WO2020019474A1 - 大规模m2m网络中基于最优功率退避的非正交随机接入方法 - Google Patents
大规模m2m网络中基于最优功率退避的非正交随机接入方法 Download PDFInfo
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- H04W28/02—Traffic management, e.g. flow control or congestion control
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- Y02D30/00—Reducing energy consumption in communication networks
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- the invention belongs to the technical field of random access in large-scale M2M networks, and relates to a non-orthogonal random access method based on optimal power backoff in large-scale M2M networks.
- M2M has become the main communication scenario for 5G.
- 3GPP defines M2M as a machine type communication (MTC) communication method for data transmission through a cellular network.
- MTC machine type communication
- PRACH physical random access signals
- RA Sending random access
- the purpose of the present invention is to overcome the shortcomings of the prior art described above, and provide a non-orthogonal random access method based on optimal power backoff in a large-scale M2M network.
- the method can effectively improve system throughput and reduce equipment access. Into the delay.
- the non-orthogonal random access method based on optimal power backoff in the large-scale M2M network includes the following steps:
- the coverage of an eNB includes N MTCDs.
- the arrival model of each MTCD follows a beta distribution, and the channels of each MTCD follow Rayleigh fading. If all channel gains are independent, the specific process of the network random access 4 message is:
- the base station obtains the optimal MTCD number I * in the NOMA device group, and then increases the ACB factor by I * times and sends it to all MTCDs.
- the MTCD that passes the ACB test sends the first message Msg1 to the base station through the physical random access channel.
- the first message Msg1 is labeled PA, and the labeled PA includes the PA and the labeled ZC sequence, so that the base station can identify the PA selected by the MTCD in the first step of the random access RA, and judge the number of MTCDs that choose the same PA;
- the base station sends a second message Msg2 to the MTCD according to all selected PAs, and records the second message Msg2 as a random access response RAR.
- the random access response RAR includes the PA ID, uplink resource allocation, and instructions for selecting the PA.
- MTCD mark index and timing advance information and power allocation information corresponding to MTCD, MTCD monitors RAR represented by RA-RNTI on the physical downlink control channel PUSCH;
- the MTCD capable of listening to the RAR transmits the third message Msg3 on the corresponding physical uplink shared channel PUSCH according to the selected tag PA, and the third message Msg3 is PA ID + tag index + information to be sent according to the allocated power.
- Each MTCD of the same PA is NOMA on the same physical uplink shared channel PUSCH through multiplexing in the power domain.
- the base station regards all MTCDs that choose the same PA as a NOMA device group, and then uses SIC to decode the data packet of the NOMA device group on each physical uplink shared channel PUSCH, and sends a fourth message Msg4 to the successfully decoded MTCD.
- the four messages Msg4 are the contention resolution message CRI, the MTCD that received the CRI sends an acknowledgement ACK to the base station, the MTCD that did not receive the CRI performs uniform random backoff, and reconnects at the corresponding next random access opportunity RAO, When any MTCD fails to RA within the maximum number of retransmissions, the MTCD is deemed to have failed to access and the MTCD is discarded.
- the MTCD constitutes a NOMA equipment group.
- the base station estimates the Rayleigh fading channel coefficient corresponding to the MTCD according to the received power of each labeled PA.
- the modulo square of the Rayleigh fading channel coefficient of one MTCD of the PA sorts the MTCDs from large to small, and sends RARs to the NOMA device group according to the sorting order, where the PA ID and Tag index indicate that the MTCD corresponding to the PA is selected.
- the timing advance information TA is used for the uplink synchronization of each MTCD.
- the uplink grant UL grant indicates that the base station assigns the PUSCH for the third message Msg3 to the NOMA equipment group, and the power backoff is used for the adjustment of the transmission power of each MTCD. , So that the one MTCD can share the same PUSCH resource through multiplexing in the power domain.
- the number of MTCDs in a NOMA device group, and the average probability of successful SIC decoding of an MTCD during J PA transmissions as constraints, in order to optimize the power backoff factor and select the MTCD device of a PA
- the number is a variable, and the optimization problem is set with the goal of the maximum throughput that the PA can provide:
- p s is the minimum average probability that a MTCD successfully accesses during J PA transmissions
- Q i (I, q) represents the probability that the i-th MTCD is successfully decoded when the first i-1 MTCD is successfully decoded and removed from the received signal.
- a particle swarm algorithm is used to solve the optimal backoff factor corresponding to each I value, and then the I is traversed to solve for the maximum throughput I and the corresponding backoff factor.
- the non-orthogonal random access method based on optimal power backoff in the large-scale M2M network constructs a system model by using the optimal power backoff factor and selecting the optimal MTCD number of the same PA during the specific operation, thereby maximizing
- the throughput that a PA can provide is adjusted by the ACB factor according to the number of MTCDs that the PA can provide at the maximum throughput, so that more MTCDs pass the ACB test, so that multiple MTCD devices can be reused in the same domain through the power domain.
- the third message Msg3 is transmitted on the physical uplink shared channel PUSCH to achieve the purpose of improving the system throughput and reducing the access delay.
- FIG. 1 is a flowchart of the present invention
- Figure 3 is a graph showing the change of the total throughput with the total MTCD number of the system in the simulation experiment
- FIG. 4 is a graph of the average access delay in the simulation experiment as a function of the total MTCD number of the system
- Fig. 5 is a graph showing the change of the probability of successful access with the total MTCD number of the system.
- the coverage of an eNB includes N MTCDs.
- the arrival model of each MTCD follows a beta distribution, and the channels of each MTCD follow Rayleigh fading. If all channel gains are independent, the specific process of the network random access 4 message is:
- the base station sends a second message Msg2 to the MTCD according to all selected PAs, and records the second message Msg2 as a random access response RAR.
- the random access response RAR includes the PA ID, uplink resource allocation, and instructions for selecting the PA.
- MTCD mark index and timing advance information and power allocation information corresponding to MTCD, MTCD monitors RAR represented by RA-RNTI on the physical downlink control channel PUSCH;
- the MTCD capable of listening to the RAR transmits the third message Msg3 on the corresponding physical uplink shared channel PUSCH according to the selected tag PA, and the third message Msg3 is PA ID + tag index + information to be sent according to the allocated power.
- Each MTCD of the same PA is NOMA multiplexed on the same physical uplink shared channel PUSCH through the power domain.
- the base station regards all MTCDs that choose the same PA as a NOMA device group, and uses SIC to decode the data packet of the NOMA device group on each physical uplink shared channel PUSCH, and sends a fourth message Msg4 to the MTCD that is successfully decoded.
- the message Msg4 is the competition resolution message CRI.
- the MTCD that received the CRI sends an acknowledgement ACK to the base station.
- the MTCD that does not receive the CRI performs uniform random backoff, and reconnects at the corresponding next random access opportunity RAO.
- any MTCD fails to RA within the maximum number of retransmissions, it is deemed that the MTCD access fails and the MTCD is discarded.
- the MTCD constitutes a NOMA device group.
- the RAR format is shown in Table 1.
- the base station estimates the Rayleigh fading channel coefficient corresponding to the MTCD according to the received power of each labeled PA.
- the MTCDs are sorted according to the modulo square of the Rayleigh fading channel coefficients of the MTCD of the PA selected, and the RAR is sent to the NOMA device group according to Table 1 according to the sorting order, where: PA ID and Tag index indicate that the MTCD corresponding to the tag PA is selected.
- the timing advance information TA is used for uplink synchronization of each MTCD.
- the uplink grant UL grant indicates the PUSCH allocated by the base station to the NOMA device group to transmit the third message Msg3.
- the power backoff is used to adjust the transmission power of each MTCD, so that the one MTCD can share the same PUSCH resource through multiplexing in the power domain.
- the power domain multiplexing scheme and SIC in the present invention are:
- Each MTCD of the same PA ID is selected to form a NOMA device group.
- the base station sorts the module squared according to the channel coefficient of each NOMA device group from large to small, and then sends a third message Msg3 on the same PUSCH according to the power domain multiplexing scheme.
- the transmit power of the i-th MTCD of a NOMA equipment group is:
- p max is the maximum transmission power constraint
- p u is the target arrival power of the first MTCD in the NOMA equipment group
- ⁇ is the power backoff factor
- M is the number of RBs allocated to the corresponding PUSCH, and the MTCDs of the same NOMA device group are the same;
- ⁇ represents the compensation for the difference in uplink and downlink path loss
- PL i is the estimated path loss of the i-th MTCD in the NOMA equipment group.
- Equation (1) shows that the MTCD's arrival power decreases one by one with the power backoff step size ⁇ , then the received signal y on the PUSCH corresponding to a PA ID is:
- g i is the Ruili fading coefficient, g i is a circularly symmetric complex Gaussian random variable with an independent mean of 0 and a variance of u;
- x i is the signal transmitted by the i-th MTCD
- n is an additional Gaussian white noise, n to N (0, ⁇ 2 ).
- the data packet that successfully detects the i-th MTCD in a NOMA device group can be expressed as: The data packets of the first i-1 MTCD have been successfully detected and removed from the acceptance signal:
- the SINR of the i-th MTCD is not less than the detection threshold, that is:
- the base station sorts the Moduli square of the Rayleigh channel coefficients of the MTCD that selected the PA from large to small:
- 2 , Then sort the MTCDs in this order, where the transmit power of the i-th MTCD is p i p u- (i-1) ⁇ + 10log 10 (M) + ⁇ PL i , where p i is expressed in watts as:
- the number of MTCDs in a NOMA group is limited and cannot be infinitely large.
- the reasonable value range of I is mainly discussed from the three factors that require the PA and SIC detection capabilities and time delay.
- N ZC 839, where N ZC represents the length of the ZC sequence, and let A mean that the tag indexes of one MTCD that selects a PA are different.
- the SIC detector adds a delay to the detection of each level of users.
- the complexity of the SIC detector will increase and the processing delay will increase. It will become too large to meet real-time requirements.
- the MAC contention resolution timer is 48 subframes. Since multiplication requires more time in the specific implementation, the multiplication time is used to represent the processing of the SIC detector. In time, the multiplier needs about 0.8us to complete one operation.
- the number of multiplication operations required by the traditional SIC detector is: 1 4 +2 4 +... + K 4 , which must be processed in 48ms.
- K ⁇ 12 combining the above factors.
- the number of MTCDs in a NOMA group can be limited to 1 to 13, but the present invention idealizes the above factors in subsequent solutions, as long as I is a positive integer can.
- an optimization problem which aims to optimize the maximum throughput that a PA can provide by optimizing the power backoff factor and selecting the number of devices of a PA, and has the following constraints: 1) the value of the power backoff factor Range; 2) a reasonable value range for the number of devices in a NOMA group; 3) the average probability that a MTCD will succeed in SIC decoding during J PA transmissions, the optimization problem can be expressed as:
- p s is the minimum average probability that an MTCD successfully accesses during J PA transmissions.
- T PA (I, ⁇ ) indicate the throughput that the PA can provide
- Q i (I, ⁇ ) indicates that the first i-1 MTCDs were successfully decoded and received from the received signal.
- the probability of successful decoding of the i-th MTCD is then
- T PA (I, ⁇ ) 1.Q 1 (I, ⁇ ) (1-Q 2 (I, ⁇ )) + 2Q 1 (I, ⁇ ) Q 2 (I, ⁇ ) (1-Q 3 (I, ⁇ )) + (11)
- T PA (I, ⁇ ) Q 1 (I, ⁇ ) + Q 1 (I, ⁇ ) Q 2 (I, ⁇ ) + Q 1 (I, ⁇ ) Q 2 (I, ⁇ ) Q 3 (I, ⁇ ) (12)
- the probability Q i (I, ⁇ ) is under the condition of
- 2 The solution is a probability distribution problem that is a linear weighted sum of sequential statistics. It is difficult and complicated to directly solve it.
- the classic conclusion of Sukhatme is used to convert it into a probability distribution problem of linear weighted sum of independent independent index random variables.
- 2 The corresponding variables are G 1 , G 2 , ... G I.
- the classic conclusion by Sukhatme is: sequential index random variable
- the spacing variable is:
- the interval variable is an independent exponential random variable, and its exponential distribution parameter is i times the exponential distribution parameter of the modulus square of each MTCD Rayleigh fading channel coefficient, that is, Using this conclusion to convert the weighted combination of sequential statistics into a weighted linear combination of exponential random variables with independent and different distributions, there are:
- the particle swarm optimization (PSO) algorithm with fast convergence speed is used to solve the optimal backoff factor and maximum throughput corresponding to each I value, and then traverse I to find the I and backoff factor that maximize the throughput.
- the basic idea of the PSO algorithm is to find the optimal solution through the cooperation and information sharing between individuals in the group.
- Speed that is, the change in the value of the i-th backoff factor in the next iteration is v i , then in the k-th iteration, the speed update formula of particle i is:
- the position update formula of particle i is:
- c 1 and c 2 are learning factors and acceleration constants, which are used to adjust the maximum step size of the learning
- rand () is a random number between 0 and 1 and is used to increase search randomness
- pbesti is the best position of particle i in the first k iterations
- gbest is the optimal position of the particle swarm in the first k iterations.
- the first term represents the previous velocity of the particles
- the second term represents the self-learning part
- the third term represents the social learning part.
- T PA (I, q) M 1 (I, q) + M 2 (I, q) + ... + M I (I, q) (39)
- a 1 (I, q) A 2 (I, q) ⁇ A 0 (I, q), where A 0 (I, q) q) is the product of I q-subtraction functions that take a positive value, so A 0 (I, q) is a subtraction function of q and takes a positive value.
- the traditional orthogonal random access scheme with traditional ACB and the non-orthogonal random access scheme with traditional ACB in the reference are used.
- 3dB 3dB
- Figure 3 is the change curve of the total throughput with the total MTCD number of the four schemes.
- the total throughput is defined as the number of MTCDs successfully accessed within the maximum number of transmissions.
- the ORA scheme is a traditional orthogonal with traditional ACB.
- the optimal scheme of the present invention has the best overall throughput performance, followed by the suboptimal scheme of the present invention, followed by the NORA scheme in the reference, and finally the slow growth of the total throughput. ORA program.
- the reference NORA scheme uses power domain multiplexing to allow PA colliding devices to transmit on the same PUSCH, the total throughput is greater than the ORA scheme, but the present invention finds the optimal power backoff factor and I, and according to the most The optimal solution adjusts the size of the ACB factor, allows more MTCDs to pass the ACB test, and uses the optimal power backoff scheme to fully allow more devices to backoff with a more efficient power transmission of the third message Msg3 on the same PUSCH, so that The total throughput is greatly increased.
- Figure 4 shows the change curve of the average access delay with the total MTCD number of the system in the three scenarios.
- the average access delay is defined as the average number of RAOs required for an MTCD from initial RA to successful access. 4 It can be known that the average access delay increases with the increase in the number of MTCDs. This is because the increase in the number of MTCDs leads to the increase of PA collision equipment. In addition, for the NORA solution, the SIC decoding burden increases, resulting in an increase in average access delay. It can be clearly seen from FIG. 4 that the optimal solution and the suboptimal solution in the present invention greatly reduce the average access delay of each MTCD.
- FIG. 5 shows the change curves of the successful access probability with the total MTCD number of the system under the four schemes.
- the successful access probability is defined as the ratio of the MTCD number of successful access to the total MTCD number.
- the present invention is applicable to a mM2M network with a larger number of MTCDs, which can greatly improve the throughput of the system.
- the average access delay can be reduced and the probability of successful access can be increased.
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Abstract
本发明公开了一种大规模M2M网络中基于最优功率退避的非正交随机接入方法,包括以下步骤:1)基站将ACB因子增大最优MTCD数I *倍后发送给所有MTCD,通过ACB检验的MTCD通过物理随机接入信道向基站发送第一个消息Msg1,判断选择同一PA的MTCD数量,即当前接入时隙发起随机接入尝试的MTCD数量;2)基站根据所有被选择的PA向MTCD发送第二个消息Msg2,MTCD监听物理下行控制信道PUSCH上以RA-RNTI表征的RAR;3)能够监听到RAR的MTCD根据所选标记PA传输第三个消息Msg3,同一PA的各MTCD通过功率域的复用在相同物理上行共享信道PUSCH上NOMA。4)基站采用SIC解码物理上行共享信道PUSCH上的数据包,并对成功解码的MTCD发送第四个消息Msg4,该方法能够有效的提升系统的吞吐量,降低设备接入时延。
Description
本发明属于大规模M2M网络中的随机接入技术领域,涉及一种大规模M2M网络中基于最优功率退避的非正交随机接入方法。
作为物联网的主要通信平台,M2M成为了5G的主要通信场景。3GPP将M2M通过蜂窝网络进行数据传输的通信方式定义为机器类通信(MTC)。然而,蜂窝网络中部署M2M存在3个关键问题:首先,由于机器类通信设备(MTCD)的数量巨大,大量基于事件触发型MTCD短时间内在物理随机接入信(PRACH)上采用基于竞争方式突发随机接入(RA),会引发接入碰撞,导致网络拥塞,产生较大的时延;其次,由于通信数据总量巨大但单次数据量小,若MTCD先通过随机接入与基站建立连接、再传输数据的通信方式,不仅造成MTCD与基站之间严重的信令开销,同时将降低系统资源利用率;最后由于无线资源有限,所以存
时频资源的合理分配问题。因此无论是从能源的节省,频谱资源的有效利用,还是设备的服务质量要求保障等方面来讲,急需针对MTCD的业务特性,对现有蜂窝网络进行改进和优化,研究大规模M2M(mM2M)在蜂窝网络中的有效随机接入方案。一些文献针对ACB机制做以改进,缓解了网络拥塞问题;一些文献针对资源的合理分配及有效使用深入研究,缓解了资源有限的问题。但是这些研究本质上不能根本解决mM2M网络的拥塞等问题,鉴于非正交多址接入技术的优点,有人提出通过功率域复用让碰撞设备成为一个NOMA组,这一方法大大缓解了网络拥塞,提升了系统吞吐量,降低了接入时延。然而,这一方法只是提出了一个框架,并没有深入研究怎样的功率域复用能获得最大吞吐量,也没有结合ACB机制做以调整,使系统充分发挥功率域复用的优势,进一步提升吞吐量,降低接入时延。
发明内容
本发明的目的在于克服上述现有技术的缺点,提供了一种大规模M2M网络中基于最优功率退避的非正交随机接入方法,该方法能够有效的提升系统的吞吐量,降低设备接入时延。
为达到上述目的,本发明所述的大规模M2M网络中基于最优功率退避的非正交随机接入方法包括以下步骤:
一个eNB的覆盖范围内包含N个MTCD,各MTCD的到达模型服从贝塔分布,各MTCD的信道服从瑞利衰落,设所有的信道增益均为独立的,则网络随机接入4消息具体过程为:
1)基站获取NOMA设备组中的最优MTCD数I
*,再将ACB因子增大I
*倍后发送给所有MTCD,通过ACB检验的MTCD通过物理随机接入信道向基站发送第一个消息Msg1,第一个消息Msg1为标记PA,标记PA包括PA及标记ZC序列,使得基站能够在随机接入RA的第一步鉴别出被MTCD选择的PA,判断选择同一PA的MTCD数量;
2)基站根据所有被选择的PA向MTCD发送第二个消息Msg2,将第二个消息Msg2记作随机接入响应RAR,随机接入响应RAR包括PA ID、上行资源分配、指示选择该PA的MTCD的标记索引以及对应MTCD的定时超前信息及功率分配信息,MTCD监听物理下行控制信道PUSCH上以RA-RNTI表征的RAR;
3)能够监听到RAR的MTCD根据所选标记PA,按照所分配的功率在对应物理上行共享信道PUSCH上传输第三个消息Msg3,第三个消息Msg3为PA ID+标记索引+需要发送的信息。同一PA的各MTCD通过功率域的复用在相同物理上行共享信道PUSCH上NOMA。
4)基站将所有选择同一PA的MTCD视为一NOMA设备组,再采用SIC解码每个物理上行共享信道PUSCH上NOMA设备组的数据包,并对成功解码的MTCD发送第四个消息Msg4,第四个消息Msg4,为竞争解决消息CRI,收到CRI的MTCD向基站回发确认信息ACK, 未收到CRI的MTCD进行均匀随机退避,并在对应的下一随机接入机会RAO重新接入,当任一MTCD在最大重传次数内未成功RA时,则认定该MTCD接入失败,并抛弃该MTCD。
设选择某一PA ID的MTCD有I个,该I个MTCD构成一个NOMA设备组基站根据每个标记PA的接收功率来估计对应MTCD的瑞利衰落信道系数,基站BS回发RAR之前,根据选择该PA的I个MTCD的瑞丽衰落信道系数的模平方从大到小对MTCD进行排序,并根据该排序顺序向该NOMA设备组发送RAR,其中,PA ID及Tag index指示选择相应标记PA的MTCD,定时超前信息TA用于每个MTCD的上行同步,上行授权UL grant表示基站为给NOMA设备组所分配的用来传输第三个信息Msg3的PUSCH,功率退避用于每个MTCD发射功率的调整,使得所述I个MTCD能够通过功率域的复用共享相同的PUSCH资源。
以功率退避因子的取值范围、一个NOMA设备组中MTCD的数量及一个MTCD在J次PA传输时SIC解码成功的平均概率为约束条件,以通过优化功率退避因子及选择某一PA的MTCD设备数为变量,以该PA所能提供的最大吞吐量为目标,构建优化问题:
其中,p
s为一个MTCD在J次PA传输时成功接入的最小平均概率;
对式(9)进行简化得:
其中,Q
i(I,q)表示前i-1个MTCD成功解码并从接收信号中移除时,第i个MTCD成功解码的概率。
当MTCD的最小传输速率约束R
0小于预设阈值时,则采用粒子群算法求解每个I值对应的最优退避因子,然后遍历I,求解最大化吞吐量的I及对应退避因子。
当MTCD的最小传输速率约束R
0大于等于预设阈值时,则采用归纳法求解退避因子的次优解,其中,退避因子次优解为q=1/β,然后遍历I求解I的次优解。
前i-1个MTCD成功解码并从接收信号中移除时,第i个MTCD成功解码的概率Q
i(I,q)为:
本发明具有以下有益效果:
本发明所述的大规模M2M网络中基于最优功率退避的非正交随机接入方法在具体操作时,通过最优功率退避因子及选择同一PA的最优MTCD数量构建系统模型,从而最大化一个PA所能提供的吞吐量,根据PA提供最大吞吐量时所能承载的MTCD数量调整ACB因子,让更多的MTCD通过ACB检验,从而让多个MTCD设备通过功率域的复用在相同的物理上行共享信道PUSCH上传输第三个消息Msg3,以达到提高系统吞吐量的目的,同时降低接入时延。
图1为本发明的流程图;
图2为本发明中粒子群算法的流程图;
图3为仿真实验中总吞吐量随系统总MTCD数的变化曲线图;
图4为仿真实验中平均接入时延随系统总MTCD数的变化曲线图;
图5为成功接入概率随系统总MTCD数的变化曲线图。
下面结合附图对本发明做进一步详细描述:
参考图1,本发明所述的大规模M2M网络中基于最优功率退避的非正交随机接入方法包括以下步骤:
一个eNB的覆盖范围内包含N个MTCD,各MTCD的到达模型服从贝塔分布,各MTCD的信道服从瑞利衰落,设所有的信道增益均为独立的,则网络随机接入4消息具体过程为:
1)基站获取NOMA设备组中的最优MTCD数I
*,再将ACB因子增大I
*倍后发送给所有MTCD,通过ACB检验的MTCD通过物理随机接入信道向基站发送第一个消息Msg1,第一个消息Msg1为标记PA,标记PA包括PA及标记ZC序列,使得基站能够在随机接入RA的第一步鉴别出被MTCD选择的PA,判断选择同一PA的MTCD数量;
2)基站根据所有被选择的PA向MTCD发送第二个消息Msg2,将第二个消息Msg2记作随机接入响应RAR,随机接入响应RAR包括PA ID、上行资源分配、指示选择该PA的MTCD的标记索引以及对应MTCD的定时超前信息及功率分配信息,MTCD监听物理下行控制信道PUSCH上以RA-RNTI表征的RAR;
3)能够监听到RAR的MTCD根据所选标记PA,按照所分配的功率在对应物理上行共享信道PUSCH上传输第三个消息Msg3,第三个消息Msg3为PA ID+标记索引+需要发送的信息。同一PA的各MTCD通过功率域的复用在相同物理上行共享信道PUSCH上的NOMA。
4)基站将所有选择同一PA的MTCD视为一NOMA设备组,采用SIC解码每个物理上行共享信道PUSCH上NOMA设备组的数据包,并对成功解码的MTCD发送第四个消息Msg4,第四个消息Msg4,为竞争解决消息CRI,收到CRI的MTCD向基站回发确认信息ACK,未收到CRI的MTCD进行均匀随机退避,并在对应的下一随机接入机会RAO重新接入,当任一MTCD在最大重传次数内未成功RA时,则认定该MTCD接入失败,并抛弃该MTCD。
设选择某一PA ID的MTCD有I个,该I个MTCD构成一个NOMA设备组,RAR格式如表1所示,基站根据每个标记PA的接收功率来估计对应MTCD的瑞利衰落信道系数,基站BS回发RAR之前,根据选择该PA的I个MTCD的瑞丽衰落信道系数的模平方从大到小对MTCD进行排序,并根据该排序顺序按照表1向该NOMA设备组发送RAR,其中,PA ID及Tag index指示选择相应标记PA的MTCD,定时超前信息TA用于每个MTCD的上行同步,上行授权UL grant表示基站为该NOMA设备组所分配的用来传输第三个信息Msg3的PUSCH,功率退避用于每个MTCD发射功率的调整,使得所述I个MTCD能够通过功率域的复用共享相同的PUSCH资源。
表1
一、本发明中功率域复用方案及SIC为:
选择同一PA ID的各MTCD构成一个NOMA设备组,基站根据各NOMA设备组的信道系数的模平方由大到小进行排序,然后按照功率域复用方案在同一PUSCH上发送第三个消息Msg3,一个NOMA设备组的第i个MTCD的发射功率为:
p
i=min{p
max,p
u-(i-1)ρ+10log
10(M)+ωPL
i} (1)
p
max为最大传输功率约束;
其中:p
u为NOMA设备组中第一个MTCD的目标到达功率;
ρ为功率退避因子;
M为对应PUSCH所分配的RB数,同一个NOMA设备组的MTCDs的M相同;
ω表示上下行路径损耗差的补偿;
PL
i为NOMA设备组中第i个MTCD对下行路径损耗的估计值。
式(1)表明MTCD的到达功率以功率退避步长ρ逐个递减,则某个PA ID对应的PUSCH上的接收信号y为:
其中:
h
i为第i个MTCD与eNB之间的信道系数,h
i=g
i/l
i;
g
i为瑞丽衰落系数,g
i为独立的均值为0,方差为u的圆周对称复高斯随机变量;
x
i为第i个MTCD发射的信号;
n为附加高斯白噪声,n~N(0,σ
2)。
于SIC,假设所有MTCD具有相同的最小传输速率约束R
0,则检测每个MTCD的信干噪比SINR的最小门限
成功检测一个NOMA设备组中第i个MTCD的数据包可以表示为:前i-1个MTCD的数据包已成功检测并从接受信号中移除:
SINR
1≥β,SINR
2≥β,...SINR
i-1≥β (3)
且第i个MTCD的SINR不小于检测门限,即:
基站在回发RAR之前,对选择该PA的I个MTCD的瑞丽信道系数模平方由大到小进行排序:|g
1|
2≥|g
2|
2≥...≥|g
I|
2,然后按照该顺序对各MTCD进行排序,其中,第i个MTCD的发射功率p
i=p
u-(i-1)ρ+10log
10(M)+ωPL
i,p
i表示为瓦特形式为:
则第i个MTCD的到达功率p
r,i为:
为了使SIC检测顺序与功率复用顺序一致,需有p
r,i≥p
r,i+1,i=1,...I-1,则有:
二、计算一个NOMA组中MTCD数实际的合理取值范围的具体步骤为:
一个NOMA组中的MTCD数是有限的,不可能无限大,主要从标记PA、SIC检测能力及时延要求3个因素讨论I的合理取值范围。
首先在传统LTE中,每个PA的标记索引数为N
ZC=839个,N
ZC表示ZC序列的长度,设A表示选择某一PA的I个MTCD的标记索引均不一样,则有
当P(A)≥90%时,I≤13,其次,SIC检测器对每级用户的检测都会增加一个时延,当系统负荷较大时,SIC检测器的复杂度会增加,处理时延也会变得很大,以致不能满足实时要求;最后,MAC竞争解决定时器时长为48个子帧,由于乘法运算在具体实现中需要更多时间,因此用乘法运算时间来表示SIC检测器的处理时间,乘法器完成一次运算大概需要0.8us,当有K级用户时,传统的SIC检测器所需的乘法运算次数为:1
4+2
4+…+K
4,要在48ms内处理完所有NOMA用户,则K<12,综合以上因素,实际中求解时可把一个NOMA组中MTCD的数量限制为1~13,但是本发明在后续求解中把以上因素理想化,只要I为正整数即可。
三、获取最优退避因子及一个NOMA设备组的最优MTCD数的具体操作为:
先构建优化问题,所述优化问题旨在通过优化功率退避因子及选择某一PA的设备数来优化该PA所能提供的最大吞吐量,并有以下约束条件:1)功率退避因子的取值范围;2)一个 NOMA组中设备数的合理取值范围;3)一个MTCD在J次PA传输时SIC解码成功的平均概率,则优化问题可以表示为:
其中:p
s为一个MTCD在J次PA传输时成功接入的最小平均概率。
当任一PA被I个MTCD选择时,令T
PA(I,ρ)表示该PA所能提供的吞吐量,Q
i(I,ρ)表示前i-1个MTCD成功解码并从接收信号中移除时,第i个MTCD成功解码的概率,则有
T
PA(I,ρ)=1·Q
1(I,ρ)(1-Q
2(I,ρ))+2·Q
1(I,ρ)Q
2(I,ρ)(1-Q
3(I,ρ))+ (11)
...+I·Q
1(I,ρ)Q
2(I,ρ)...Q
I(I,ρ)
对吞吐量表达式进行化简,则有:
T
PA(I,ρ)=Q
1(I,ρ)+Q
1(I,ρ)Q
2(I,ρ)+Q
1(I,ρ)Q
2(I,ρ)Q
3(I,ρ) (12)
+......+Q
1(I,ρ)Q
2(I,ρ)...Q
I(I,ρ)
然后需要对概率Q
i(I,ρ)进行求解,具体的,首先概率Q
i(Iρ)是在|g
1|
2≥|g
2|
2≥...≥|g
I|
2的条件下求解的,属于顺序统计量线性加权和的概率分布问题,直接求解较为困难复杂,在这里,应用Sukhatme的经典结论把其转化为相互独立指数随机变量的线性加权和的概率分布 问题,设定顺序统计量|g
1|
2≥|g
2|
2≥...≥|g
I|
2对应的变量为G
1,G
2,...G
I,由Sukhatme的经典结论有:顺序指数随机变量的间距变量为:
X
i=G
i-G
i+1,i=1,2,...I(令G
I+1=0) (13)
该间距变量为相互独立的指数随机变量,且其指数分布参数为每个MTCD瑞利衰落信道系数模平方的指数分布参数的i倍,即
利用该结论将顺序统计量的加权组合转化为相互独立不同分布的指数随机变量的加权线性组合,则有:
由式(15),得:
采用特征函数来求解Q
i(I,q)的概率分布;
则Z
i,n的特征函数为:
其中,系数α
i,n可通过一组方程得到:
1)当b
i,n>0时,对其求反变换,可得对应的PDF为:
2)当b
i,n<0时,对其求反变换,可得对应的PDF为:
则Z
I,i的PDF为:
则Q
i(I,q)可表示为:
根据以上推导,得到Q
i(I,q)的数学闭式表达式为:
综上,得优化问题的数学表达式为:
求解优化问题的具体过程为:
a)采用粒子群算法求解最优退避因子及一个NOMA组的最优MTCD数,具体为:
首先固定I,采用并行计算,收敛速度较快的粒子群(PSO)算法求解每个I值对应的最优退避因子及最大吞吐量,然后遍历I,求出使得吞吐量最大的I及退避因子,PSO算法的基本思想是通过群体中个体之间的协作和信息共享来寻找最优解。在本发明的优化问题中,取粒子数m=20,即初始化时随机选取20个退避因子,用q
i表示粒子i的位置,即第i个退避因子取值q
i,v
i表示粒子i的速度,即第i个退避因子下一次迭代时取值的变化量为v
i,则第k次迭代中,粒子i的速度更新公式为:
粒子i的位置更新公式为:
c
1,c
2为学习因子及加速度常数,用于调节学习最大步长;
rand()为0~1间的随机数,用于增加搜索随机性;
pbesti为前k次迭代中粒子i的最佳位置;
gbest为前k次迭代中粒子群的最佳位置。
在粒子速度更新公式中,第一项表示粒子先前的速度,第二项表示自我学习部分,第三项表示社会学习部分,具体算法流程见图3。
b)当最小传输数据速率较大时,采用归纳法对最小传输数据速率较大的设备求次优解。
β>1时,Q
i(I,q)的数学闭式表达式为:
ETSI协议表明已有的适用于智能电网的潜在技术中,数据速率有望大于3.0720bps/Hz,并且随着M2M网络的发展,未来几年MTCD的数据速率必定是越来越大的,则对应的SIC检测门限
也较大,此时
这一解区间占据了退避因子解空间的大部分,所以考虑在
上求解最优退避因子,此时,可以得到下述优化问题:
其中:
记:
则有:
对式(37)及(38)展开,得到T
PA(I,q)与T
PA(I+1,q)的关系如下:
T
PA(I,q)=M
1(I,q)+M
2(I,q)+...+M
I(I,q) (39)
B)假设T
PA(I,q)随q单调减,则T
PA(I+1,q)也单调减。
首先我们来证明命题B),假设T
PA(I,q)随q单调减,则T
PA(I+1,q)也单调减:
记:
为了证明命题B),需证明命题C):
C)F(I,q)是q的减函数;
命题C)的证明:
直接求导里面含有一个级数求和问题不好求,考虑缩放,令:
其中,Z(I,q)为q的减函数且取值为正,则A
1(I,q)=A
2(I,q)·A
0(I,q),其中A
0(I,q)为I个取值为正的q减函数的乘积,所以A
0(I,q)为q的减函数且取值为正。
综上,F(I,q)单调减。命题C)成立。
由于F(I,q)单调减,所以T
PA(I+1,q)相当于T
PA(I,q)中被相加的各项均乘了一个q的减函数,因此,命题B)成立。接下来证明命题A),具体的,
综上,命题A)成立。
另外,T
PA(1,q)=e
-ψβ与q无关。综上,
T
PA(I,q)在
上随q单调减,所以对于任意I值,T
PA(I,q)在
时取得最大值。因此,当MTCD数据传输速率较大时,对于任意I值,我们可以取退避因子的次优解为
然后遍厉I,从而求得I及q的次优解。
仿真实验
本次仿真实验的仿真参数设置如表2所示:
表2
为了证明本发明中最优方案与次优方案性能的优越性,采用带有传统ACB的传统正交随机接入方案及参考文献中带有传统ACB的非正交随机接入方案(功率退避因子为3dB)作为对比方案。
图3为四种方案下总吞吐量随系统总MTCD数的变化曲线,所述总吞吐量定义为在最大传输次数内成功接入的MTCD数,ORA方案即为带有传统ACB的传统正交随机接入方案,由图3可知,本发明的最优方案的总吞吐量性能最好,然后是本发明的次优方案,其次为参考文献中的NORA方案,最后为总吞吐量增长缓慢的ORA方案。因为参考文献的NORA方案采用功率域复用让PA碰撞的设备在相同PUSCH上传输,所以相比ORA方案总吞吐量更大,但是本发明求得了最优的功率退避因子及I,且根据最优解调整了ACB因子的大小,让更多MTCD通过ACB检验,并采用最优的功率退避方案充分地让更多设备以更高效的功率退避在相同PUSCH上传输第三个消息Msg3,从而使得总吞吐量大大增加。
图4所示为三种方案下平均接入时延随系统总MTCD数的变化曲线,所述平均接入时延定义为平均一个MTCD从初次RA到接入成功所需的RAO数,由图4可知,平均接入时延随MTCD数的增加而增加,这是因为MTCD数的增加导致PA碰撞的设备增加,此外对于NORA方案,SIC解码负担增加,从而导致平均接入时延增加。由图4可可明显看出本发明中的最优方案及次优方案大大降低了每个MTCD的平均接入时延。
图5所示为四种方案下成功接入概率随系统总MTCD数的变化曲线,所述成功接入概率定义为接入成功的MTCD数与总MTCD数的比值。由图5可知,本发明的最优及次优方案可以在最大重传次数内,提升MTCD的成功接入概率,而另外2种方案下,成功接入概率随MTCD数的增加而先不变后减小,这是因为MTCD数的增加导致PA碰撞的设备增加,重传设备增加,导致更多设备无法在最大重传次数内接入成功。由图5可知,本发明大大提升了每个MTCD的成功接入概率,更适合mM2M网络。
因此综上可知,本发明适用于MTCD数更多的mM2M网络,可以大大提升系统的吞吐量,对于每个MTCD,可以减小平均接入时延,增加成功接入概率。
以上内容是对本发明进行的详细说明,不能认定本发明的仅限于此,对于本发明所属技术领域的普通技术人员来说,在不脱离本发明构思的前提下,还可以做出若干简单的推演或替换,都应当视为属于本发明由所提交的权利要求书确定专利保护范围。
Claims (6)
- 一种大规模M2M网络中基于最优功率退避的非正交随机接入方法,其特征在于,包括以下步骤:一个eNB的覆盖范围内包含N个MTCD,各MTCD的到达模型服从贝塔分布,各MTCD的信道服从瑞利衰落,设所有的信道增益均为独立的,则网络随机接入4消息具体过程为:1)基站获取NOMA设备组中的最优MTCD数I *,再将ACB因子增大I *倍后发送给所有MTCD,通过ACB检验的MTCD通过物理随机接入信道向基站发送第一个消息Msg1,第一个消息Msg1为标记PA,标记PA包括PA及标记ZC序列,使得基站能够在随机接入RA的第一步鉴别出被MTCD选择的PA,判断选择同一PA的MTCD数量;2)基站根据所有被选择的PA向MTCD发送第二个消息Msg2,将第二个消息Msg2记作随机接入响应RAR,随机接入响应RAR包括PA ID、上行资源分配、指示选择该PA的MTCD的标记索引以及对应MTCD的定时超前信息及功率分配信息,MTCD监听物理下行控制信道PUSCH上以RA-RNTI表征的RAR;3)能够监听到RAR的MTCD根据所选标记PA,按照所分配的功率在对应物理上行共享信道PUSCH上传输第三个消息Msg3,第三个消息Msg3为PA ID+标记索引+需要发送的信息,同一PA的各MTCD通过功率域的复用在相同物理上行共享信道PUSCH上NOMA;4)基站将所有选择同一PA的MTCD视为一NOMA设备组,再采用SIC解码每个物理上行共享信道PUSCH上NOMA设备组的数据包,并对成功解码的MTCD发送第四个消息Msg4,第四个消息Msg4,为竞争解决消息CRI,收到CRI的MTCD向基站回发确认信息ACK,未收到CRI的MTCD进行均匀随机退避,并在对应的下一随机接入机会RAO重新接入,当任一MTCD在最大重传次数内未成功RA时,则认定该MTCD接入失败,并抛弃该MTCD。
- 根据权利要求1所述的大规模M2M网络中基于最优功率退避的非正交随机接入方法,其特征在于,设选择某一PA ID的MTCD有I个,该I个MTCD构成一个NOMA设备组,基站根据每个标记PA的接收功率来估计对应MTCD的瑞利衰落信道系数,基站BS回发RAR之前,根据选择该PA的I个MTCD的瑞丽衰落信道系数的模平方从大到小对MTCD进行排序,并根据该排序顺序向该NOMA设备组发送RAR,其中,PA ID及Tag index指示选择相应标记PA的MTCD,定时超前信息TA用于每个MTCD的上行同步,上行授权UL grant表示基站为该NOMA设备组所分配 的用来传输第三个信息Msg3的PUSCH,功率退避用于每个MTCD发射功率的调整,使得所述I个MTCD能够通过功率域的复用共享相同的PUSCH资源。
- 根据权利要求3所述的大规模M2M网络中基于最优功率退避的非正交随机接入方法,其特征在于,当MTCD的最小传输速率约束R 0小于预设阈值时,则采用粒子群算法求解每个I值对应的最优退避因子,然后遍历I,求解最大化吞吐量的I及对应退避因子。
- 根据权利要求1所述的大规模M2M网络中基于最优功率退避的非正交随机接入方法,其特征在于,当MTCD的最小传输速率约束R 0大于等于预设阈值时,则采用归纳法求解退避因子的次优解,其中,退避因子次优解为q=1/β,然后遍历I求解I的次优解。
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