Summary:
For the long-term evolution of railway (LTE-R) communication system, carry out adaptive modulation and coding (AMC) research. By introducing the Moore State Machine (MSM) model, an AMC strategy is proposed. According to the modulation and coding method (MCS) adopted by the LTE-R system, the finite state set of MSM is designed. For different modulation methods, the relationship curve between bit error rate (BER) and signal-to-noise ratio (SNR) is obtained. Given the target BER, the SNR thresholds corresponding to different modulation methods are obtained. On the basis of these thresholds, by adding and subtracting a certain SNR constant, the SNR thresholds corresponding to different MCSs are obtained. At the same time, in order to reduce the frequent switching of MCS near the SNR threshold, the upper and lower bounds are set on the SNR threshold to obtain the state transition SNR threshold interval of the MSM. Based on the obtained upper and lower bounds of the SNR threshold, the MSM is designed to realize the dynamic adjustment of the MCS. The simulation results show that the proposed AMC method has more stable spectrum efficiency and throughput than the traditional AMC method based on piecewise function. In addition, compared with the fixed modulation strategy, the proposed AMC method has better BER performance.
0 Preface
According to the plan of the International Railway Union, the future railway mobile communication will adopt the Long-Term Evolution for Railway (LTE-R) system [1]. The moving speed of high-speed trains can reach 350 km/h, and the terrain along the railway is complex and changeable, which makes the wireless channel state present dynamic changes. Adaptive Modulation and Coding (AMC) technology can dynamically adjust modulation and coding schemes (Modulation and Coding Schemes, MCS) based on real-time channel state information, which can significantly improve system performance. Therefore, in order to better provide high-quality communication services for users of the LTE-R system, it is of great significance to carry out AMC research.
The AMC issue has caused widespread concern. Aiming at the vehicular communication environment, literature [2] proposes an AMC (AMC-Piecewise Function, AMC-PF) method based on a piecewise function, which can adjust the MCS in time according to the channel state information. Literature [3], [4] proposed AMC strategy based on Markov model, which can get the steady-state probability of each MCS state. By combining the Hybrid Automatic Repeat Request (HARQ) protocol, the AMC schemes proposed in [5] and [6] can ensure that the system has good transmission accuracy. Literature [7] proposed an AMC scheme based on the best combination of power control and HARQ, which can significantly reduce the average transmit power. Literature [8] proposed an AMC mechanism based on Moore State Machine (MSM), which uses frame error rate and channel attenuation factor as the conversion parameters for different MCS states. On the basis of literature [8], literature [9] proposes an improved AMC strategy, which uses real-time signal-to-noise ratio (SNR) as the MSM state transition parameter, and sets the upper and lower bounds of the SNR threshold to avoid Switch MCS frequently.
However, the AMC-PF method will cause the MCS to frequently switch at the junction of the segmented intervals; although the Markov model can obtain the steady state probability of different states, it has the disadvantage of not being able to track the real-time channel state in time; the AMC method combined with HARQ exists A certain delay. MSM is a model that has a limited number of states and can transfer between these states. It has flexible and dynamic characteristics and is a powerful tool for analyzing dynamic changes. Therefore, inspired by the literature [8], [9], this article will use MSM to study the AMC problem in the LTE-R system. Different from literature [9], literature [9] obtains the SNR threshold through reference [1], and this article will obtain a more reasonable SNR threshold through simulation. In addition, performance evaluation of system error rate and throughput is also performed.
Aiming at the LTE-R communication system, this paper proposes an improved AMC method based on MSM. According to the modulation and coding method used in the LTE-R system, the finite state set of MSM is designed. According to different modulation methods, the relationship curve between Bit Error Rate (BER) and SNR is obtained, and the basic threshold corresponding to different modulation methods is obtained for a given target BER. Based on these thresholds, SNR thresholds corresponding to different MCSs are obtained by increasing and decreasing a certain SNR constant. At the same time, in order to reduce the frequent switching of MCS near the SNR threshold, the SNR threshold range for state transition is obtained by setting the upper and lower limits of the SNR threshold. According to the obtained upper and lower limits of the SNR threshold, the MSM is designed to realize the dynamic change of the MCS. Finally, through simulation, the performance of the proposed MSM-based AMC method is evaluated in terms of spectrum efficiency, bit error rate and throughput.
1 System model
The network structure of the LTE-R communication system is shown in Figure 1. Distributed base stations are used to solve the network coverage problem of high-speed railway communication systems [10]. The distributed base station separates the remote antenna unit (RAU) from the base band unit (BBU), and the BBU and RAU are used to process baseband signals and radio frequency signals respectively [11]. Centralize the BBU, core network, and wireless network control equipment in the computer room. RAUs can be flexibly set up along the railway. Multiple RAUs are connected to the BBU through optical fibers, which can avoid long-distance transmission of radio frequency signals, reduce transmission loss, and expand network coverage.
In addition, considering that the radio signal has serious penetration loss when it travels through the train compartments, it is necessary to install a Vehicular Station (VS) on the top of the train. In order to ensure reliable communication between the RAU and the train, two VSs are generally installed, respectively, on the top of the first and last carriages. The two can work independently or cooperatively according to the specific situation. At the same time, install a repeater (Repeater, R) in each carriage. Different User Equipment (UE) access the network through the repeater.
2 Adaptive modulation and coding method based on Moore state machine
This section proposes an improved MSM-based AMC method for the LTE-R communication system. First, set the finite state set of MSM; second, set the SNR threshold of MSM; finally, design a specific MSM.
2.1 Moore state machine finite state set setting
For the fast time-varying characteristics of the LTE-R system, consider Quadrature Phase Shift Keying (QPSK), 16-ary Quadrature Amplitude Modulation (16QAM) and Sixty Four Three kinds of modulation methods are used to control quadrature amplitude modulation (64-ary Quadrature Amplitude Modulation, 64QAM). Properly combine with {1/2, 2/3, 3/4} 3 kinds of coding efficiency to obtain the finite state set of MSM, which is represented by the symbol S. The elements of the set S are shown in formula (1):
Each state corresponds to an SNR threshold. MSM will perform state transitions based on real-time SNR, and adjust MCS in time to adapt to the current channel environment. For the "Stop" state in the state set, it means that when the real-time SNR is lower than a small SNR threshold, the system will stop sending data.
2.2 Moore state machine signal-to-noise ratio threshold setting
In wireless communication systems, different modulation methods have different BER performance. Under the Rayleigh fading channel, through simulation, the BER performance curves of QPSK, 16QAM and 64QAM are obtained, as shown in Figure 2. Assuming that the target BER is used, the SNR thresholds corresponding to the three modulation modes can be obtained, which are 7.31 dB, 11.55 dB, and 16.28 dB. This threshold is defined as the basic SNR threshold corresponding to the modulation mode.
On the basis of the modulation method, considering the coding efficiency, the SNR threshold is set. With the increase of SNR, it means that the channel conditions are good, and the channel coding can support higher coding efficiency. If the SNR gradually decreases, the channel conditions are poor and the coding efficiency needs to be reduced. Based on this idea, based on the modulation method, by adding and subtracting a certain SNR constant, the coding efficiency is taken into consideration, and the SNR threshold corresponding to the MSM state is set. In the QPSK modulation mode, the SNR thresholds for the coding efficiency of 1/2 and 3/4 are obtained by adding or subtracting 1.5 dB from 7.31 dB, which are 5.81 dB and 8.81 dB respectively. Similarly, the basic SNR threshold corresponding to 16QAM is 11.55 dB. Add and subtract 1.5 dB to obtain the SNR thresholds when the coding efficiency is 1/2 and 3/4, which are 10.05 dB and 13.05 dB. For 64QAM, add or subtract 1.5 dB from the basic SNR threshold of 16.28 dB to obtain the SNR thresholds for coding efficiency of 2/3 and 3/4, which are 14.78 dB and 17.78 dB, respectively. For the "Stop" state, the channel conditions are extremely poor at this time, the channel fading is very serious, the system will not send data, and the corresponding SNR threshold is assumed to be 0 dB.
For the LTE-R communication system, when the real-time SNR fluctuates in a small range around the threshold, the system will frequently switch MCS. If the real-time SNR is slightly lower or higher than the threshold, it has little impact on the currently adopted MCS, and it does not need to be changed immediately. Only when the SNR changes greatly, the MCS needs to be changed in time. In addition, in an actual high-speed railway communication system, changing the MCS requires a certain amount of processing time. If not necessary, try to avoid frequently changing system parameters. Therefore, if a reasonable upper and lower threshold is set at each SNR threshold to form an SNR threshold buffer, frequent MCS switching can be avoided to a large extent. For the 7 states of MSM, the following SNR threshold upper and lower limits are set:
among them,
i represents the SNR threshold corresponding to the i-th state, and Δi represents the SNR threshold change amount corresponding to the i-th state. The specific setting of the MSM state transition SNR threshold is shown in Table 1.
2.3 Moore state machine design
The SNR in the LTE-R communication system presents the characteristics of dynamic changes. According to the real-time SNR, the MSM dynamically switches between 7 states. In order to show the conversion relationship between the seven states more clearly, the design of MSM is divided into two scenarios: SNR increase and decrease. In the case of SNR increase, only when the real-time SNR increases to the upper limit of the SNR threshold as set in Table 1, the MSM performs state transition. The specific MSM is shown in Figure 3, where α represents the real-time SNR. For the case of SNR reduction, only when the real-time SNR is reduced to the lower limit of the SNR threshold as set in Table 1, the MSM performs state transition. The specific MSM is shown in Figure 4.
In actual application, the above two MSMs need to be combined. At the initial moment, according to the real-time SNR, the MSM will be in a certain state. Then, at the next moment, according to the real-time SNR, the MSM transitions from the current state to other states. If the real-time SNR is higher than the SNR at the previous moment, the MSM shown in Figure 3 is used for state transition. If the real-time SNR is lower than the SNR at the previous moment, the MSM shown in Figure 4 is used for state transition.
3 Simulation results and analysis
This section uses simulation to evaluate the performance of the proposed MSM-based AMC method. The relevant simulation parameters are set as follows: The upper limit and lower limit of the SNR threshold corresponding to the 7 states of MSM are shown in Table 1. For real-time SNR, assume that in 20 time slots, the SNR is α3=8.81 dB and α5=13.05 dB with small range fluctuation. In the first 10 time slots, the SNR takes a uniformly distributed random number in the interval of [7.0 dB, 9.5 dB], and in the last 10 time slots, the SNR takes a uniformly distributed random number in the interval of [12.0 dB, 14.0 dB]. The specific real-time SNR changes are shown in Figure 5.
Evaluate the volatility of spectrum efficiency. The spectral efficiency can be calculated by the following formula:
Among them, SE is the spectral efficiency, the unit is bit/s/Hz. SNR represents the real-time signal-to-noise ratio. Convert the SNR thresholds in Table 1 except for the "Stop" state into non-dB form, respectively: [3.81, 7.60, 10.12, 20.18, 30.06, 59.98]. Substituting equation (3) again, the spectral efficiency corresponding to the last six states of MSM can be obtained, which are: [2.26, 3.10, 3.47, 4.40, 4.96, 5.93], and the unit is bit/s/Hz. For the "Stop" state, since the system does not send any data, its spectrum efficiency is 0 bit/s/Hz.
Figure 6 compares the spectral efficiency volatility of the AMC-PF method and the MSM-based AMC (AMC-MSM) method. It can be seen from the figure that, compared with the AMC-PF method, the AMC-MSM method has greatly reduced spectral efficiency fluctuations and has a more stable spectral efficiency. The reason is that the AMC-MSM method sets the upper and lower limits of the SNR threshold, which can greatly reduce the frequent conversion of MCS.
Figure 7 shows the BER comparison result between the AMC-MSM method and the general modulation method. Compared with the QPSK modulation method, when the SNR is low, the BER performance of AMC-MSM is consistent with it, but as the SNR increases, the BER will increase. This is because the AMC-MSM method selects high-order modulation and coding methods according to the increase in SNR, so that the BER rises accordingly. Comparing the BER curves of 16QAM and 64QAM, it can be found that the BER performance of AMC-MSM is better in the case of low SNR. The reason is that the AMC-MSM method can select an appropriate modulation and coding method according to the SNR, which brings performance improvement.
In addition, the throughput performance is evaluated. Throughput can be calculated by the following formula:
Among them, T is the throughput; B is the system bandwidth, which is assumed to be 5 MHz.
Figure 8 compares the system throughput of the AMC-MSM method and the AMC-PF method. It can be seen that with the increase of SNR, the system throughput of the two methods is showing an increase. This is the complement of the previous BER curve. Although high-order modulation methods will increase BER, high-order modulation methods cannot be avoided due to the increase in BER. This is a process that needs to be balanced. In addition, the throughput curve of AMC-MSM is slightly lower than that of AMC-PF. This is because the AMC-MSM method considers avoiding frequent MCS conversion and sets the SNR threshold buffer.
4 Conclusion
This article proposes an improved AMC strategy based on MSM for LTE-R system. Through simulation, a more reasonable SNR threshold is obtained, and the SNR threshold buffer is set. The design can overcome the MSM of frequent MCS switching to a certain extent. The simulation results show that the proposed AMC-MSM method has more stable spectrum efficiency and throughput than the traditional AMC-PF method, and has better BER performance than higher-order modulation methods. Since the MSM state in this article only considers the modulation method and coding efficiency, the next step will be to design a more effective AMC method based on the data packet frame length.
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