation results show that the proposed uplink estimation method can accurately compute the uplink channel quality of neighbor cells where the estimation error rate is less than 0.7% The simulation results also show that the proposed handoff scheme reduces handoff-call-dropping probability by up to 69% compared to LTE-Advanced system. In addition, the end-to-end delay of the proposed scheme can be better than that of LTE-Advanced system by 26%.