用于MIMO广播信道的带多波束选择的正交随机波束成形算法

本文提出一种基于有限反馈的波束和用户选择方案,在这种方案中,用户端利用一个随机正交码本对其信道方向信息(CDI)进行量化,计算其最大信号与干扰加噪声功率比(SINR),并把这些信息反馈给基站;基站根据接收到的这些反馈信息,按照和容量最大的准则选择出多个正交波束以及相应的多个用户.和sharif等人最近提出的方案相比,我们提出的方案能根据系统参数,如用户数和信噪比(SNR),对选择的波束成形矢量及其对应的用户的数量和集合进行调整,当用户数量较小时,和容量性能得到了很大的提升,同时避免了选择波束成形矢量时的用户冲突,另外,基站也不需要广播波束成形矢量给各个用户.     

Hybrid zero-forcing beamforming/orthogonal beamforming with user selection for MIMO broadcast channels

This letter proposes a hybrid transmission scheme by combining zero-forcing beamforming (ZFBF) and orthogonal beamforming (OBF) for the multiple-input multiple-output broadcast channel. This method first utilizes ZFBF for only a part of the scheduled users with approximately orthogonal channels. By further constructing orthogonal beamformers in the null space of the ZFBF user channels, it then employs OBF for the rest of users to fully exploit the spatial dimension. Theoretical analysis, as well as simulation results, verify that our scheme outperforms the conventional ZFBF scheme and OBF scheme with user selection.     

智能反射表面辅助的非正交多址接入系统用户分组、波束赋形与相移的优化

该文研究智能反射表面(IRS)辅助的多天线非正交多址接入(NOMA)网络中用户分组、发送波束赋形、相移等的联合优化问题。系统中1个分组分配1个波束并在组内进行连续干扰消除检测。该文提出一种不依赖于发送波束赋形和IRS相移的用户分组配对策略,将用户分组与其他优化分离,显著降低了优化问题求解的难度和计算复杂度。进一步,联合优化基站发送波束赋形、功率分配和IRS相移矩阵,最小化基站的总发送功率。原始优化问题是一个多变量相互耦合的非凸优化问题,利用松弛变量、连续凸逼近、半定松弛、交替迭代优化等方法将原问题转化为凸问题并求解。仿真结果显示,相较于1个用户1个波束的方案,所提方案在基站天线数较少时性能更优,而在天线数较多时也与该对比方案非常接近,但所提方案的优化计算复杂度更低。而对比采用不同分组算法、随机IRS相移方案、最大比发射方案,以及无IRS的方案,所提方案的性能始终更优。     

Enhanced Unitary Beamforming Scheme for Limited-Feedback Multiuser MIMO Systems

In this letter, we consider practical downlink multiuser multiple-input multiple-output systems where each user has multiple antennas and codebook-based limited channel feedback is available at base station. We propose a preprocessing scheme for downlink transmission where a unitary beamforming matrix is used. Firstly, we propose how to construct the unitary matrix that maximizes sum rate. Secondly, we propose a codebook-based channel feedback method for the proposed beamforming method. Numerical results show that the proposed scheme outperforms conventional zero-forcing beamforming scheme in terms of sum rate.     

A study of opportunism for multiple-antenna systems

Recently proposed opportunistic beamforming exploits the multiuser diversity to reduce the feedback by not requiring the precoding information used for closed-loop schemes to be known at the transmitter. Opportunism could also be beneficially employed for other multiple-antenna transmission techniques like cophasing and antenna selection. For opportunistic beamforming and antenna selection, we give closed-form expressions for throughput that closely approximate the performance of these schemes with a Proportionally Fair scheduler (PFS) at low signal-to-noise ratios (SNRs). For large number of transmit antennas, opportunistic cophasing has similar performance as opportunistic beamforming. Asymptotic dependence of the required number of users to achieve the gains of opportunism on the number of transmit antennas is exponential for opportunistic beamforming (and cophasing for large numbers of transmit antennas), and at best linear for opportunistic antenna selection. For multiple-antenna receivers, we additionally examine an opportunistic multiple-input multiple-output (MIMO) scheme that transmits multiple data streams simultaneously to the same user.     

The Effect of Finite Rate Feedback on CDMA Signature Optimization and MIMO Beamforming Vector Selection

We analyze the effect of finite rate feedback on code-division multiple-access (CDMA) signature optimization and multiple-input multiple-output (MIMO) beamforming vector selection. In CDMA signature optimization, for a particular user, the receiver selects a signature vector from a codebook to best avoid interference from other users, and then feeds the corresponding index back to the specified user. For MIMO beamforming vector selection, the receiver chooses a beamforming vector from a given codebook to maximize the instantaneous information rate, and feeds back the corresponding index to the transmitter. These two problems are dual: both can be modeled as selecting a unit norm vector from a finite size codebook to ldquomatchrdquo a randomly generated Gaussian matrix. Assuming that the feedback link is rate limited, our main result is an exact asymptotic performance formula where the length of the signature/beamforming vector, the dimensions of interference/channel matrix, and the feedback rate approach infinity with constant ratios. The proof rests on the large deviations of the underlying random matrix ensemble. Further, we show that random codebooks generated from the isotropic distribution are asymptotically optimal not only on average, but also in probability.     

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.     

大规模天线SWIPT的安全速率性能分析

多入单出广播系统中,现有研究均是在完整信道状态信息下来优化单用户安全速率,而实际上,系统中不可能只存在一个用户,基站往往接收到的也是不完整信道状态信息.针对此问题,提出了一种顽健性波束成形方案.在多用户情况下,考虑信道估计误差对系统安全速率的影响,采用粒子群算法来联合优化发射波束成形矢量、人工噪声协方差和功率分流比,从而在确保用户收集一定能量的同时最大化安全传输速率.仿真结果表明,所提方案相对于理想情况下的安全速率略微降低,但考虑到存在窃听用户和估计误差的情况,对实际系统具有指导意义.     

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.     

认知无线电网络中基于主系统有限反馈的频谱共享方案

摘 要：提出一种频谱共享方案,该方案适用于同时存在多个主用户和一对次用户的场景。各主用户依据接收机反馈的有限信道质量信息（CQI, channel quality information）分配发送功率及传输速率。次用户根据偷听到的主系统CQI有限反馈,以适当的功率及速率接入信道。次用户接入信道的行为对各主用户造成一定干扰,以致主系统传输速率遭受一定损失。本文在主系统速率损失约束条件下,研究得出了使次系统吞吐量最大化的次用户发送功率及传输速率最佳分配方案。数值结果表明,对于每个主用户仅需反馈3-4个量化比特,次系统的有效吞吐量就可堪比于主次发射端均拥有主系统链路完整CQI的情况。仿真结果显示,所提出的频谱共享方案能够满足主系统速率损失约束。     

Throughput-Optimal Precoding and Rate Allocation for MISO Systems With Noisy Feedback Channels

A throughput metric is considered for a multiple-input single-output (MISO) system with noisy feedback of channel state information (CSI). The goal is to optimize a precoding matrix with a medium-access control layer metric. The problem is a nonlinear multidimensional optimization. Results show that the optimal precoding turns into beamforming when the signal-to-noise ratio (SNR) of CSI feedback is sufficiently large. A necessary condition for the optimality of beamforming under the throughput metric is determined, and the necessary and sufficient condition is numerically found based on the Gauss-Chebyshev Quadrature method. Next, the rate allocation for beamforming and spatial diversity is analyzed. Then, a two-mode transmission scheme is proposed such that the transmitter is engaged in either the beamforming mode or the spatial diversity mode depending on the SNR of the CSI feedback. It is shown that at a fairly high SNR of CSI feedback, the rate allocation needs to be reduced, while at a low SNR of CSI feedback, the allocated rate should be increased. It is shown that when the SNR of CSI feedback is lower than a threshold, there always exists an SNR of the transmitted signal such that the CSI feedback can be viewed as the real CSI solely for the purpose of rate allocation. The result also shows that the throughput of two-mode transmission is almost the same as the throughput of the optimal precoding scheme, even with a low SNR and large feedback delay.     

Opportunistic Beamforming over Rayleigh Channels with Partial Side Information

In recent years, diversity techniques have evolved into highly attractive technology for wireless communications in different forms. For instance, the channel fluctuations of the users in a network are exploited as multiuser diversity by scheduling the user with the best signal-to-noise ratio (SNR). When fading is slow, beamforming at a multiple antenna transmitter is used to induce artificial channel fluctuations to ensure multiuser diversity in the network. Such a beamforming scheme is called opportunistic beamforming since the transmitter uses random beamforming to artificially induce opportunism in the network [1]. Opportunism requires a large number of users in the system in order to reach the performance of the true beamforming that uses perfect channel state information (CSI). In this paper we investigate the benefit of having partial CSI at an opportunistic transmitter. In the investigation, we focus on the maximum normalized SNR scheduling where user?s feedback consists of SNR relative to its channel gain. We show that opportunism can be beneficially used to increase the average throughput of the system. Simulations support the analytical average throughput results obtained as the amount of CSI and the number of users vary.     

针对非理想定时同步的多模协作多点传输

针对非理想定时同步对协作多点传输的负面影响,提出了多模协作多点传输算法。通过推导协作波束成形模式和联合处理模式在非理想定时同步条件下的平均可达速率,得到模式选择变量和模式选择门限。在多模协作多点传输算法中,用户首先对定时同步误差进行估计,并计算其模式选择变量和模式选择门限。然后用户选择协作多点传输的下行传输模式,并将其选择结果反馈给协作基站。最后,根据各用户的反馈,协作基站以最大化平均可达传输速率为准则,自适应地在协作波束成形模式和联合处理模式之间切换。仿真结果表明多模协作多点传输算法在定时同步误差较小时,采用联合处理模式,以保持空间复用增益,在定时同步误差较大时,采用协作波束成形模式,以避免用户间的额外干扰。因此,在非理想定时同步误差条件下,多模协作多点传输算法比仅采用协作波束成形模式或联合处理模式的传统协作多点传输算法具有更好的性能。     

Error Analysis of Grouped Multilevel Space-Time Trellis Coding with the Combined Application of Massive MIMO and Cognitive Radio

In today’s scenario, demand for error-correcting codes with minimal error constraints for wireless communications. Multilevel coding scheme with trellis codes as component codes provides flexible data transmission rates, coding gain, diversity gain with improved spectral efficiency and low decoding complexity. This paper investigates the potential improvements by using the Multilevel coding scheme with massive Multiple-Input Multiple-Output in Cognitive Radio Networks with trellis codes as component codes. This paper discussed space-time coding with beamforming and antenna grouping according to the channel state information. Multilevel Space-time coding is based on multi-level Quadrature Amplitude Modulation signaling and beamforming to mitigate the effect of primary users for the enactment of secondary users in Cognitive Radio. The primary users provide channels dynamically to the secondary user for an unknown duration. Our transmission use Quadrature Amplitude Modulation based signals, with an adaptive grouping of antenna which weight according to the optimization, which inherently depends upon the resource allocation of the secondary user. The results show that the proposed coded system achieves Bit error rate/Symbol error rate/Frame error rate and Signal to noise ratio varies according to sources sensing time.

     

Effective channel control random beamforming for single user MIMO systems

In general, it has been demonstrated that the performance of conventional random beamforming (RBF) approaches that of ideal eigen beamforming when the number of users is large in a cell by exploiting multi-user diversity. However, if the number of users decreases, such as femto or pico cell in the 3GPP Long Term Evolution-Advanced standard, the performance degradation occurs in the RBF scheme due to the lack of multi-user diversity. In this paper, we present a novel precoder based on singular value decomposition (SVD) using feedback of weight values in an RBF environment. For achieving performance improvement in the femto cell environment, we generate a precoding matrix appropriate to user channel by controlling the feedback values with an equivalent feedback quantity. In the simulation results, we verify the outstanding performance of the proposed scheme for a small number of users.     

The optimality of beamforming in uplink multiuser wireless systems

This paper considers the optimal uplink transmission strategy that achieves the sum-capacity in a multiuser multi-antenna wireless system. Assuming an independent identically distributed block-fading model with transmitter channel side information, beamforming for each remote user is shown to be necessary for achieving sum-capacity when there is a large number of users in the system. This result stands even in the case where each user is equipped with a large number of transmit antennas, and it can be readily extended to channels with intersymbol interference if an orthogonal frequency division multiplexing modulation is assumed. This result is obtained by deriving a rank bound on the transmit covariance matrices, and it suggests that all users should cooperate by each user using only a small portion of available dimensions. Based on the result, a suboptimal transmit scheme is proposed for the situation where only partial channel side information is available at each transmitter. Simulations show that the suboptimal scheme is not only able to achieve a sum rate very close to the capacity, but also insensitive to channel estimation error.     

Low complexity resource allocation and scheduling algorithms for downlink SDMA systems

The downlink zero-forcing beamforming strategy in the case of random packet arrivals is investigated. Under this setting, the relevant fairness criterion is the stabilization of all buffer queues which guarantees a bounded average delay for all users. It has been shown that allocating resources to maximize a queue-length-weighted sum of the rates is a stabilizing policy. However, the high complexity of user selection and the feasible rates determination for optimal scheme may prevent the real-time scheduling operation. Two low complexity algorithms are provided taking the channel state, queue state and orthogonality into account. In particular, the authors pick the first user with the largest product between channel gain and queuing length, and select the remaining users to construct candidate user set based on the greedy user selection method or channel orthogonal user selection method. Then, the power and rate allocation for the selected users are implemented based on the modified water-filling method. The complexity of the proposed algorithms is analyzed. The average delay and average throughput are studied in homogeneous scenarios and heterogeneous scenarios, respectively. Simulation results show that the proposed algorithms can take full advantage of the multi-user diversity gain and provide average delay (or throughput) and fairness improvement compared with channel-aware-only schemes.     

Hybrid beamforming design based on unsupervised machine learning for millimeter wave systems

This article proposes a hybrid beamforming design with reduced channel state information (CSI) feedback. We use a beam sweeping procedure to provide channel measurements and feed a CSI report scheme. Thereby, the base station (BS) can perform an adequate estimation of the channel characteristics with reduced signaling overhead. Consequently, we need short pilot sequences and very few precoding matrix indicators (PMIs) to properly describe channel behavior. Moreover, we also evaluate different user selection strategies based on unsupervised machine learning framework that exploits the channel information provided by the proposed beam sweeping scheme. Our performance evaluation indicates that the user selection based on fuzzy c‐means is able to efficiently explore the reduced CSI. The proposed hybrid beamforming scheme reduces the multi‐user interference and achieves significant gains in total data rate as channel conditions and interference environment becomes more challenging.     

Joint Optimization of User Set Selection and Transmit Power Allocation for Orthogonal Random Beamforming in Multiuser MIMO Systems

When the number of users is finite, the performance improvement of the orthogonal random beamforming (ORBF) scheme is limited in high signal‐to‐noise ratio regions. In this paper, to improve the performance of the ORBF scheme, the user set and transmit power allocation are jointly determined to maximize sum rate under the total transmit power constraint. First, the transmit power allocation problem is expressed as a function of a given user set. Based on this expression, the optimal user set with the maximum sum rate is determined. The suboptimal procedure is also presented to reduce the computational complexity, which separates the user set selection procedure and transmit power allocation procedure.     

面向服务质量的RIS辅助的多用户NOMA系统功率分配方案

可重构智能超表面(RIS)可被视为通信网络中具有特殊功能的“中继”来配合非正交多址接入(NOMA)系统构建一种协同的信息传输方案。考虑到未来物联网(IoT)场景下不同用户设备对服务质量(QoS)的不同需求,该文提出一种RIS辅助的多用户NOMA通信系统模型,并针对两类用户(信息用户和能量用户)的QoS需求设计了一种基于迭代优化的功率分配方法。该方法通过联合设计RIS相移矩阵、基站端波束赋形以及NOMA系统串行干扰消除顺序来最小化系统的总发射功率,以全面减轻通信系统中基站的能耗负担。仿真结果表明,与无RIS的场景相比,RIS辅助的NOMA系统可有效减小基站的能耗;在有RIS的场景下,所提功率分配方法的能耗明显低于RIS端随机选择相位的方式和基站端直接采用迫零波束赋形的方式。