Beamforming and power allocation in the downlink of MIMO cognitive radio systems based on multiobjective optimization

In this paper, power allocation and beamforming are considered in a multiple input multiple output (MIMO) downlink cognitive radio (CR) communication system, which a base station (BS) serves one primary user (PU) and one secondary user (SU). In order to design the CR system, a constrained multiobjective optimization problem is presented. Two objectives are the signal to noise plus interference ratios (SINRs) of PU and SU. Since PU has a spectrum license for data communication, a constraint in the optimization problem is that the SINR of PU must be greater than a predefined threshold based on the PU demand requirement. Another constraint is a limitation on power in BS. By considering the mentioned model, three iterative algorithms are proposed. At each iteration of all algorithms, the receiver beamforming vectors are derived based on the maximization of PU and SU SINRs, by assuming that the allocated powers and BS beamforming vectors are known. Also, power is assigned to users such that the constraint of power limitation is satisfied. The difference between the algorithms is in the obtaining of transmitter beamforming parameters. We evaluate the performance of the proposed algorithms in terms of bit error rate (BER) in simulations. Also, the computational complexity of the proposed algorithms is obtained.     

Adaptive opportunistic fair scheduling over multiuser spatial channels

We consider the problem of opportunistic fair scheduling (OFS) of multiple users in downlink time-division multiple-access (TDMA) systems employing multiple transmit antennas and beamforming. OFS is an important technique in wireless networks to achieve fair bandwidth usage among users, which is performed on a per-frame basis at the media access control layer. Multiple-transmit-antenna beamforming provides TDMA systems with the capability of supporting multiple concurrent transmissions, i.e., multiple spatial channels at the physical layer. Given a particular subset of users and their channel conditions, the optimal beamforming scheme can be calculated. The multiuser opportunistic scheduling problem then refers to the selection of the optimal subset of users for transmission at each time instant to maximize the total throughput of the system subject to a certain fairness constraint on each individual user's throughput. We propose discrete stochastic approximation algorithms to adaptively select a better subset of users. We also consider scenarios of time-varying channels for which the scheduling algorithm can track the time-varying optimal user subset. We present simulation results to demonstrate the performance of the proposed scheduling algorithms in terms of both throughput and fairness, their fast convergence, and the excellent tracking capability in time-varying environments.     

基于非理想CSI的下行MU-MIMO鲁棒波束成形

在下行多用户多入多出（MU-MIMO）系统中,基站（BS）所获得的非理想信道状态信息（CSI）会导致频分双工（FDD）系统预编码性能变差.现有的MU-MIMO鲁棒预编码算法虽然可以对抗非理想CSI所导致的系统性能损失,但其只考虑其中一种或两种信道误差的鲁棒性,因此系统性能提升有限.本文通过建立包含信道估计误差、量化误差和延时误差的联合信道误差模型,推导出具有集中式特性的基于最小均方误差（MMSE）的鲁棒波束成形矩阵的闭式解;随后将这种信道条件应用到分布式通信系统,并推导出具有分布式特性的基于信号泄露的MMSE的鲁棒波束成形矩阵的闭式解.数值分析表明,本文所提的集中式和分布式MU-MIMO波束成形算法,与只考虑量化误差的鲁棒MMSE算法相比,具有更优的系统和速率与误码率,补偿了上述三种信道误差所导致的预编码性能损失.     

Graph‐based resource allocation algorithms for multiuser downlink MIMO‐OFDMA networks

Multiuser multiple‐input multiple‐output orthogonal frequency division multiple access (MIMO‐OFDMA) is considered as the practical method to attain the capacity promised by multiple antennas in the downlink direction. However, the joint calculation of precoding/beamforming and resource allocation required by the optimal algorithms is computationally prohibitive. This paper proposes computationally efficient resource allocation algorithms that can be invoked after the precoding and beamforming operations. To support stringent and diverse quality of service requirements, previous works have shown that the resource allocation algorithm must be able to guarantee a specific data rate to each user. The constraint matrix defined by the resource allocation problem with these data rate constraints provides a special structure that lends to efficient solution of the problem. On the basis of the standard graph theory and the Lagrangian relaxation, we develop an optimal resource allocation algorithm that exploits this structure to reduce the required execution time. Moreover, a lower‐complexity suboptimal algorithm is introduced. Extensive simulations are conducted to evaluate the computational and system‐level performance. It is shown that the proposed resource allocation algorithms attain the optimal solution at a much lower computational overhead compared with general‐purpose optimization algorithms used by previous MIMO‐OFDMA resource allocation approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

Reliability feedback–aided low‐complexity detection in uplink massive MIMO systems

Massive multiple‐input multiple‐output (MIMO) plays a crucial role in realizing the demand for higher data rates and improved quality of service for 5G and beyond communication systems. Reliable detection of transmitted information bits from all the users is one of the challenging tasks for practical implementation of massive‐MIMO systems. The conventional linear detectors such as zero forcing (ZF) and minimum mean square error (MMSE) achieve near‐optimal bit error rate (BER) performance. However, ZF and MMSE require large dimensional matrix inversion which induces high computational complexity for symbol detection in such systems. This motivates for devising alternate low‐complexity near‐optimal detection algorithms for uplink massive‐MIMO systems. In this work, we propose an ordered sequential detection algorithm that exploits the concept of reliability feedback for achieving near‐optimal performance in uplink massive‐MIMO systems. In the proposed algorithm, symbol corresponding to each user is detected in an ordered sequence by canceling the interference from all the other users, followed by reliability feedback‐based decision. Incorporation of the sequence ordering and the reliability feedback‐based decision enhances the interference cancellation, which reduces the error propagation in sequential detection, and thus, improves the BER performance. Simulation results show that the proposed algorithm significantly outperforms recently reported massive‐MIMO detection techniques in terms of BER performance. In addition, the computational complexity of the proposed algorithm is substantially lower than that of the existing algorithms for the same BER. This indicates that the proposed algorithm exhibits a desirable trade‐off between the complexity and the performance for massive‐MIMO systems.     

Joint beamforming and power control in downlink multiuser multiple‐input multiple‐output systems

In this paper, we study joint beamforming and power control for downlink multiple‐input multiple‐output systems with multiple users and target values for signal‐to‐interference plus noise ratios (SINRs). We formulate this as a constrained optimization problem of minimizing total interference subject to constraints on the beamforming vector norms, target SINRs, and total transmit power. Necessary and sufficient conditions satisfied by the optimal beamformer and power allocation are presented, and a new algorithm for joint beamforming and power control is proposed. This adapts the beamforming vectors and transmit powers incrementally, and it stops when the specified SINR targets are achieved with minimum powers. The proposed algorithm is illustrated with numerical results obtained from simulations, which study its convergence and compare it with other similar algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

异构网中宏、微基站间存在频偏时的干扰协调方法

该文考虑骨干网只能进行少量信息交换的多载波异构蜂窝网络,研究微系统进行下行传输时对宏系统的干扰协调问题。针对多载波宏基站和微基站之间存在频偏的场景,在保证对宏用户的干扰小于预定干扰门限的前提下,以最大化微系统数据率为目标,在已知瞬时干扰信道和统计干扰信道信息的条件下分别设计最优和次优发射预编码。分析和仿真的结果表明,次优算法只需迭代一次就能达到接近最优算法的性能,因此具有较低的计算复杂度。所提出的方法只需要在宏基站和微基站之间通过骨干网交换少量信息,具有较低的信息共享资源开销。所提出的方法适用于微基站附近存在多个宏用户的场景。     

Low complexity margin adaptive resource allocation in downlink MIMO-OFDMA system

We study the downlink multiuser Multiple Input Multiple Output-Orthogonal Frequency Division Multiple Access (MIMO-OFDMA) system for margin adaptive resource allocation where the Base Station (BS) has to satisfy individual Quality of Service (QoS) constraints of the users subject to transmit power minimization. Low complexity solutions involve beamforming techniques for multiuser inter-stream interference cancellation. However, when beamforming is introduced in the margin adaptive objective, it becomes a joint beamforming and resource allocation problem. We propose a sub-optimal twostep solution which decouples beamforming from subcarrier and power allocation. First a reduced number of user groups are formed and then the problem is formulated as a convex optimization problem. Finally an efficient algorithm is developed which allocates the best user group to each subcarrier. Simulation results reveal comparable performance with the hugely complex optimal solution.     

Robust Cognitive Beamforming With Bounded Channel Uncertainties

This paper studies the robust beamforming design for a multi-antenna cognitive radio (CR) network, which transmits to multiple secondary users (SUs) and coexists with a primary network of multiple users. We aim to maximize the minimum of the received signal-to-interference-plus-noise ratios (SINRs) of the SUs, subject to the constraints of the total SU transmit power and the received interference power at the primary users (PUs) by optimizing the beamforming vectors at the SU transmitter based on imperfect channel state information (CSI). To model the uncertainty in CSI, we consider a bounded region for both cases of channel matrices and channel covariance matrices. As such, the optimization is done while satisfying the interference constraints for all possible CSI error realizations. We shall first derive equivalent conditions for the interference constraints and then convert the problems into the form of semi-definite programming (SDP) with the aid of rank relaxation, which leads to iterative algorithms for obtaining the robust optimal beamforming solution. Results demonstrate the achieved robustness and the performance gain over conventional approaches and that the proposed algorithms can obtain the exact robust optimal solution with high probability.      

On the Performance of Cellular Two-Way Relay Systems with Analog Network Coding and Multiuser Diversity

We consider a cellular two-way relaying system in which a multi-antenna base station (BS) communicates bidirectionally with one of several single-antenna mobile stations (MSs) via a single-antenna relay using analog network coding. We employ MS selection coupled with beamforming at the BS so as to maximize the end-to-end signal-to-noise ratios. In the considered system, the target rates at the sources can generally be different owing to the asymmetric traffic flow in opposite directions. With such a general setup, we perform an overall system outage probability analysis over Rayleigh fading channels. For more insights, we derive a closed-form asymptotic expression for overall outage probability and an upper bound expression for ergodic sum-rate of the system. Based on these expressions, we show that the system achieves a performance gain, and a diversity order of minimum of the number of BS antennas and the number of MSs. Moreover, we address the problem of optimization of relay location in order to minimize the overall system outage under asymmetric traffic conditions. Finally, we provide numerical and simulation results to corroborate the theoretical analysis and the advantages offered by the proposed scheme.     

Optimal designs of collaborative relay‐assisted multiuser beamforming for cellular systems

With careful calculation of signal forwarding weights, relay nodes can be used to work collaboratively to enhance downlink transmission performance by forming a virtual multiple‐input multiple‐output beamforming system. Although collaborative relay beamforming schemes for single user have been widely investigated for cellular systems in previous literatures, there are few studies on the relay beamforming for multiusers. In this paper, we study the collaborative downlink signal transmission with multiple amplify‐and‐forward relay nodes for multiusers in cellular systems. We propose two new algorithms to determine the beamforming weights with the same objective of minimizing power consumption of the relay nodes. In the first algorithm, we aim to guarantee the received signal‐to‐noise ratio at multiusers for the relay beamforming with orthogonal channels. We prove that the solution obtained by a semidefinite relaxation technology is optimal. In the second algorithm, we propose an iterative algorithm that jointly selects the base station antennas and optimizes the relay beamforming weights to reach the target signal‐to‐interference‐and‐noise ratio at multiusers with nonorthogonal channels. Numerical results validate our theoretical analysis and demonstrate that the proposed optimal schemes can effectively reduce the relay power consumption compared with several other beamforming approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

Joint hybrid beamforming and power splitting design in millimeter-wave simultaneous wireless information and power transfer system

A joint hybrid beamforming and power splitting(JHBPS) design problem for simultaneous wireless information and power transfer(SWIPT) in millimeter-wave(mmWave) system is studied.The considered scenario is a multi-antenna base station(BS) transfers information and energy simultaneously to multiple single-antenna receivers.BS adopts hybrid digital and analog beamforming architecture to reduce hardware costs.Receivers separate acquired signals with power splitters either for information decoding(ID) or energy harvesting(EH).The aim is minimizing total transmission power by joint design of hybrid beamforming and PS under ID and EH requirements.It is difficult to obtain the optimal hybrid beamformer directly since the analog beamformer and digital beamformer are multiplied.Therefore,a two-stage algorithm is proposed to solve the problem.In the first stage,the optimal beamformer and PS ratios are obtained by solving the joint transmission beamforming and PS design problem.In the second stage,the optimal beamformer is approximated with the product of analog beamformer and digital beamformer.The superiority of proposed algorithm over the existing algorithms is demonstrated through simulations.Moreover,the effectiveness of approximation algorithm is testified.     

System evaluation of optimal downlink beamforming with congestion control in wireless communication

We investigate the use of congestion control and joint optimal downlink beamforming, power control, and access point allocation, in a multi-cell wireless communication system. The access points of the system employ smart antennas and single antennas are used at the terminals. The possibility to send messages to multiple terminals at the same frequency in the same time slot is exploited. We show how previously proposed algorithms for optimal downlink beamforming easily can be extended to determine also the optimal access point for each mobile terminal. In order to assign resources, optimal beamforming requires a feasible set of mobiles, i.e. that all admitted users can be offered the required signal-to-interference-and-noise ratio. Therefore, an algorithm for deciding which mobile terminals to admit or reject from a congested system is proposed and evaluated. Using the proposed congestion algorithm, joint optimal downlink beamforming is evaluated and the throughput increase as compared to decentralized beamforming algorithms and other congestion control strategies is assessed from a system point of view. The results show that the proposed strategy can almost double the throughput compared to decentralized beamforming algorithms and give a fivefold increase in throughput compared to conventional beamforming without any interference suppression.     

User clustering and robust beamforming design in multicell MIMO-NOMA system for 5G communications

In this paper, we present a robust beamforming design to tackle the weighted sum-rate maximization (WSRM) problem in a multicell multiple-input multiple-output (MIMO) – non-orthogonal multiple access (NOMA) downlink system for 5G wireless communications. This work consider the imperfect channel state information (CSI) at the base station (BS) by adding uncertainties to channel estimation matrices as the worst-case model i.e., singular value uncertainty model (SVUM). With this observation, the WSRM problem is formulated subject to the transmit power constraints at the BS. The objective problem is known as non-deterministic polynomial (NP) problem which is difficult to solve. We propose an robust beamforming design which establishes on majorization minimization (MM) technique to find the optimal transmit beamforming matrix, as well as efficiently solve the objective problem. In addition, we also propose a joint user clustering and power allocation (JUCPA) algorithm in which the best user pair is selected as a cluster to attain a higher sum-rate. Extensive numerical results are provided to show that the proposed robust beamforming design together with the proposed JUCPA algorithm significantly increases the performance in term of sum-rate as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.     

Biorthogonal Frequency Division Multiple Access Cellular System with Angle Division Reuse Scheme

In conventional OFDMA cellular systems, mobile stations (MSs) suffer from large ICI in fully loaded cellular environments with full cell frequency reuse, especially at the cell-edge. The fundamental cause is that the signals from serving Base Station (BS) and interference BSs, are modulated by same exponential bases, at same subcarrier. In this paper, a generalized low-complexity fractional Fourier transform (FrFT) based biorthogonal frequency division multiple access (B-OFDMA) cellular system with multiple angle division reuse scheme (MADR) scheme for inter-cell interference (ICI) cancellation is proposed. FrFT angle is regarded as a kind of time-frequency combination resource (TFCR), and it can be optimally allocated to each BS of the cellular system, based on simplified minimal base correlation coefficient (MBCC) criteria, which confirms the inner-cell mutual orthogonality between modulating bases at different subcarriers, and inter-cell mutual approximate orthogonality between modulating bases at same subcarriers. Therefore, at the receiver, ICI can be dramatically suppressed by MMSE equalization and correlative detection in respective optimal FrFT domain. Extensive system simulations are conducted for various practical scenarios to demonstrate the superior performance of the proposed FrFT MADR scheme in bit error rate (BER) and system throughput, especially for cell-edge MSs, compared with conventional OFDMA cellular with different ICI cancellation schemes and scheduling schemes.     

Joint precoding and power allocation for multiuser transmission in MIMO relay networks

This paper proposes a joint precoding and power allocation strategy to maximize the sum rate of multiuser multiple‐input multiple‐output (MIMO) relay networks. A two‐hop relay link working on amplify‐and‐forward (AF) mode is considered. Precoding and power allocation are designed jointly at the base station (BS). It is assumed that there are no direct links between the BS and users. Under individual power constraints at the BS and relay station, precoders designed based on zero forcing, minimum mean‐square error and maximum ratio transmission are derived, respectively. Optimal power allocation strategies for these precoders are given separately. To demonstrate the performance of the proposed strategies, we simulate the uncoded bit error rate performance of the underlined system. We also show the difference of the sum rate of the system with the optimal power allocation strategies and with average power transmission. The simulation results show the advantages of the proposed joint precoding and power allocation strategies as expected. Copyright © 2011 John Wiley & Sons, Ltd.     

基于联合用户分组及天线选择的大规模MIMO波束成形

大规模MIMO系统中,当小区用户数与基站天线数较大时,各用户的信道条件不尽相同,提出一种适用于大规模MIMO下行链路的基于联合用户分组及天线选择的迫零波束成形算法。将用户分成两组,选择信道条件较优的一组用户来接收信号,并为每一个发送数据流选择最优的基站天线组合进行通信,以较小的性能损失,换取大规模MIMO 射频电路的成本与功耗的大幅度降低。仿真结果证明,该算法能够较好地实现系统性能与硬件复杂度的折中。     

多小区MU-MIMO系统中基于泄露干扰迫零的分布式块对角化预编码设计

该文对多小区MU-MIMO中的预编码设计进行了研究。通过将单小区块对角化预编码进行扩展,将泄漏到邻小区的干扰纳入考虑范围,采用泄露干扰迫零的块对角化预编码,利用发送端提供的额外自由度直接将泄露干扰进行子空间迫零,消除泄露干扰,并且小区内用户之间也进行子空间迫零,消除用户间干扰;从而降低小区间干扰对多用户MIMO系统的不利影响。并且对本文所提算法复杂度进行了定量分析,表明该方案具有较低的计算复杂度。最后通过仿真全面分析了不同参数条件下的系统性能,结果显示该方法能够提高系统的传输速率。      

A Low Complexity Correlation Algorithm for Compressive Channel Estimation in Massive MIMO System

Channel state information is essential for base station (BS) to fully exploit the merits of massive multiple input multiple output, which consumes large amount of pilot overhead attributed to tremendous number of BS antennas. Accordingly, huge computational complexity of correlation operation tends to be an obstacle for the implementation of compressive channel estimation algorithms, especially for greedy algorithms. In this paper, pilot overhead problem lightens by exploiting common support property due to the close space of BS antenna array. Furthermore, a low complexity correlation algorithm is proposed for each iteration of greedy algorithm, which exploits the inherent of pilot distribution and sensing matrix composed of pilot sequence. Complexity of proposed algorithm related to pilot distribution is also investigated. Performance analysis and simulation results prove that the proposed algorithm maintains the same performance, while achieves much less computational complexity than the original greedy algorithm.     

Downlink beamforming for DS-CDMA mobile radio with multimediaservices

Downlink beamforming is a promising technique for direct-sequence code-division multiple-access (DS-CDMA) systems with multimedia services to effectively reduce strong interference induced by high data rate users. A new downlink beamforming technique is proposed that converts the downlink beamforming problem into a virtual uplink one and takes into account the data rate information of all users. Since the main complexity of this method is due to the existence of multidelay paths, two simplified algorithms are suggested using an equivalent one-path channel vector to replace multipath channel vectors. Computer simulation results are given to evaluate the downlink capacity of DS-CDMA systems using a base station antenna array and the new algorithms proposed