WO2012162871A1 - 多用户多流波束赋形方法和装置、以及基站 - Google Patents
多用户多流波束赋形方法和装置、以及基站 Download PDFInfo
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- WO2012162871A1 WO2012162871A1 PCT/CN2011/074785 CN2011074785W WO2012162871A1 WO 2012162871 A1 WO2012162871 A1 WO 2012162871A1 CN 2011074785 W CN2011074785 W CN 2011074785W WO 2012162871 A1 WO2012162871 A1 WO 2012162871A1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
- H04B7/0452—Multi-user MIMO systems
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
- H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
- H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
Definitions
- Multi-user multi-stream beamforming method and device and base station
- the present invention belongs to the field of wireless communication technologies, and in particular, to a multi-user multi-stream beamforming method and apparatus, and a base station using the multi-user multi-stream beamforming method and apparatus. Background technique
- MIMO Multiple-Input Multiple-Output
- SA Smart Antennas
- the beamforming technology can perform signal pre-processing on the weight of the antenna array according to the channel characteristics of the user, and has the capability of expanding coverage, increasing system capacity, and reducing interference.
- Multi-antenna multi-stream beamforming technology combines MIMO and smart antenna technology to make full use of airspace resources, and simultaneously transmit multiple shaped data streams to achieve spatial multiplexing without increasing power and sacrificing bandwidth.
- the channel capacity of the communication system enables high speed and reliable information transmission.
- the single-user multi-stream beamforming technology enables a single user to transmit multiple data streams at a certain time, and at the same time obtain shaping gain and spatial multiplexing gain, thereby obtaining a larger than conventional single-flow beamforming technology.
- the traditional dual-stream beamforming technology only supports two data streams, and the algorithm based on channel decomposition SVD (singular value decomposition) is applied from dual-stream to multi-stream, because the effective eigenvalue of the channel will be extremely affected. Earth reduces system performance. Therefore, the algorithm for multi-stream beamforming requires a large difference from the algorithm requirements for dual-stream beamforming.
- SVD singular value decomposition
- multi-user multi-stream beamforming technology utilizes multi-user diversity effect to bring higher total system capacity, and can also realize simultaneous transmission of more user data streams, but multiple users also It brings new problems such as user interference.
- the traditional multi-user MIMO technology based on block diagonalization and signal-to-noise ratio algorithm, all users in the system need to be processed.
- the implementation of the algorithm requires many matrix inversion or iterative solution, and the complexity is extremely high. Suppressing multi-user interference in MIMO channels is the primary problem in multi-user systems, the number of users The improvement of the channel state is more complicated and requires more feedback channel overhead. Therefore, designing a more efficient multi-user multi-stream beamforming algorithm is of great significance.
- the signal-to-noise-and-noise ratio (SLNR) algorithm proposed by Mirette Sade et al. expects each user's received signal power to be as large as possible, and the sum of its noise power and interference power to other users is as small as possible, thus solving the problem between users.
- the signal interference and the mutual interference of the data stream within the user are slowed down. Its advantage is that the objective function subtly avoids the nesting of the weight matrix of the transmitter between users, so that the optimized closed solution can be directly derived. In addition, this solution also breaks through the antenna constraints and has a wider application space.
- the inventors of the present invention found that the signal-to-noise-to-noise ratio (SLNR) algorithm proposed by Mirette Sade et al. is only for a single user, and does not consider the average signal-to-noise ratio of the entire system. Therefore, there are disadvantages in which the performance of the entire system cannot be optimized in some cases. In addition, even if the signal-to-noise ratio of the system is reduced, even the algorithm of Mirette Sade et al. cannot improve the overall throughput of the system. Further, the conventional method does not consider the matching problem between the transmitter precoding vector and the actual reception processing vector. Summary of the invention
- the present invention has been made in view of the above-described circumstances of the conventional art, in order to alleviate or eliminate one or more disadvantages due to conventional limitations, and at least provide a beneficial choice.
- a multi-user multi-stream beamforming method comprising the following steps: a) calculating each user of the plurality of users according to a minimum leak criterion Forming a matrix; b) determining, according to the shaping matrix of each user, a user average signal leakage ratio of the plurality of users; c) determining whether the average user leakage noise ratio of the user is stable, if the user averages a signal leakage If the noise ratio is not stable, then return to step a) to recalculate the shaping matrix of each user using the calculated shaping matrix of each user.
- a multi-user multi-stream beamforming method comprising the following steps for each of a plurality of users: a) determining a shaping matrix of the user; b) Determining whether there is a data stream that needs to be retransmitted; and c) if it is determined that there is a retransmitted data stream that needs to be retransmitted, then selecting an optimized shaping vector in the user's shaping matrix is assigned to the data stream.
- a multi-user multi-stream beamforming device includes: a shaping matrix calculating unit, calculating a forming matrix of each of the plurality of users according to a minimum leak criterion; a user average letter-to-noise ratio calculating unit, determining, according to the shaping matrix of each user a user average signal leakage ratio of the plurality of users; and a user average signal leakage ratio smoothness determining unit, determining whether the average user leakage noise ratio of the user is stable, wherein if the average user leakage noise ratio is not stable,
- the shaping matrix calculation unit recalculates the shaping matrix of each user by using the calculated shaping matrix of each user.
- a multi-user multi-stream beamforming apparatus comprising: a shaping matrix computing unit, determining a shaping matrix of each of a plurality of users; retransmitting the data stream a determining unit, determining, according to each user of the plurality of users, whether there is a data stream that needs to be retransmitted; optimizing the shape vector assigning unit, and determining, by the retransmitted data stream determining unit, that a certain user needs to retransmit the data stream Then, an optimized shaping vector is selected for the data stream in the shaping matrix for the user.
- the present invention also provides a base station using the above method or the apparatus described above.
- the present invention proposes a method of combining HARQ mechanisms with multi-user multi-stream beamforming. This method can realize multi-user multi-stream beamforming transmission under LTE-A, and improve the transmission rate and throughput of the system.
- the present invention proposes a multi-user multi-stream beamforming method combining a HARQ mechanism and a minimum leakage criterion (SLNR) algorithm, which can implement multi-user multi-stream beamforming under LTE-A, and reduce or even eliminate inter-user interference. . Even in the case of multi-stream transmission, the system signal-to-noise ratio is reduced due to the distribution of power to more streams, which can improve the overall throughput of the system.
- SLNR minimum leakage criterion
- a logic component readable program and a logic component readable tangible storage medium storing the logic component readable program are provided, and when the logic component readable program is executed by the logic component, The logic component functions as a shaping device as described herein or causes the logic component to implement the shaping methods described herein.
- FIG. 1 shows a schematic functional block diagram of a base station that can employ the multi-user multi-stream beamforming method of the present invention or a multi-stream beamforming device of the present invention
- FIG. 2 illustrates a multi-user multi-stream beamforming method in accordance with an embodiment of the present invention
- FIG. 3 illustrates a specific implementation of the steps of determining a shape matrix for each user in accordance with an embodiment of the present invention
- FIG. 5 illustrates a multi-user multi-stream beamforming method in accordance with yet another embodiment of the present invention
- FIG. 6 illustrates a multi-user multi-stream beamforming device in accordance with an embodiment of the present invention
- FIG. Functional block diagram of a shaped matrix computing unit 601 of an embodiment
- FIG. 8 illustrates a multi-user multi-stream beamforming device of another embodiment
- FIG. 9 illustrates another embodiment in accordance with the present invention Multi-user multi-stream beamforming device.
- FIG. 1 shows a schematic functional block diagram of a base station in which the multi-user multi-stream beamforming method of the present invention or the multi-stream beamforming device of the present invention can be employed, in which the base station has a small portion that is not closely related to the present invention. description. For the convenience of description, the corresponding user (UE) is also shown in Fig. 1.
- the base station selects the user according to a certain principle, and determines the specific user who performs beamforming, that is, the user (UE) to which the data is to be sent.
- the user selection principle may be based on channel state information uploaded by the user, etc., and is not within the scope of the present invention.
- sent to all through The signal of the credit user is first encoded by channel coder 101 and then the encoded data is modulated in modulator 102. Then, mapping of the codeword to the data layer is performed in the mapping unit 103. The data of each layer is then beamformed (beamformed) in beamforming module 104. Then, it is transmitted through multiple transmit antennas.
- the UE performs linear processing on the received signal by demodulation to recover the corresponding data.
- the beamforming module 104 of the present invention may employ the multi-user multi-stream beamforming method of the present invention or include a multi-user multi-stream beamforming device. Although some of the components in the figures are shown as multiple, they can also be implemented by a single component.
- step S201 a shape matrix of each of the plurality of users is calculated according to a minimum leak criterion. Then, in step S202, the average user leakage noise ratio of the plurality of users is determined according to the shaping matrix of each user. Next, in step S203, it is determined whether the average user leakage noise ratio of the user is stable. If the user average signal leakage ratio is stable (step S203),
- step S204 the shaping matrix of each user calculated in step S201 is determined as the final shaping matrix. Otherwise, if the average user leakage noise ratio is not smooth (step S203, NO), then in step S205, it is judged whether a predetermined number of times has elapsed. If it is determined that the predetermined number of times has elapsed (step S205, YES), the processing proceeds to the step
- step S201 Determine the shaping matrix of each user calculated in step S201 as the final shaping matrix. If it is determined that the predetermined number of times has elapsed (NO in step S205), the processing returns to step S201, in which the calculation of the forming matrix is performed again using the previously calculated shaping matrix.
- step S205 is an optional step. On the one hand, from a system design perspective, complexity and feedback tolerance cycles need to be limited. On the other hand, for some systems, too many loop iterations are not required due to factors such as performance requirements. However, for some systems, this number of iterations may not be required.
- FIG. 3 shows a specific implementation of step S201 according to an embodiment of the present invention.
- step S301 an initial receiving merge matrix of each user among multiple users is determined, or each user calculated according to the last iteration
- the shaping matrix determines the updated receiving merge matrix of each user (which can be collectively referred to as determining the user's receiving merge matrix).
- step S302 the singular solution is calculated according to the initial reception merge matrix or the updated reception merge matrix of each user according to the minimum leak criterion.
- step S303 the singular solution is used to determine each user's Forming matrix.
- FIG. 4 illustrates a multi-user multi-stream beamforming method in accordance with another embodiment of the present invention. Comparing the method shown in Fig. 2 with the method described in Fig. 4, the method further includes step S401 and step S402.
- step S401 it is determined whether each of the plurality of users has a data stream that needs to be retransmitted. If a user has a data stream that needs to be retransmitted (step S401, YES), then in step S402, the user's shaping matrix selects an optimized shaping vector (corresponding to a shape vector of a better quality channel) to be assigned to the user data flow. If a user does not have a data stream that needs to be retransmitted (step S401, NO), then each of the shaping vectors in the user's shaping matrix is sequentially allocated in step S403.
- step S401 it is determined whether each of the plurality of users has a data stream that needs to be retransmitted. If a user has a data stream that needs to be retransmitted (step S
- Each of the shaping matrices may be a precoding matrix.
- FIG. 5 illustrates a multi-user multi-stream beamforming method in accordance with yet another embodiment of the present invention.
- the forming matrix of the user is determined.
- the user's shaping matrix can be determined according to the minimum leakage criterion, and the shaping matrix can also be determined according to other criteria.
- the forming matrix is determined according to the MMSE criterion.
- the method for determining the shape matrix according to the MMSE criterion can be found, for example, in the literature "Introduction to Space-Time Wireless Communication", Tsinghua University Press, pp. 140, 2007.12, first edition, the entire contents of which is hereby incorporated by reference.
- step S502 it is determined whether there is a data stream that needs to be retransmitted. If it is determined that there is a data stream that needs to be retransmitted (YES in step S502), then in step S503, an optimized shaping vector is selected in the user's shaping matrix to be assigned to the data stream. If it is determined that there is no data stream that needs to be retransmitted (NO in step S502), then in step S504, each of the shaping vectors in the user's shaping matrix is sequentially allocated.
- the shaping matrix can also be determined using the methods shown in Figures 2 through 3.
- ⁇ ,..., 1 ⁇ 2 be the information symbols sent to the user respectively, and the user can receive an independent data stream, which is an xl-dimensional vector, that is, if ⁇ ,..., ⁇ are all full-rank vectors
- the second term represents the interference to other users of the user, denotes the power of additive white noise, H k m k XN t Weirui Li a fading channel matrix:
- Multi-Flow Beamforming Scheme When beamforming the first user's data, different beamforming algorithms can be used to obtain the beamforming vector matrix. This chapter only discusses some multi-stream beamforming applications based on non-codebook beamforming algorithms.
- the linear receiving matrix ⁇ can be considered as a matched filter:
- Equation (6) is the sum of the interference and noise received by the user. It can be known from equation (6) that selecting the appropriate shaping matrix to weight the signal can reduce or eliminate the co-channel interference between users.
- SINR Minimum Leakage Criterion
- the SLNR criterion is based on the criterion that the user sends the signal leakage to a minimum, that is, each user is required to select an appropriate beamforming matrix, which minimizes the interference of the user signal to other users, that is, the signal leaked to other users is the smallest. Its mathematical expression is:
- the SLNR in this paper should be understood in a broad sense, including, for example, the noise leakage noise ratio. Therefore, to choose an optimized shape matrix F fc t e [l,..., ), so that ⁇ is the largest,
- the optimized shape matrix should consist of up to 3 ⁇ 4 eigenvalues corresponding to the normalized feature vectors in order from left to right, ie (assuming the feature values are on the diagonal of the matrix from small to large Arranged in order, the top left is the smallest, the bottom right is the largest):
- V, , end V fe (:, end-m fe +l)
- each user's receiving merge matrix is:
- F corresponds to the precoding vector (matrix) determined by the i-th iteration of the kth user.
- N k corresponds to the number of streams transmitted by the kth user of the MU-MIMO system, and p corresponds to the signal to noise ratio.
- the transmit precoding vector and the actual receive processing vector are matched, thereby improving the performance of the system.
- the iteration condition ⁇ SLNR (i -, - SLNR (i - l , ⁇ ⁇ S ) is included in 5, and its intuitive meaning is to rely on an iterative algorithm to converge the nested shape matrix and the optimized solution of the receive merge matrix, that is, to find as large as possible The solution corresponding to the SLNR value.
- the algorithm tends to converge, the SLNR will no longer increase significantly, and then iterate out of the iteration to obtain the final result. In the above process, considering the performance or system design factors, etc. The maximum number of iterations is set.
- Multi-stream beamforming scheme with joint HARQ mechanism Multi-stream beamforming is to reduce the power or signal-to-noise ratio of a certain data stream in the case of high signal-to-noise ratio, and to transmit one or more new ones by reducing the power. data flow.
- the channel capacity is a logarithmic function of the signal-to-noise ratio. As the signal-to-noise ratio increases, the capacity increase trend becomes more and more slow. Therefore, multi-stream beamforming can greatly improve the overall transmission capacity while ensuring that the data stream capacity is not greatly reduced.
- the overall signal-to-noise ratio of the system will decrease, and the quality of different transport streams will vary greatly.
- the fairness between transport streams can be effectively guaranteed and the throughput can be enhanced.
- the HARQ mechanism can be utilized to maximize system throughput.
- the kth user data transmission it can be based first on the minimum leakage criteria (or The multi-stream beamforming algorithm of other criteria) obtains a beamforming vector matrix whose shape vectors are arranged in order of eigenvalue size.
- each stream is first shaped sequentially using the resulting beamforming vector matrix.
- the optimized shaping vector of the beamforming vector matrix is assigned to the stream for beamforming and retransmitting the packet. If there are other streams that feed back the NACK signal to the transmitting end, the remaining beamforming vectors are sequentially allocated and the packet is retransmitted.
- This approach increases the fairness between multiple transport streams of the system at the expense of the efficiency loss of a good quality transport stream. Since the multi-stream beamforming improves the overall transmission capacity at a high signal-to-noise ratio at a reduced signal-to-noise ratio, the scheme can enhance throughput when the signal-to-noise ratio is reduced.
- the apparatus includes a forming matrix calculating unit 601, a user average letter-to-noise ratio calculating unit 602, and a user average letter-to-noise ratio smoothing determining unit 603.
- the shaping matrix calculation unit 601 calculates the shaping matrix of each of the plurality of users according to the minimum leakage criterion.
- the user average signal leakage ratio calculation unit 602 determines the average user leakage noise ratio of the plurality of users according to the shaping matrix of each user.
- the user average noise leakage ratio determining unit 603 determines whether the average user leakage noise ratio of the user is stable. Wherein, if the average user leakage noise ratio is not stable, the shaping matrix calculation unit recalculates the shaping matrix of each user by using the calculated shaping matrix of each user.
- Figure 7 shows a functional block diagram of a shaped matrix calculation unit 601 of an embodiment.
- the shaping matrix calculation unit includes: an initial reception merge matrix calculation unit 701 that determines an initial reception merge matrix of each of a plurality of users; and an updated reception merge matrix calculation unit 702 that is based on the last The calculated shaping matrix of each user determines the updated receiving merge matrix of each user; the singular solution computing unit 703 calculates the initial receiving merge matrix or the updated receiving merge matrix according to each user according to the minimum leak criterion. A singular solution; and a shape determination matrix determining unit 704 that uses the singular solution to determine a shape matrix of each user.
- the multi-user multi-stream beamforming device may further include an iterative determining unit 604.
- the iterative decision unit 604 is an optional unit.
- the iterative determining unit 604 determines whether the user average letter-to-noise-ratio signal determining unit has performed a predetermined number of determinations or whether the shaping matrix calculating unit performs the calculation of the forming matrix of each user of the predetermined number of times. If the predetermined number of times has been determined Or the calculation of the shaping matrix of each user for the predetermined number of times is performed, and the processing is ended.
- Figure 8 illustrates another embodiment of a multi-user multi-stream beamforming device.
- the multi-user multi-stream beamforming device shown in FIG. 8 further includes: a retransmission data stream determining unit 801, for each of the plurality of users The user judges whether there is a data stream that needs to be retransmitted; the optimized shape vector assigning unit 802, in the re-transmission data stream judging unit judges that a certain user has a data stream that needs to be retransmitted, in the shaping matrix for the user The optimized shaping vector is selected to be assigned to the data stream, otherwise the shaping vector in the shaping matrix for the user is assigned in turn.
- Figure 9 illustrates a multi-user multi-stream beamforming device in accordance with another embodiment of the present invention.
- the apparatus includes: a shaping matrix calculation unit 901 that determines an shaping matrix of each of a plurality of users; and a retransmission data stream determining unit 902 for each of the plurality of users Determining whether there is a data stream that needs to be retransmitted; the optimization shaping vector assigning unit 903, when the retransmission data stream judging unit judges that a user has a data stream that needs to be retransmitted, in the shaping matrix for the user The optimized shaped vector is selected to be assigned to the data stream.
- the shaping matrix calculation unit 901 can determine the shaping matrix according to a minimum leakage criterion, a minimum mean square error (MMSE) criterion, or the like.
- MMSE minimum mean square error
- the device may further include: a user average signal leakage ratio calculation unit, determining an average user leakage noise ratio of the plurality of users according to the shaping matrix of each user calculated by the shaping matrix calculation unit a user average signal leakage ratio smoothness determining unit determines whether the average user leakage noise ratio of the user is stable, wherein if the average user leakage noise ratio is not stable, the shaping matrix calculation unit uses the calculated The shaping matrix of each user recalculates the shaping matrix of each user.
- a user average signal leakage ratio calculation unit determining an average user leakage noise ratio of the plurality of users according to the shaping matrix of each user calculated by the shaping matrix calculation unit
- a user average signal leakage ratio smoothness determining unit determines whether the average user leakage noise ratio of the user is stable, wherein if the average user leakage noise ratio is not stable, the shaping matrix calculation unit uses the calculated The shaping matrix of each user recalculates the shaping matrix of each user.
- the above apparatus and method of the present invention may be implemented by hardware, or may be implemented by hardware in combination with software.
- the present invention relates to a logic component readable program that, when executed by a logic component (executed directly after execution or interpretation, compilation, etc.), enables the logic component to implement the apparatus or components described above, or The logic component implements the various methods or steps described above.
- Logical components such as field programmable logic components, microprocessors, and places used in computers Processor and so on.
- the present invention also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash, a magneto-optical disk, a memory card, a memory stick, and the like.
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Abstract
本发明涉及一种多用户多流波束赋形方法和装置、以及基站。该多用户多流波束赋形方法包括以下步骤:a)根据最小泄露准则,计算所述多个用户中的各用户的赋形矩阵;b)根据各用户的所述赋形矩阵确定所述多个用户的用户平均信漏噪比;c)确定所述用户平均信漏噪比是否平稳,如果所述用户平均信漏噪比不平稳,则返回步骤a)利用已计算出的各用户的所述赋形矩阵重新计算各用户的所述赋形矩阵。
Description
多用户多流波束赋形方法和装置、 以及基站
技术领域
本发明属于无线通信技术领域, 尤其涉及多用户多流波束赋形方法 和装置以及使用所述多用户多流波束赋形方法和装置的基站。 背景技术
多输入多输出(Multiple-Input Multiple-Output , MIMO)技术可以 利用收、 发端配置多副天线产生的空间自由度和空时信号处理技术在不 增加带宽和天线发送功率的情况下, 成倍地提高通信系统容量和频谱利 用率。 智能天线 (Smart Antennas, SA)技术能够利用数字信号处理技术产 生空间定向波束, 有效抑制干扰信号, 大幅提高频谱利用率和信道容量。 波束赋形技术能够根据使用者的信道特性对天线阵列加权来进行信号预 处理, 具有扩大覆盖、 提高系统容量、 降低干扰的能力。 多天线多流波 束赋形技术将 MIMO与智能天线技术融合起来,可以充分利用空域资源, 在不增加功率和牺牲带宽的前提下, 同时传输多个赋形数据流来实现空 间复用, 提高无线通信系统的信道容量, 实现高速和可靠的信息传输。
采用单用户多流波束赋形技术, 可以使得单个用户在某一时刻可以 进行多个数据流传输, 同时获得赋形增益和空间复用增益, 从而获得比 传统单流波束赋形技术更大的传输速率。 传统的双流波束赋形技术只支 持两个数据流, 而所采用的基于信道分解的 SVD (奇异值分解)等算法在 从双流应用到多流上时, 由于信道的有效特征值的影响会极大地降低系 统性能。 因此, 多流波束赋形的算法要求与双流波束赋形的算法要求有 很大的不同。
比起单用户多流波束赋形技术, 多用户多流波束赋形技术利用多用 户分集效应带来更高的系统总容量, 也可以实现更多用户数据流的同时 传输, 但多用户同时也带来了用户间干扰等新问题。 在传统的基于块对 角化、 信泄噪比算法的多用户 MIMO技术中, 需要处理系统内的所有用 户, 算法的实现需要很多的矩阵求逆或者迭代求解, 复杂度极高。 抑制 MIMO信道中的多用户干扰在多用户系统中是首要解决的问题, 用户数
的提高会造成信道状态更复杂, 需要更大的反馈信道的开销, 因此设计 更有效的多用户的多流波束赋形算法具有重要的意义。
Mirette Sade 等人提出的基于信漏噪比 (SLNR)算法期望待求的每一 个用户的接收信号功率尽量大, 同时其噪声功率与泄漏对其他用户的干 扰功率之和尽量小, 从而解决用户间的信号干扰和用户内数据流的互扰 放慢。 它的优势在于目标函数巧妙地回避了发射端加权矩阵在用户间的 嵌套, 从而可以直接推导出优化闭合解。 另外, 这种方案还突破了天线 限制条件, 具有更广阔的应用空间。
但是, 在研究本发明的过程中, 本发明的发明人发现, Mirette Sade 等人提出的基于信漏噪比 (SLNR)算法只是针对单个用户的, 并没有考虑 整个系统的平均信漏噪比, 因而存在在某些情况下, 不能实现整个系统 性能最优的缺点。另外,在系统的信噪比降低的情况下,即使 Mirette Sade 等人的算法也不能实现系统整体吞吐量的提高。 进一步, 传统方法没有 考虑发射端预编码向量和实际接收处理向量的匹配问题。 发明内容
因而, 本发明鉴于常规技术的上述情况作出, 用以缓解或消除因常 规的局限所具有的一个或更多个缺点, 至少提供一种有益的选择。
为了实现以上目的, 根据本发明的一个方面, 提供了一种多用户多 流波束赋形方法, 所述方法包括以下步骤: a) 根据最小泄露准则, 计算 所述多个用户中的各用户的赋形矩阵; b )根据各用户的所述赋形矩阵确 定所述多个用户的用户平均信漏噪比; c)确定所述用户平均信漏噪比是 否平稳, 如果所述用户平均信漏噪比不平稳, 则返回步骤 a)利用已计算 出的各用户的所述赋形矩阵重新计算各用户的所述赋形矩阵。
根据本发明的另一方面, 提供了一种多用户多流波束赋形方法, 所 述方法包括针对多个用户中的各用户的以下步骤: a) 确定所述用户的赋 形矩阵; b ) 确定是否存在需要重传的数据流; 以及 c) 如果确定存在需 要重传的重传数据流, 则在该用户的赋形矩阵中选择优化的赋形矢量分 配给该数据流。
根据本发明的另一方面, 提供了一种多用户多流波束赋形装置, 所
述装置包括: 赋形矩阵计算单元, 根据最小泄露准则, 计算所述多个用 户中的各用户的赋形矩阵; 用户平均信漏噪比计算单元, 根据各用户的 所述赋形矩阵确定所述多个用户的用户平均信漏噪比; 以及用户平均信 漏噪比平稳判断单元, 确定所述用户平均信漏噪比是否平稳, 其中, 如 果所述用户平均信漏噪比不平稳, 则所述赋形矩阵计算单元利用所计算 出的各用户的所述赋形矩阵重新计算各用户的所述赋形矩阵。
根据本发明的在另一方面, 提供了一种多用户多流波束赋形装置, 所述装置包括: 赋形矩阵计算单元, 确定多个用户中的各用户的赋形矩 阵; 重传数据流判断单元, 针对所述多个用户中的各用户的判断是否有 需要重传的数据流; 优化赋形矢量分配单元, 在重传数据流判断单元判 断出某一用户有需要重传的数据流时, 则在针对该用户的赋形矩阵中选 择优化的赋形矢量分配给该数据流。
本发明还提供了一种基站, 所述基站使用上述的方法或包括上述的 装置。
本发明提出了将 HARQ机制与多用户多流波束赋形相结合的方法。 采用本方法可以在 LTE-A下实现多用户多流波束赋形传输, 提升系统的 传输速率和吞吐量。
进一步,本发明提出了结合 HARQ机制和最小泄露准则 (SLNR)算法 相结合的多用户多流波束赋形方法, 能够实现 LTE-A下的多用户多流波 束赋形, 减少甚至消除用户间干扰。 即使在多流传输的情况下, 由于分 配功率给更多的流进行传输而造成系统信噪比降低, 也能提升系统整体 的吞吐量。
根据本发明的再一方面, 提供了一种逻辑部件可读程序以及存储该 逻辑部件可读程序的逻辑部件可读有形存储介质, 当所述逻辑部件可读 程序被逻辑部件执行时, 能够使所述逻辑部件用作本文所述的赋形装置 或使所述逻辑部件实现本文所述的赋形方法。
应该注意, 术语"包括 /包含 /具有"在本文使用时指特征、 要件、 步骤 或组件的存在, 但并不排除一个或更多个其它特征、 要件、 步骤或组件 的存在或附加。
以上的一般说明和以下结合附图的详细说明都是示意性的, 不是对
本发明的保护范围的限制。 附图说明
从以下参照附图对本发明的详细描述中, 将更清楚地理解本发明的 以上和其它目的、 特征和优点。 在附图中, 相同或类似的标号指示相同 或类似的元素。
图 1 示出了可以采用本发明多用户多流波束赋形方法或包括本发明 的多流波束赋形装置的基站的示意性功能框图;
图 2示出了依据本发明一种实施方式的多用户多流波束赋形方法; 图 3示出了依据本发明的一种实施方式, 确定各用户的赋形矩阵的 步骤的具体实现;
图 4示出了依据本发明的另一种实施方式的多用户多流波束赋形方 法;
图 5示出了依据本发明再一种实施方式的多用户多流波束赋形方法; 图 6示出了依据本发明一种实施方式的多用户多流波束赋形装置; 图 7示出了一种实施方式的赋形矩阵计算单元 601的功能性方框图; 图 8示出了另一种实施方式的多用户多流波束赋形装置; 以及 图 9示出了依据本发明另一种实施方式的多用户多流波束赋形装置。 具体实施方式
下面参照附图描述本发明的实施方式。 对本发明实施方式的描述都 是示例性的, 不是对本发明保护范围的限制。 在对本发明实施方式的描 述中, 省略了对于理解本发明意义不大的现有技术的描述。
图 1示出了可以采用本发明多用户多流波束赋形方法或包括本发明 的多流波束赋形装置的基站的示意性功能框图, 框图中省略了基站与本 发明关系不大的部分的描述。 为了描述的方便, 图 1 中也示出了相应的 用户 (UE)。
基站按照某种原则对用户进行选取, 确定进行波束赋形的特定用户, 即数据将要发送到的用户 (UE)。 用户选取原则可以是基于用户上传的 信道状态信息等, 不属于本发明讨论范围。 如图 1所示, 发送给所有通
信用户的信号首先经过信道编码器 101编码, 然后在调制器 102中对经 编码的数据进行调制。 然后, 在映射单元 103 中进行码字到数据层的映 射。然后在波束成形模块 104中对各层的数据进行波束成形(波束赋形)。 然后, 通过多个发射天线发送。 用户端 UE通过解调对接收信号进行线 性处理, 恢复出相应数据。 本发明的波束成形模块 104可以采用本发明 的多用户多流波束赋形方法或包括多用户多流波束赋形装置。 尽管图中 某些部件被示出为多个, 但其也可以由单个部件实现。
图 2示出了依据本发明一种实施方式的多用户多流波束赋形方法。 如图 2所示, 首先在步骤 S201 , 根据最小泄露准则, 计算所述多个用户 中的各用户的赋形矩阵。 然后在步骤 S202, 根据各用户的所述赋形矩阵 确定所述多个用户的用户平均信漏噪比。 接着, 在步骤 S203 , 确定所述 用户平均信漏噪比是否平稳。 如果所述用户平均信漏噪比平稳 (步骤
5203 , 是) , 则在步骤 S204, 将步骤 S201 中计算出的各用户的赋形矩 阵确定为最终选用的的赋形矩阵。 否则, 如果所述用户平均信漏噪比不 平稳(步骤 S203 , 否), 则在步骤 S205 , 判断是否已经经过了预定次数。 如果确定出已经经过了预定次数 (步骤 S205 , 是) , 则处理进行到步骤
5204,将步骤 S201中计算出的各用户的赋形矩阵确定为最终选用的赋形 矩阵。 如果确定出已经经过了预定次数 (步骤 S205 , 否) , 则处理返回 步骤 S201 , 在步骤 S201 中利用先前算出的赋形矩阵, 再次进行赋形矩 阵的计算。
应该注意,步骤 S205是可选的步骤。一方面,从系统设计的角度看, 需要限制复杂度和反馈容忍周期。 另一方面, 对于某些系统来说, 由于 性能要求等因素, 也不需要进行过多的循环迭代。 但对于某些系统而言, 则可能不需要这种迭代次数的限定。
图 3示出了依据本发明的一种实施方式, 步骤 S201的具体实现, 首 先在步骤 S301 , 确定多个用户中的各用户的初始接收合并矩阵, 或根据 上次迭代计算出的各用户的赋形矩阵确定各用户的更新后接收合并矩阵 (可以统称为确定用户的接收合并矩阵) 。 然后, 在步骤 S302, 依据最 小泄露准则, 根据各用户的所述初始接收合并矩阵或所述更新后接收合 并矩阵计算奇异解。 接着, 在步骤 S303 , 利用所述奇异解确定各用户的
赋形矩阵。
图 4 示出了依据本发明的另一种实施方式的多用户多流波束赋形方 法。 对比图 2所示的方法, 图 4所述的方法, 所述方法还包括步骤 S401 和步骤 S402。 在步骤 S401 中, 针对所述多个用户中的各用户判断是否 有需要重传的数据流。如果某用户有需要重传的数据流(步骤 S401 ,是), 则在步骤 S402该用户的赋形矩阵中选择优化的赋形矢量(对应于质量较 好的信道的赋形矢量) 分配给该数据流。 如果某用户没有需要重传的数 据流 (步骤 S401 , 否), 则在步骤 S403顺次地分配该用户的赋形矩阵中 的各赋形矢量。
各赋形矩阵可以是预编码矩阵。
图 5示出了依据本发明再一种实施方式的多用户多流波束赋形方法。 如图 5所示, 针对多个用户中各用户, 首先在步骤 S501 , 确定所述用 户的赋形矩阵。在该步骤中可以依据最小泄露准则确定用户的赋形矩阵, 也可以依据其他的准则确定赋形矩阵。例如依据 MMSE准则确定赋形矩 阵。 依据 MMSE准则确定赋形矩阵的方法, 例如可以参见文献《空时无 线通信导论》 清华大学出版社 140页 2007.12第一版, 通过引用, 将其全部内容并入本文中。 然后, 在步骤 S502, 确定是否存在需要重传 的数据流。如果确定存在需要重传的数据流(步骤 S502, 是), 则在步骤 S503 , 在该用户的赋形矩阵中选择优化的赋形矢量分配给该数据流。 如 果确定不存在需要重传的数据流 (步骤 S502, 否), 则在步骤 S504, 顺 次分配该用户的赋形矩阵中的各赋形矢量。
在一种优选的实施方式中, 也可以采用图 2到图 3所示的方法确定 赋形矩阵。
下面对多用户多流波束赋形方法的数学推理和实现方法进行简要的 描述, 以方便对本发明的进一步理解或满足专利法对于公开的要求。 但 是应该注意, 下面的方法主要针对最小泄露准则进行, 但在很多地方也 可以采用其他的准则。 本发明的保护范围应以权利要求中的描述为准, 不应以说明书的描述过分限制本发明的保护范围。 对于本发明方法的描 述也可以用来理解本发明的装置。
MU-MIMO系统应用场景
假设该 MU-MIMO系统应用场景中, 设发射天线数为 Nf, 接收天线 数为 Nr, 系统中有 个接收用户 Μ ,Μ ..,Μ^, 其中用户 M 的接收天 线数为 , 即 ^=| ¾。
k=l
设^ ,...,½分别为给 个用户发送的信息符号, 用户 可接收到 个独立数据流, 则 是一个 xl维的向量, 也就是说如果 ^ ,…,^均 为满秩向量的话系统总共实现的传输流流数 N为 ^=1; , 否则为 k=l
Sl,s2,...,½的秩总和。
当对第 个用户的数据进行波束赋形的时候, 对于发送符号 ¾ =[¾,¾,...,¾mJT,需要计算一个 Ni xw¾的赋形矩阵 对发送信号加权, 且其满足 ll ll2=l。 个用户赋形后一同由发射端发送, 其表达式为: κ
χ =∑¾ (!) 用户 接收到信号可表示为:
K j=l,j≠k
多流波束赋形方案 当对第 个用户的数据进行波束赋形的时候, 为得到波束赋形矢量 矩阵 , 可采取不同的波束赋形算法。 本章仅讨论一些基于非码本的波 束赋形算法的多流波束赋形应用。
用户 通过下行专用导频信号估计出下行等效信道 =^ , 同时
出噪声功率 ^后, 则线性接收矩阵\^可认为是一个匹配滤波器:
、H
(5)
II HA II
其中, ll - ll ¾^ Frobenius (F范数)。
将式 (5)代入式 (4), 可得:
式 (6)中第二项为用户 接收到的干扰和噪声总和, 由式 (6)可知, 选 择适当的赋形矩阵 对信号进行加权,可以降低或消除用户间 的同道干扰。
最小泄露准则 (SLNR)算法的多流应用 发送端在同时与多个用户进行通信时, 每个用户将会受到其它所有 用户的干扰, 即共信道干扰 CCI, 从而定义了干扰及信干噪比 SINR。 用 户间的干扰是每个用户受到其它同时通信的所有用户的信号干扰, 是由 接收到其它用户的信号引起的。 这里引用一个概念: 泄漏。 泄漏是指每 个用户对其它所有用户的干扰, 从某种意义上来讲, 每个用户都有部分 信号功率泄漏到了其它用户。 这是因为基站在给每个用户发送该用户的 信号同时, 这个信号也发送到了其它的用户所引起的。
由式 (2), 第 个用户接收到的信号为:
K
SLNR准则是基于用户发送信号泄露最小的准则,即要求每个用户选 择合适的波束赋形矩阵, 这个矩阵可使该用户信号对其他用户的干扰总 和最小, 即泄露到其他用户的信号最小。 其数学表达式为:
" + ∑ II H II2 由式 (8)可知, 若噪声功率一定, 当 ^^ 较小时, 用户 发送信号对 其他用户造成的干扰总和较大, 即信号泄露较大; 反之, 则造成的干扰
总和较小, 即信号泄露较小。
本文中的 SLNR应做广义的理解, 例如还包括信漏干扰噪声比等。 所以, 要选择一个优化的赋形矩阵 Ffc te[l,..., ), 使得 Λ 最大,
1
其中, tr[.]表示矩阵的迹。 因为有 E[ S ] , 所以在统计平均意 义下, ^^ 表达式可简化为
IIW,H,F, II^
SLNR,,
κ (11)
IIW.z, 11^ +11 ∑ WyH .F, ll:
j=l,j≠k
II Wkzk ll^ = tr[W,z,z^W,H]□ 2/mtr[W^ (12) 用户 通过下行专用导频信号估计出下行等效信道 =Hfe , 同时 估算出噪声功率^后, 则线性接收矩阵Wfc可认为是一个匹配滤波器:
(HA)
(13) II HA II
于是
TnT
为了获得优化的系统性能, 则需要寻求 (7)式的最大值所对应的波束 赋形矩阵和接收合并矩阵。 求解这个问题涉及到利用广义瑞利商 (generalized Rayleigh quotient)的推广理论。具体而言, 可以进行如下广义 特征值分解:
(16) 其中,函数 eig(A,Z)表示对 (Α,Ζ)进行广义特征值分解操作,矩阵 ¼的 列矢量表示对应特征矢量, 对角矩阵! 的对角线上的元素表示对应特征 值。 mk表示用户 k的接收天线数目, I表示单位阵, Imk代表第 k用户的 噪声矩阵。 显然, 优化的赋形矩阵 应由最多《¾个特征值所对应的归一 化的特征矢量按从左至右的顺序组成, 即 (假设特征值在矩阵 对角线 上是按照从小到大的顺序排列, 左上方最小, 右下方最大):
V, , end) Vfe(:,end-mfe +l)
II Nk , end) \\F \\Nk , end-m^ +1)11
其中, "end"表示最末一个值, Vk (:, 数值参数)指矩阵 Vk的由所述 数值参数指示的列。 然后可以利用 (5)式求得接收合并矩阵。
因而可以如下地进行迭代算法:
计算 [Vfe,Dfe] = eig(Pfe,Qfe), P,=(W«H,)HW«H,
赋形矩阵 { (''),...,^}。
④ 计算用户平均信漏噪比指针:
⑤ 如果 ≥1且 IWJVRW -WJV -" ^^ (这里 是某个较小的数), 或者 i = Tmax , 其中 rmax表示迭代算法设定的最大迭代数, 则跳转到⑥, 否 则 = + 1, 并根据接收机类型更新接收合并矩阵, 然后跳转到②。
w ('■) (Η ('·— ")H 例如对于匹配滤波接收机,可以利用公式 II Η^Γ1} ^更新接收合 并 矩 阵 。 而 对 于 匪 SE 接 收 /
(HkF lr(HkF l) + ^INi
更新接收合并矩阵。
其中 F 对应于第 k个用户第 i- 1次迭代确定的预编码向量 (矩阵)。 Nk对 应 MU-MIMO系统第 k个用户传输的流数, p对应信噪比。
通过根据接收机类型更新接收合并矩阵, 使得发射端预编码向量和实 际的接收处理向量得到了匹配, 从而可以提高系统的性能。
⑥ = F ), W, = w , 其中, fc=l,2〜,K。
在⑤中包含迭代条件 \ SLNR(i、- SLNR(i-l、 \≤S , 其直观含义是希望依 靠迭代算法来收敛嵌套的赋形矩阵和接收合并矩阵的优化解, 即寻找尽 量大的 SLNR值所对应的解。当算法趋于收敛时, SLNR将不再明显增加, 这时就跳出迭代, 从而获得最终结果。 在上面的处理流程中, 考虑到性 能或系统设计的因素等, 设定了最大迭代数。
联合 HARQ机制的多流波束赋形方案 多流波束赋形是在高信噪比的情况下将某个数据流的功率降低或者 说信噪比降低, 利用降低功率来发送一个或者多个新的数据流。 根据香 农信道容量相关理论可知, 信道容量是关于信噪比的对数函数, 随着信 噪比的提升, 容量增加的趋势越来越缓。 所以多流波束赋形可以在保证 数据流容量不大幅降低的情况下, 极大提升传输整体容量。
然而在流数增加的情况下, 系统整体信噪比会下降, 不同传输流的 质量也相差很大。结合 HARQ机制可以有效的保证传输流之间的公平性, 增强吞吐量。
表示信号第 i次的传输,假设信道矩阵 H(0对于每次传输都一样。 在结合 HARQ后, 如果传输包被检测为无误, 就会传送一个 ACK给发 射端告知不再传输该传输包, 否则将会传输一个 NACK来要求重新传输 这个传输包。 在波束赋形中, 不同流的质量存在明显差异, 依据本发明 的实施方式, 可以利用 HARQ机制来最大化系统吞吐量。
例如在第 k个用户数据传输中, 可以首先由基于最小泄露准则 (或
其他准则) 的多流波束赋形算法得到波束赋形矢量矩阵, 其赋形矢量按 特征值大小顺序排列。 在每个用户数据流的第一个包传输时, 先利用所 得波束赋形矢量矩阵按顺序对每个流赋形。 针对某个流的上次传输向发 射端反馈 NACK信号时, 将波束赋形矢量矩阵的优化赋形矢量分配给该 流进行波束赋形并重传该包。 如果同时有其他流向发射端反馈 NACK信 号则依序分配剩余的波束赋形矢量并重传该包。 这个方案以质量好的传 输流的效率损失为代价提升了系统的多个传输流之间的公平性。 由于多 流波束赋形以在高信噪比下以降低信噪比为代价提升整体传输容量, 所 以该方案在信噪比降低时可以增强吞吐量。
图 6示出了依据本发明一种实施方式的多用户多流波束赋形装置。 如图 6所示, 该装置包括赋形矩阵计算单元 601、用户平均信漏噪比计算 单元 602、 以及用户平均信漏噪比平稳判断单元 603。
赋形矩阵计算单元 601根据最小泄露准则, 计算所述多个用户中的 各用户的赋形矩阵。 用户平均信漏噪比计算单元 602根据各用户的所述 赋形矩阵确定所述多个用户的用户平均信漏噪比。 用户平均信漏噪比平 稳判断单元 603确定所述用户平均信漏噪比是否平稳。 其中, 如果所述 用户平均信漏噪比不平稳, 则所述赋形矩阵计算单元利用所计算出的各 用户的所述赋形矩阵重新计算各用户的所述赋形矩阵。
图 7示出了一种实施方式的赋形矩阵计算单元 601的功能性方框图。 如图 7所示,该赋形矩阵计算单元包括:初始接收合并矩阵计算单元 701, 其确定多个用户中的各用户的初始接收合并矩阵; 更新后接收合并矩阵 计算单元 702,其根据上次计算出的各用户的赋形矩阵确定各用户的更新 后接收合并矩阵; 奇异解计算单元 703, 其依据最小泄露准则, 根据各用 户的所述初始接收合并矩阵或所述更新后接收合并矩阵计算奇异解; 以 及赋形矩阵确定单元 704, 其利用所述奇异解确定各用户的赋形矩阵。
此外, 回到图 6, 依据本发明的一种实施方式, 所述多用户多流波束 赋形装置还可以包括迭代判断单元 604。迭代判断单元 604是一个可选的 单元。 该迭代判断单元 604判断所述用户平均信漏噪比平稳判断单元是 否已经进行了预定次数的确定或所述赋形矩阵计算单元是否进行了所述 预定次数的各用户的赋形矩阵的计算, 如果已经进行了预定次数的确定
或进行了所述预定次数的各用户的赋形矩阵的计算, 则结束处理。
图 8示出了另一种实施方式的多用户多流波束赋形装置。与图 6所示 的多用户多流波束赋形装置相比, 图 8所示的多用户多流波束赋形装置 还包括:重传数据流判断单元 801,针对所述多个用户中的各用户的判断 是否有需要重传的数据流;优化赋形矢量分配单元 802,在重传数据流判 断单元判断出某一用户有需要重传的数据流时, 在针对该用户的赋形矩 阵中选择优化的赋形矢量分配给该数据流, 否则依次分配针对该用户的 赋形矩阵中的赋形矢量。
图 9示出了依据本发明另一种实施方式的多用户多流波束赋形装置。 如图 9所示, 所述装置包括: 赋形矩阵计算单元 901, 其确定多个用户中 的各用户的赋形矩阵; 重传数据流判断单元 902,针对所述多个用户中的 各用户的判断是否有需要重传的数据流; 优化赋形矢量分配单元 903, 在 重传数据流判断单元判断出某一用户有需要重传的数据流时, 则在针对 该用户的赋形矩阵中选择优化的赋形矢量分配给该数据流。
赋形矩阵计算单元 901 可以根据最小泄露准则、 最小均方误差 (MMSE) 准则等确定赋形矩阵。
另外, 所述装置还可以包括: 用户平均信漏噪比计算单元, 根据所述 赋形矩阵计算单元计算出的各用户的所述赋形矩阵确定所述多个用户的 用户平均信漏噪比; 用户平均信漏噪比平稳判断单元, 确定所述用户平 均信漏噪比是否平稳, 其中, 如果所述用户平均信漏噪比不平稳, 则所 述赋形矩阵计算单元利用所计算出的各用户的所述赋形矩阵重新计算各 用户的所述赋形矩阵。
对装置的描述和对方法的描述可以相互参照、 相互理解。 在一种实 施方式中出现的特征可以以相同或类似的方式应用到另一实施方式, 取 代该另一实施方式中的特征或与该另一实施方式中的特征一起使用。
本发明以上的装置和方法可以由硬件实现, 也可以由硬件结合软件 实现。 本发明涉及这样的逻辑部件可读程序, 当该程序被逻辑部件所执 行 (直接执行或解释、 编译等后执行) 时, 能够使该逻辑部件实现上文 所述的装置或构成部件, 或使该逻辑部件实现上文所述的各种方法或步 骤。 逻辑部件例如现场可编程逻辑部件、 微处理器、 计算机中使用的处
理器等。 本发明还涉及用于存储以上程序的存储介质, 如硬盘、 磁盘、 光盘、 DVD、 flash, 磁光盘、 存储卡、 存储棒等等。
以上结合具体的实施方式对本发明进行了描述, 但本领域技术人员 应该清楚, 这些描述都是示例性的, 并不是对本发明保护范围的限制。 本领域技术人员可以根据本发明的精神和原理对本发明做出各种变型和 修改, 这些变型和修改也在本发明的范围内。
Claims
1、 一种多用户多流波束赋形方法, 所述方法包括以下步骤:
a) 根据最小泄露准则, 计算所述多个用户中的各用户的赋形矩阵; b )根据各用户的所述赋形矩阵确定所述多个用户的用户平均信漏噪 c)确定所述用户平均信漏噪比是否平稳, 如果所述用户平均信漏噪 比不平稳, 则返回步骤 a)利用已计算出的各用户的所述赋形矩阵重新计 算各用户的所述赋形矩阵。
2、 根据权利要求 1所述的方法, 所述步骤 a) 包括:
( 1 )确定所述多个用户中的各用户的初始接收合并矩阵, 或根据上 次计算出的各用户的赋形矩阵确定各用户的更新后接收合并矩阵;
(2)依据最小泄露准则, 根据各用户的所述初始接收合并矩阵或所 述更新后接收合并矩阵计算奇异解;
(3 ) 利用所述奇异解确定各用户的赋形矩阵。
3、 根据权利要求 2所述的方法, 其特征在于,
其中, K表示所述多个用户的总数, mk表示用户 k的接收天线数 目, I表示单位阵, Imk代表第 k用户的噪声矩阵, Imk ( [l:mk],: ) 表 示矩阵 Imk的第 1到第 mk行, i表示当前迭代次数;
在所述步骤 (2) 中, 如下地计算奇异解:
Ντπτ
— L ^ ' i K " K J 7
函数 eig (参数 1, 参数 2)表示对 (参数 1, 参数 2)进行广义特征值分 解操作, Wk代表第 k个用户的接收端合并矩阵, 对角矩阵! ^的对角线上 的元素表示对应特征值, Hk表示第 k个用户的多天线信道矩阵, 上标 H 代表矩阵共轭转置, 上标 T表示矩阵转置, σ 表示用户 k的噪声功率, Vk代表根据最小泄露原则得到的预编码矩阵, 矩阵 ¼的列矢量表示对应 特征矢量; 以及
在所述步骤 (3 ) 中, 利用以下公式计算用户 k的赋形矩阵
Vk (:, 数值参数)指矩阵 Vk的由所述数值参数指示的列,下标 F表示 F 范数。
4、 根据权利要求 1所述的方法, 其特征在于, 在所述步骤 c中, 还 判断所述步骤 c) 是否已经进行了预定次数的确定或所述步骤 a) 是否进 行了所述预定次数的各用户的赋形矩阵的计算, 如果已经进行了预定次 数的确定或进行了所述预定次数的各用户的赋形矩阵的计算, 则结束处
5、 根据权利要求 1所述的方法, 其特征在于,
如果! ^^ - ^^- ^, 是预定的数, 则判断用户平均信漏噪比 平稳, 其中 i表示迭代次数, SLNR(1)表示第 i次迭代时得到的用户平均信 漏噪比。
6、 根据权利要求 1所述的方法, 其中在所述步骤 a) 中, 通过根据接 收机类型来更新接收合并矩阵而利用已计算出的各用户的所述赋形矩阵 重新计算各用户的所述赋形矩阵。
7、 根据权利要求 1所述的方法, 其特征在于, 所述方法还包括针对 所述多个用户中的各用户的如下的步骤:
判断是否有需要重传的数据流;
如果有需要重传的数据流, 则在该用户的赋形矩阵中选择对应于信道 质量较好的信道的赋形矢量分配给该数据流。
8、 一种多用户多流波束赋形方法, 所述方法包括针对多个用户中的 各用户的以下步骤:
a) 确定所述用户的赋形矩阵;
b ) 确定是否存在需要重传的数据流; 以及
c ) 如果确定存在需要重传的重传数据流, 则在该用户的赋形矩阵中 选择对应于信道质量较好的信道的赋形矢量分配给该数据流。
9、 根据权利要求 8所述的方法, 其特征在于, 在所述步骤 a) 中, 根 据最小泄露准则确定所述用户的赋形矩阵。
10、 根据权利要求 8所述的方法, 其特征在于, 所述方法包括以下步 骤:
根据各用户的所述赋形矩阵确定所述多个用户的用户平均信漏噪 比;
确定所述用户平均信漏噪比是否平稳, 如果所述用户平均信漏噪比不 平稳, 则返回步骤 a)利用已计算出的各用户的所述赋形矩阵重新计算各 用户的所述赋形矩阵。
11、 一种多用户多流波束赋形装置, 所述装置包括:
赋形矩阵计算单元, 根据最小泄露准则, 计算所述多个用户中的各 用户的赋形矩阵;
用户平均信漏噪比计算单元, 根据各用户的所述赋形矩阵确定所述 多个用户的用户平均信漏噪比; 以及
用户平均信漏噪比平稳判断单元, 确定所述用户平均信漏噪比是否 平稳,
其中, 如果所述用户平均信漏噪比不平稳, 则所述赋形矩阵计算单 元利用所计算出的各用户的所述赋形矩阵重新计算各用户的所述赋形矩 阵。
12、 根据权利要求 11所述的装置, 其中, 所述赋形矩阵计算单元包 括:
初始接收合并矩阵计算单元, 确定多个用户中的各用户的初始接收 合并矩阵;
更新后接收合并矩阵计算单元, 根据上次计算出的各用户的赋形矩 阵确定各用户的更新后接收合并矩阵;
奇异解计算单元, 依据最小泄露准则, 根据各用户的所述初始接收 合并矩阵或所述更新后接收合并矩阵计算奇异解;
赋形矩阵确定单元, 利用所述奇异解确定各用户的赋形矩阵。
13、 根据权利要求 11所述的装置, 其特征在于, 所述装置还包括迭 代判断单元, 所述迭代判断单元判断所述用户平均信漏噪比平稳判断单 元是否已经进行了预定次数的确定或所述赋形矩阵计算单元是否进行了 所述预定次数的各用户的赋形矩阵的计算, 如果已经进行了预定次数的 确定或进行了所述预定次数的各用户的赋形矩阵的计算, 则结束处理。
14、 根据权利要求 11述的装置, 其特征在于, 所述装置还包括: 重传数据流判断单元,针对所述多个用户中的各用户的判断是否有需 要重传的数据流;
优化赋形矢量分配单元, 在重传数据流判断单元判断出某一用户有需 要重传的数据流时, 则在针对该用户的赋形矩阵中选择对应于信道质量 较好的信道的赋形矢量分配给该数据流。
15、 根据权利要求 11 述的装置, 其特征在于, 所述更新后接收合并 矩阵计算单元通过根据接收机类型来更新接收合并矩阵而利用已计算出 的各用户的所述赋形矩阵重新计算各用户的所述赋形矩阵。
16、 一种多用户多流波束赋形装置, 所述装置包括:
赋形矩阵计算单元, 确定多个用户中的各用户的赋形矩阵; 重传数据流判断单元,针对所述多个用户中的各用户的判断是否有需 要重传的数据流;
优化赋形矢量分配单元, 在重传数据流判断单元判断出某一用户有需 要重传的数据流时, 则在针对该用户的赋形矩阵中选择对应于信道质量 较好的信道的赋形矢量分配给该数据流。
17、 根据权利要求 16所述的装置, 其特征在于, 所述赋形矩阵计算 单元根据最小泄露准则确定所述用户的赋形矩阵。
18、 根据权利要求 17所述的装置, 其特征在于, 所述装置还包括: 用户平均信漏噪比计算单元, 根据所述赋形矩阵计算单元计算出的 各用户的所述赋形矩阵确定所述多个用户的用户平均信漏噪比;
用户平均信漏噪比平稳判断单元, 确定所述用户平均信漏噪比是否 平稳,
其中, 如果所述用户平均信漏噪比不平稳, 则所述赋形矩阵计算单 元利用所计算出的各用户的所述赋形矩阵重新计算各用户的所述赋形矩 阵。
19、 一种基站, 所述基站包括权利要求 11-18 任一项所述的多用户 多流波束赋形装置或使用权利要求 1-10任一项所述的多用户多流波束赋 形方法。
20、 一种逻辑部件可读程序, 当所述逻辑部件可读程序被逻辑部件 执行时,能够使所述逻辑部件作为权利要求 11-18中任一项所述的多用户 多流波束赋形装置工作或使所述逻辑部件实现权利要求 1-10中任一项所 述的方法。
21、 一种逻辑部件可读有形存储介质, 所述有形存储介质存储有权 利要求 20所述的逻辑部件可读程序。
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| US9030161B2 (en) * | 2011-06-27 | 2015-05-12 | Board Of Regents, The University Of Texas System | Wireless power transmission |
| KR102102414B1 (ko) * | 2015-04-20 | 2020-04-20 | 한국전자통신연구원 | Wlan 시스템에서의 하향 링크에 대한 간섭 정렬 방법 및 이를 수행하기 위한 액세스 포인트 및 사용자 단말 |
| US12408042B2 (en) * | 2019-02-27 | 2025-09-02 | Northeastern University | Method for spectrum sharing by primary and secondary networks based on cognitive beamforming |
| CA3252088A1 (en) * | 2022-02-18 | 2023-08-24 | Viasat, Inc. | METHOD AND APPARATUS FOR FORMING EMISSION BEAMS |
| KR20240092878A (ko) * | 2022-12-15 | 2024-06-24 | 한국과학기술원 | 다수의 사용자를 위한 멀티 에이전트 심층 강화학습을 적용한 간섭 제어 및 하이브리드 빔포밍 방법 및 시스템 |
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| CN1909438A (zh) * | 2005-08-05 | 2007-02-07 | 松下电器产业株式会社 | 在特征波束成形发送mimo系统中使用的重传方法和设备 |
| US20080075196A1 (en) * | 2006-06-14 | 2008-03-27 | Samsung Electronic Co., Ltd. | Apparatus and method for transmitting/receiving data in a closed-loop multi-antenna system |
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| KR101392342B1 (ko) * | 2007-08-17 | 2014-05-08 | 삼성전자주식회사 | 다중 입/출력 통신 방법 및 이를 이용한 다중 입출/력 통신시스템 |
| EP2198664B1 (en) * | 2007-08-31 | 2012-10-17 | Koninklijke Philips Electronics N.V. | Enhanced multi-user transmission |
| US8098755B2 (en) * | 2007-09-07 | 2012-01-17 | Broadcom Corporation | Method and system for beamforming in a multiple user multiple input multiple output (MIMO) communication system using a codebook |
| US8683284B2 (en) * | 2007-09-25 | 2014-03-25 | Samsung Electronics Co., Ltd. | Receiving apparatus and method |
| KR101576915B1 (ko) * | 2009-12-28 | 2015-12-14 | 삼성전자주식회사 | 낮은 복잡도의 공동의 유출 억압 기법을 사용하는 통신 시스템 |
| US20110176633A1 (en) * | 2010-01-20 | 2011-07-21 | Eric Ojard | Method and system for orthogonalized beamforming in multiple user multiple input multiple output (mu-mimo) communication systems |
| KR101883944B1 (ko) * | 2010-02-22 | 2018-07-31 | 한국전자통신연구원 | 무선 통신 시스템에서의 사운딩 방법 및 이를 수행하는 장치 |
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| CN1909438A (zh) * | 2005-08-05 | 2007-02-07 | 松下电器产业株式会社 | 在特征波束成形发送mimo系统中使用的重传方法和设备 |
| US20080075196A1 (en) * | 2006-06-14 | 2008-03-27 | Samsung Electronic Co., Ltd. | Apparatus and method for transmitting/receiving data in a closed-loop multi-antenna system |
| US20090322614A1 (en) * | 2008-06-30 | 2009-12-31 | Cisco Technology, Inc. | Orthogonal/partial orthogonal beamforming weight generation for mimo wireless communication |
| CN101754347A (zh) * | 2008-12-19 | 2010-06-23 | 大唐移动通信设备有限公司 | 多流波束赋形传输时cqi估计方法、系统及设备 |
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| US9287955B2 (en) | 2016-03-15 |
| CN103329457A (zh) | 2013-09-25 |
| US20140086086A1 (en) | 2014-03-27 |
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