Optimized and low-complexity power allocation and beamforming with full duplex in massive MIMO and small-cell networks

The Journal of Supercomputing - By combining massive multiple-input and multiple-output (Ma-MIMO) and small-cell approaches, it is possible to improve the capacity of the network, with the features...     

大规模MIMO系统中低复杂度预编码技术研究

基于大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)系统,提出两类低复杂度预编码算法。首先,通过大规模MIMO系统的渐近正交信道特性近似求逆矩阵,提出了逐次超松弛(Successive Over Relaxation,SOR)预编码算法,能够降低矩阵计算复杂度。其次,在SOR基础上,进一步提出了共轭梯度(Conjugate Gradient,CG)算法,通过引入适当的预处理矩阵对矩阵进行预处理,使其特征值分布更为集中,降低了条件数,加快了算法的收敛速度,从而显著降低了计算复杂度。仿真表明,提出的SOR方法误码率性能优于传统的正则化迫零(Regularization Zero-Forcing,RZF)预编码,而CG算法能够在保证SOR误码率性能的情况下进一步降低计算时间复杂度。     

Asymptotic SEP of MIMO beamforming in two-hop AF relaying systems

This paper derives an asymptotic average symbol error probability(SEP)expression for multiple-input multiple-output(MIMO)two-hop amplify-and-forward(AF)relay systems with optimal beamforming.The analysis at high signal-to-noise ratio(SNR)quantifies the diversity order and array gain,which are valid for any antenna numbers of the terminals and arbitrary channel fading models.It is also proved that the system performance is dominated by the relatively degraded one of the two-hop channels.Our results based on the simple expressions provide valuable insights into the performance and practical design considerations of MIMO AF networks.     

Cross-layer design for cooperative MIMO systems with relay selection and imperfect CSI

Based on imperfect channel state information (CSI) and relay selection, a cross-layer optimization scheme is developed for cooperative MIMO system, and the corresponding system performance is investigated in Rayleigh fading channel. By the theoretical analysis and mathematical manipulation, the average spectral efficiency (SE), packet error rate (PER) and packet loss rate (PLR) are derived. As a result, closed-form expressions of the average SE, PER and PLR are obtained, respectively. According to these, a cross-layer design (CLD) scheme subject to the average PER constraints is proposed to avoid the SE performance loss caused by the conventional instantaneous PER constraints. The scheme optimizes the adaptive thresholds by maximizing the average SE of the system, and an iteration method joint the Lagrange multiplier and Newton methods is presented to solve the above optimization problem. Simulation results verify the validity of the theoretical analysis. The results show that the proposed CLD scheme can improve the SE while target PLR is maintained. The CLD scheme under average PER constraints has higher SE than the conventional CLD scheme under instantaneous PER constraints.     

An iterative BiGAMP-based receiver for coded massive MIMO systems with low-resolution ADCs

Dear editor,The hundreds of antennas deployed in massive multiple-input-multiple-output (MIMO) systems lead to an insup-portable burden in terms of hardware co...     

Maximum-likelihood detection based on branch and bound algorithm for MIMO systems

Maximum likelihood detection for MIMO systems can be formulated as an integer quadratic programming problem. In this paper, we introduce depth-first branch and bound algorithm with variable dichotomy into MIMO detection. More nodes may be pruned with this structure. At each stage of the branch and bound algorithm, active set algorithm is adopted to solve the dual subproblem. In order to reduce the complexity further, the Cholesky factorization update is presented to solve the linear system at each iteration of active set algorithm efficiently. By relaxing the pruning conditions, we also present the quasi branch and bound algorithm which implements a good tradeoff between performance and complexity. Numerical results show that the complexity of MIMO detection based on branch and bound algorithm is very low, especially in low SNR and large constellations.     

Performance analysis of MIMO systems with arbitrary number transmit antenna selection and OSTBC in the presence of imperfect CSI

In this paper, the performance analysis of MIMO systems with arbitrary number transmit antenna selection (TAS) and orthogonal space-time block coding (STBC) in Rayleigh fading channels for imperfect channel state information (CSI) is presented. For the performance analysis, the moment generating function of the system effective SNR as well as its upper and lower bounds are derived. Then, accurate and approximate expressions of bit error rate (BER) of MIMO-TAS-STBC with MPSK and MQAM are further derived. Using the approximate BER formula and imperfect CSI, an adaptive antenna selection scheme is developed for minimizing the BER. The diversity gain and coding gain are analyzed at high SNR. The results indicate that the MIMO-TAS-STBC for imperfect CSI can only achieve partial diversity order KN and the coding gain is affected by K, N, code rate, modulation pattern, and channel correlation coefficients, when K transmit antennas are selected and N receive antennas are used. Simulation results show that the theoretical analysis matches the simulation result well, and the approximate expressions are close to the accurate ones but have a lower complexity.     

MIMO two-way relay channel with superposition coding and imperfect channel estimation

This paper deals with the superposition coding (SPC) scheme in multiple-input multiple-output two-way relay channels subject to imperfect channel estimation. In this scenario, two multiple antenna terminals, which are unable to communicate directly, exchange information with each other via a multiple antenna relay. We determine the impact of the channel estimation error degradation on the achievable rate region for two main SPC techniques: (a) SPC without channel state information (CSI) at the users, (b) SPC with an imperfect CSI at the users where a waterfilling power allocation is employed. We demonstrate that imperfect CSI significantly improves the achievable rate at low signal-to-noise ratios (SNRs) while it becomes less critical at high SNRs. In addition, a SPC power allocation technique that incorporates the average channel statistics and does not require any instantaneous CSI is also investigated. We show how the available power is split between the two bi-directional (superimposed) data flows in order to maximize the system performance and to support fairness as well as to maximize the achievable sum-rate.     

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.     

Precoder and combiner design for dynamically sub-connected hybrid architecture with low-resolution DACs/ADCs in mmWave massive MIMO systems

Dear editor, The integration of mmWave and massive multiple-input multiple-output (mMIMO) becomes inevitable in future 5G wireless communication systems[1],in w...     

Beamforming techniques for massive MIMO systems in 5G: overview,classification, and trends for future research

Massive multiple-input multiple-output (MIMO) systems combined with beamforming antenna array technologies are expected to play a key role in next-generation wireless communication systems (5G), which will be deployed in 2020 and beyond. The main objective of this review paper is to discuss the state-of-the-art research on the most favourable types of beamforming techniques that can be deployed in massive MIMO systems and to clarify the importance of beamforming techniques in massive MIMO systems for eliminating and resolving the many technical hitches that massive MIMO system implementation faces. Classifications of optimal beamforming techniques that are used in wireless communication systems are reviewed in detail to determine which techniques are more suitable for deployment in massive MIMO systems to improve system throughput and reduce intra- and inter-cell interference. To overcome the limitations in the literature, we have suggested an optimal beamforming technique that can provide the highest performance in massive MIMO systems, satisfying the requirements of next-generation wireless communication systems.     

Multi-pair massive MIMO amplify-and-forward relaying system with low-resolution ADCs: performance analysis and power control

In this paper, we focus on a general multi-pair massive MIMO amplify-and-forward (AF) relaying system where the relay antennas employ low-resolution analog-to-digital converters (ADCs) to reduce the hardware cost. First, considering the effect of low quantization on channel estimation, a tight closed form approximation of the system ergodic achievable rate is derived. Second, some asymptotic analysis is presented to reveal the impacts of the system parameters on the achievable rate. Particularly, the generalized power scaling schemes are characterized. The results indicate that in some cases, when the number of relay antennas grows without bound, the impact of the finite resolution ADCs on data transmission can be eliminated. To enhance the achievable rate of the quantized systems, the optimal user and relay power control schemes are proposed. Furthermore, to reap all the benefits of low-resolution ADCs, another power control scheme is also designed to minimize the total power consumption while guaranteeing the quality-of-service (QoS) requirement of each user, which can help draw some useful insights into the optimal ADC resolution from power saving perspectives. The simulation results confirm the accuracy of our theoretical analysis and the effectiveness of the proposed power control schemes.     

Robust topology optimization of skeletal structures with imperfect structural members

A topology optimization framework is proposed for robust design of skeletal structures with stochastically imperfect structural members. Imperfections are modeled as uncertain members’ out-of-straightness using curved frame elements in the form of predefined functions with random magnitudes throughout the structure. The stochastic perturbation method is used for propagating the imperfection uncertainty up to the structural response level, and the expected value of performance measure or constraint is used to form the stochastic topology optimization problem. Sensitivities are derived explicitly using the adjoint method and are used in conjunction with an efficient gradient-based optimizer in search for robust optimal topologies. Topological designs for three representative examples are investigated with the proposed algorithm and the resulting topologies are compared with the deterministic designs. It is observed that the new designs primarily feature load path diversification, which is pronounced with increasing level of uncertainty, and occasionally member thickening to mitigate the impact of the uncertainty in members’ out-of-straightness on structural performance.     

Cyclicity and well-balanced growth in systems with imperfect competition in labor markets

A dynamic macromodel of an economic system with bilateral monopolistic competition in the labor market is considered. Conditions of arising post-classical business cycles in this model are investigated under the assumption that the impact of labor remuneration on the amount of aggregated demand is restricted. Numerical experiments with the model with varied labor productivity demonstrated the possibility of main-line effects. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 29–47, September–October 2007.     

Multi-model control of MIMO systems: location and control algorithms

This paper presents a multi-model control scheme that depends on the multiple representation of a process using linear models. A dynamic system can be represented by several models, each of which is different in either the simplifications involved, the reductions involved, or the dynamic characteristics. A new tracking multi-model control algorithm for deterministic systems is proposed. An auxiliary input called the ‘state correction’ is calculated and applied to the models so as to minimize a performance index which is a function of the difference between the process outputs and the model outputs. A simulation study is given to show the potential of the proposed algorithm.     

Massive MIMO中基于统计信道的波束形成和功率分配

为了提高大规模多输入多输出系统(Massive MIMO)的总容量,提出了基于统计信道信息的波束形成和功率分配的优化算法。所提出的波束形成方法以信噪泄漏比为优化标准,而功率分配方案以系统容量为优化目标,同时满足基站总发射功率约束条件。上述优化问题转化为多个变量的等价优化形式,从而可以通过变量的交替优化迭代达到收敛。每次迭代过程中均可以求出闭式解,迭代完成后可得到优化的功率分配方案。仿真结果表明,相比于平均功率分配方案,该算法能有效地提高系统的总容量。     

A balancing approach to the realization of systems with internal passivity and reciprocity

This paper addresses the realization of positive real transfer functions which are symmetric with respect to some signature matrix. We show that a realization that is jointly internally reciprocal and internally passive can be achieved by positive real balancing.