Opportunistic Feedback for Multiuser MIMO Systems With Linear Receivers

A novel multiuser scheduling and feedback strategy for the multiple-input multiple-output (MIMO) downlink is proposed in this paper. It achieves multiuser diversity gain without substantial feedback requirements. The proposed strategy uses per-antenna scheduling at the base station, which maps each transmit antenna at the base station (equivalently, a spatial channel) to a user. Each user has a number of receive antennas that is greater than or equal to the number of transmit antennas at the base station. Zero-forcing receivers are deployed by each user to decode the transmitted data streams. In this system, the base station requires users' channel quality on each spatial channel for scheduling. An opportunistic feedback protocol is proposed to reduce the feedback requirements. The proposed protocol uses a contention channel that consists of a fixed number of feedback minislots to convey channel state information. Feedback control parameters including the channel quality threshold and the random access feedback probability are jointly adjusted to maximize the average throughput performance of this system. Multiple receive antennas at the base station are used on the feedback channel to allow decoding multiple feedback messages sent simultaneously by different users. This further reduces the bandwidth of the feedback channel. Iterative search algorithms are proposed to solve the optimization for selection of these parameters under both scenarios that the cumulative distribution functions of users are known or unknown to the base station     

多用户MIMO系统在有限反馈下结合预编码与调度算法的研究

捅要：研究了多用户多输入多输出（MIMO）系统在有限反馈下的一种结合单位预编码与用户调度算法的方案。在该系统中每一用户都具有多个接收天线,该方案具有较大的多用户分集增益和较小的计算复杂度,从而能够减少系统中的用户间干扰。每个用户独立地决定自己的天线合并矢量,并将最优波束矢量以及对应的估计信干噪比通过有限反馈信道反馈给基站,此时基站获取了相应的用户信道信息和用户间干扰信息。基于接收到的反馈信息,基站从预定义的码本中选取和速率最大的最优子集进行系统预编码,然后依照预编码矩阵调度欧氏距离最小的用户且用户个数不超过发送天线的数目。仿真结果显示该方案有效地改善了系统速率,特别是在用户数目较多或者信道环境较好的情况下。     

Grassmannian precoding MU-MIMO scheme

In this article, a Grassmannian precoding multiuser multiple-input multiple-output （MU-MIMO） scheme for downlink transmission is proposed. The proposed MU-MIMO scheme will perform scheduling and precoding simultaneously at the base station, to obtain both the multiuser diversity gain and the precoding gain, to maximize the system capacity. The precoding method is related to Grassmannian precoding, which extends the point-to-point single-user Grassmannian precoding to point-to-multipoint multiuser Grassmannian precoding. It provides further significant system capacity enhancement than the single user MIMO （SU-MIMO） system and also outperforms the block dia~onalization （BD） algorithm under the same simulation environment.     

MIMO Broadcast Scheduling with Limited Feedback

We consider multiuser scheduling with limited feedback of partial channel state information in MIMO broadcast channels. By using spatial multiplexing at the base station (BS) and antenna selection for each user, we propose a multiuser scheduling method that allocates independent information streams from all M transmit antennas to the M most favorable users with the highest signal-to-interference-plus-noise ratio (SINR). A close approximation of the achievable sum-rate throughput for the proposed method is obtained and shown to match the simulation results very well. Moreover, two reduced feedback scheduling approaches are proposed. In the first approach, which we shall refer to as selected feedback scheduling, the users are selected based on their SINR compared to a predesigned threshold. Only those selected users are allowed to feed back limited information to the BS. The resultant feedback load and achievable throughput are derived. It will then be demonstrated that with a proper choice of the threshold, the feedback load can be greatly reduced with a negligible performance loss. The second reduced feedback scheduling approach employs quantization for each user, in which only few bits of quantized SINR are fed back to the BS. Performance analysis will show that even with only 1-bit quantization, the proposed quantized feedback scheduling approach can exploit the multiuser diversity at the expense of slight decrease of throughput.     

多用户MISO系统下行链路的自适应用户选择算法

针对多用户多输入单输出(MISO)系统中的用户选择问题,该文基于多用户系统的容量公式提出一种低复杂度的自适应用户选择算法,使选择的用户数随当前的信道状态自适应变化以最大化所有用户的和速率。仿真结果表明,该算法具有接近最优的性能。在此基础上结合比例公平调度对算法进行改进以保证系统中用户服务的公平性。     

Scheduling Algorithms and Throughput Maximization for the Downlink of Packet-Data Cellular Systems with Multiple Antennas at the Base Station

The capacity-achieving coding scheme for the multiple-input multiple-output (MIMO) broadcast channel is dirty-paper coding. With this type of transmission scheme the optimal number of active users that receive data and the optimal power allocation strategy are highly dependent on the structure of the channel matrix and on the total transmit power available. In the context of packet-data access with adaptive transmission where mobile users are equipped with a single receive antenna and the base station has multiple transmit antennas, we study the optimal number of active users and the optimal power allocation. In the particular case of two transmit antennas, we prove that the optimal number of active users can be a non-monotonic function of the total transmit power. Thus not only the number of users that should optimally be served simultaneously depends on the user channel vectors but also on the power available at the base station transmitter. The expected complexity of optimal scheduling algorithms is thus very high. Yet we then prove that at most as many users as the number of transmit antennas are allocated a large amount of power asymptotically in the high-power region in order to achieve the sum-capacity. Simulations confirm that constraining the number of active users to be no more than the number of transmit antennas incurs only a marginal loss in spectral efficiency. Based on these observations, we propose low-complexity scheduling algorithms with sub-optimal transmission schemes that can approach the sum-capacity of the MIMO broadcast channel by taking advantage of multiuser diversity. The suitability of known antenna selection algorithms is also demonstrated. We consider the cases of complete and partial channel knowledge at the transmitter. We provide simulation results to illustrate our conclusions.     

空间相关信道下的交替多用户调度算法

针对多用户多输入多输出（MIMO）系统,研究了空间相关信道下的多用户调度问题。通过推导用户信道向量夹角的统计特征,分析了多用户调度算法对所调度用户间正交性的影响。分析结果表明在空间相关信道下现有基于串行搜索的调度方法在统计意义上降低了被调度用户之间的正交性,从而导致基于串行搜索的调度算法与最优的穷举搜索之间存在较大的性能差距。为了提高相关信道下多用户MIMO系统的性能,提出了一种基于交替搜索的多用户调度算法及其低复杂度实现方法。仿真结果表明,所提出的用户调度算法能够有效地弥补基于串行搜索的调度方法的性能损失,在空间独立信道和空间相关信道下以较低的计算复杂度获得接近穷举搜索的最优性能。      

MIMO广播信道中联合多用户速率和延迟约束调度的研究

该文给出了一种多入多出高斯广播信道中具有延迟约束的多用户无线数据包的传输方案。首先,在信道的QR分解及脏纸编码基础上,通过贪婪算法获取多用户分集与包延迟约束之间的有效结合。其次,将包到达速率、可达服务速率、用户数以及传输天线数构成一优化问题,得到最佳的用户组合及调度周期。最后,在不同用户数及发射天线数情况下对该方案进行了性能仿真,仿真结果表明：在满足包传递最小延迟等待要求的同时,得到了传输容量的最大化。     

Downlink scheduling of multiuser MIMO systems with transmit beamforming

This article deals with downlink scheduling for multiuser multiple-input multiple-output （MIMO） systems, where the base station communicates with multiple users simultaneously through transmit beamforming. Most of the existing transmission schemes for multiuser MIMO systems focus on optimizing sum rate performance of the system. The individual quality of service （QoS） requirements （such as packet delay and minimum transmission rate for the data traffic） are rarely considered. In this article, a novel scheduling strategy is proposed, where we try to optimize the global system performance under individual QoS constraints. By performing scheduling into two steps, namely successive user selection and power allocation, the scheduler can achieve efficient resource utilization while maintaining the QoS requirements of all users. Extensive simulations and analysis are given to show the effectiveness of the proposed scheduler.     

On Scheduling for Multiple-Antenna Wireless Networks Using Contention-Based Feedback

Multiuser diversity gain is an effective technique for improving the performance of wireless networks. This gain can be exploited by scheduling the users with the best current channel conditions. However, this kind of scheduling requires that the base station (or access point) knows some kind of channel quality indicator (CQI) information for every user in the system. When the wireless link lacks channel reciprocity, each user must feed back this CQI information to the base station. The required feedback load makes exploiting multiuser diversity extremely difficult when the number of users becomes large. To alleviate this problem, this paper considers a contention-based CQI feedback where only users whose channel gains are larger than a threshold are allowed to transmit their CQI information through a spread-spectrum based contention channel. Considering the capture effect in this contention channel, it is shown that i) the multiuser diversity gain can be exploited regardless of the number of transmit antennas at the base station and ii) the total system throughput exponentially approaches that of the full feedback scheme as the spreading code length of the contention channel linearly increases. In addition, it is also shown that multiuser diversity can be maintained with the feedback delay of time-variant channels. We also consider the issue of differentiated rate scheduling, in which the base station gives different rates to different subsets of mobiles. In this scenario, mobiles feed back their CQI with some access probability, and we show this technique causes only a negligible throughput loss compared to the case without supporting differentiated rate.     

Low Complexity Suboptimal User Selection Algorithm for Multiuser MIMO Systems with Block Diagonalization

In downlink multiuser multiple-input multiple-output (MU-MIMO) systems, block diagonalization (BD) is a well-kown precoding technique that eliminates interuser interference. The number of simultaneously supportable users with BD is limited by the number of base station transmit antennas and the number of user receive antennas. The brute-force search for the optimal user set, however, is computationally prohibitive. Therefore, we propose a low complexity and suboptimal user selection algorithm based on block diagonalization for MU-MIMO systems. We introduce a strong tight upper bound of sum capacity as selection metric. Furthermore, we employ a substitution operation to improve system performance. The computational complexity analysis and simulation results show that the proposed algorithm achieves comparable throughput with low complexity compared to the existing algorithms.     

Opportunistic Space-Division Multiple Access With Beam Selection

In this paper, a novel transmission technique for the multiple-input multiple-output (MIMO) broadcast channel is proposed that allows simultaneous transmission to multiple users with limited feedback from each user. During a training phase, the base station modulates a training sequence on multiple sets of randomly chosen orthogonal beamforming vectors. Each user sends the index of the best beamforming vector and the corresponding signal-to-interference-plus-noise ratio for that set of orthogonal vectors back to the base station. The base station opportunistically determines the users and corresponding orthogonal vectors that maximize the sum capacity. Based on the capacity expressions, the optimal amount of training to maximize the sum capacity is derived as a function of the system parameters. The main advantage of the proposed system is that it provides throughput gains for the MIMO broadcast channel with a small feedback overhead, and provides these gains even with a small number of active users. Numerical simulations show that a 20% gain in sum capacity is achieved (for a small number of users) over conventional opportunistic space division multiple access, and a 100% gain (for a large number of users) over conventional opportunistic beamforming when the number of transmit antennas is four.     

Efficient user selection for multi-cell multi-user MIMO systems with limited backhaul

Multi-cell multi-user multiple-input multiple-output (MC-MU-MIMO) is a promising technique to eliminate inter-user interference and inter-cell cochannel interference in wireless telecommunication syste...     

上行多用户MIMO系统中的用户与天线联合选择方案

在多用户MIMO系统中,基站所能同时进行通信的用户数受到基站和用户端天线数的限制,随着用户数的增加,系统的性能反而会降低,因此,用户选择技术就成为一种改善系统性能的有效技术.在本文中,针对上行多用户MIMO系统提出了一种低复杂度的用户选择算法.为获得更大的系统性能,在用户选择的基础上,进一步提出了一种用户与天线联合选择算法.这两种算法在极大地简化计算复杂度的条件下,提供了与最优算法几乎相同的性能.     

Joint utility function-based scheduling for two-way communication services in wireless networks

A type of joint utility function-based scheduling is proposed for two-way communication services in wireless networks. The scheduling of uplink and downlink services is done jointly so that the base station selects a user efficiently and fairly while considering the channel state of both the uplink and the downlink. Because a user generally has two communication links, an uplink and a downlink, the overall satisfaction with a communication service can be formulated as the sum of the quality of the uplink and downlink services. However, most of the previous types of scheduling for the uplink and downlink were designed separately and independently. This paper proposes a joint scheduling algorithm for integrated uplink and downlink services: a base station selects a user while simultaneously considering both the uplink channel state and the downlink channel state. An analytical model is developed for the purpose of determining the scheduling metric, the system throughput, and the level of fairness. The numerical and computer simulation results show that in comparison with conventional proportional fair scheduling the proposed joint scheduling achieves a better throughput while satisfying the fairness among users.     

An overview of scheduling algorithms in MIMO-based fourth-generation wireless systems

In this article an overview of the scheduling algorithms proposed for fourth-generation multiuser wireless networks based on multiple-input multiple-output technology is presented. In MIMO systems a multi-user diversity gain can be extracted by tracking the channel fluctuations between each user and the base station, and scheduling transmission for the "best" user. Based on this idea, several opportunistic scheduling schemes that attempt to improve global capacity or satisfy users with different QoS requirements have been proposed. Transmit beamforming procedures aimed at increasing the channel fluctuations have been proposed. The simultaneous exploitation of both spatial and multi-user diversity is not straightforward; however, it may be achieved by a refined selection of the "best" user. In addition, a multiple access gain can be obtained from a simple SDMA/TOMA system. Finally, several resource allocation schemes are discussed for this hybrid multiple access system.     

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.     

多用户MIMO系统下行链路的随机多波束复用技术

该文提出了一种随机多波束多用户复用技术,充分利用多用户分集以及基站多天线的空间自由度来提高系统吞吐量。不同于传统的随机波束形成技术,该技术首先在给定预编码码本内随机选取一个码字,然后调度多个空分复用用户以及其余预编码矩阵。该文采用了一种逐次调度的方式,第一次训练调度一个主发送用户并确定一个次发送预编码矩阵,通过第二次训练选择次发送用户,这种方式能以很小的反馈开销有效控制复用用户之间的相互干扰。同时,该文所提技术能进一步推广到用户具有不同天线配置的异构情形。仿真结果表明,该文技术在具有不同相关性的信道环境下都能获得较优的系统吞吐量。     

QoS‐Guaranteed Multiuser Scheduling in MIMO Broadcast Channels

This paper proposes a new multiuser scheduling algorithm that can simultaneously support a variety of different quality‐of‐service (QoS) user groups while satisfying fairness among users in the same QoS group in MIMO broadcast channels. Toward this goal, the proposed algorithm consists of two parts: a QoS‐aware fair (QF) scheduling within a QoS group and an antenna trade‐off scheme between different QoS groups. The proposed QF scheduling algorithm finds a user set from a certain QoS group which can satisfy the fairness among users in terms of throughput or delay. The antenna trade‐off scheme can minimize the QoS violations of a higher priority user group by trading off the number of transmit antennas allocated to different QoS groups. Numerical results demonstrate that the proposed QF scheduling method satisfies different types of fairness among users and can adjust the degree of fairness among them. The antenna trade‐off scheme combined with QF scheduling can improve the probability of QoS‐guaranteed transmission when supporting different QoS groups.     

一种多用户MIMO系统的公平调度算法

多用户多输入多输出(MIMO)系统中需要对用户进行合理调度,一般基于信道增益的调度算法忽略了用户之间的公平性。基于此,提出了一种公平的多用户调度算法,其思想是先根据信道条件数初选出用户,然后统计每个用户被选择的次数,如果次数之差的绝对值大于设定门限,则选择次数少的用户。这样既能获得多用户分集增益又兼顾了公平性。仿真结果表明,提出的调度算法在系统性能无明显损失的情况下保证了用户公平性。