Improved opportunistic network coding model for dynamically selecting coding
By introducing adaptive channel assessment and buffer management into the opportunistic network coding model, and dynamically selecting coding strategies, the problems of high bit error rate and low resource utilization in multi-user and multi-relay environments are solved, and more efficient transmission performance is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING COLLEGE OF INFORMATION TECH
- Filing Date
- 2025-12-10
- Publication Date
- 2026-04-14
AI Technical Summary
Existing opportunistic network coding models cannot respond to changes in channel state in real time in complex network environments with multiple users and multiple relays, resulting in high bit error rates and low resource utilization.
By introducing an adaptive channel evaluation mechanism and real-time coding strategy adjustment, combined with channel gain and buffer management, the optimal coding strategy is dynamically selected to optimize the coding decisions of relay nodes.
It significantly improves transmission efficiency in multi-user, multi-relay environments, reduces bit error rate, and optimizes resource utilization. Simulation experiments show that under low channel gain conditions, transmission efficiency is improved by 25%, bit error rate is reduced by 15%, and resource utilization is improved by 18%.
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Abstract
Description
Technical Field
[0001] This invention relates to the field of wireless network technology, and more specifically to an improved opportunistic network coding model with dynamic selection coding. Background Technology
[0002] Opportunistic Network Coding (ONC), a network coding method based on dynamic selection coding, has been widely used in wireless networks due to its ability to adaptively combine data packets under dynamic channel conditions. Unlike traditional network coding methods, ONC can flexibly adjust its coding strategy according to the current channel state and network requirements in unstable wireless channel environments. Therefore, it has high flexibility and efficiency, especially in resource-constrained environments, effectively improving data transmission performance. Its working principle is as follows: In the encoding phase, after receiving multiple data packets, the relay node selects a suitable encoding method based on the current network state, such as simple superposition of data packets (e.g., XOR operation) or complex linear encoding. In the transmission phase, the relay node sends the encoded data packets to the target node. In the decoding phase, the receiving node recovers the original data by reverse decoding based on its stored known data packets and the received encoded data packets. Through this process, ONC effectively reduces the number of transmissions and channel occupancy time, exhibiting particularly good performance in multi-user cooperative communication.
[0003] Current research on opportunistic network coding mainly focuses on the utilization of channel state information and the selection of coding strategies. For example, researchers have proposed some coding selection strategies based on channel gain, but these methods often cannot cope with complex network environments with multiple users and multiple relays in real time. Other studies focus on reducing the bit error rate through buffer optimization, but lack comprehensive consideration of real-time channel monitoring. Therefore, the innovation of this invention lies in combining channel assessment and dynamic buffer management to propose a dynamic selection coding strategy suitable for complex scenarios, aiming to provide a new solution for opportunistic network coding in cooperative communication systems. Summary of the Invention
[0004] 1. The technical problem to be solved: To address the aforementioned technical problems, this invention provides an improved opportunistic network coding model design and application based on dynamic selection coding. This model, by introducing an adaptive channel evaluation mechanism and real-time coding strategy adjustment, effectively improves coding decision efficiency in multi-user, multi-relay scenarios, reduces bit error rate, and optimizes system resource utilization. Specifically, the main contributions of this research are: First, a novel dynamic selection coding algorithm is proposed, which can intelligently select the optimal coding strategy based on real-time channel and buffer states; second, simulation experiments verify the significant advantages of the improved model in transmission efficiency, resource utilization, and bit error rate.
[0005] 2. Technical Solution: An improved opportunistic network coding model with dynamic selection coding is characterized by: real-time channel assessment and buffer management improvements to opportunistic network coding; selecting the optimal coding strategy based on the assessed channel state information and buffer state, thereby improving transmission performance in complex multi-user, multi-relay environments; wherein channel gain is used to assess the channel quality when forwarding different data packets, and the appropriate data packet corresponding to high channel quality is selected to be transmitted to the next process; in the buffer management improvement, the optimal coding strategy is to select the data packet with the most potential stored in the buffer for coding.
[0006] Furthermore, in the improved opportunistic network coding model, each relay node monitors the status of its connected channel in real time and evaluates the channel quality based on channel gain; each relay node is based on channel gain... Determine the quality of the corresponding channel conditions; when the channel gain is lower than a preset threshold... At that time, the corresponding relay node will select appropriate data packets for encoding and combination based on a preset selection method to improve the channel quality; the channel gain is the ratio between the received signal strength and noise, including signal-to-noise ratio or signal-to-noise ratio; wherein the preset selection method is a method of selecting data packets that can improve the probability of successful decoding by the receiver after encoding and combination.
[0007] Furthermore, in the improved opportunistic network coding model, each relay node selects and encodes the two most promising data packets based on the data packets stored in its buffer, thereby increasing the decoding opportunities at the receiver. Specifically, the relay node... Check the cache capacity of the relay node. When the cache capacity is lower than the preset cache capacity, its core task is to quickly clear the inventory and select the data packets with the highest deterministic decoupling as the two most promising data packets for encoding. The data packets with the highest deterministic decoupling are those that the relay node is certain, based on feedback information from the receiving end, that at least one receiving end can immediately decode a brand new and required data packet after receiving this encoded packet. When the cache capacity is higher than the preset cache capacity, its core task is global performance optimization; that is, from different combinations of data packets, select the data packet pair that can generate the greatest positive benefit to the entire network cooperation at the current moment; the basis for the greatest positive benefit includes: whether the downstream node can determine whether the data packet can be decoded, the utility value of the data packet after decoding, the transmission cost of the channel, and the impact on the network structure.
[0008] Furthermore, the improved opportunistic network coding model also includes a dynamic feedback mechanism, specifically: at each relay node, whenever the channel state or buffer state changes, the relay node adjusts the coding strategy based on real-time information.
[0009] Furthermore, in the improved opportunistic network coding model, the coding function of each relay node... for: In the above formula, This refers to the data packet encoded with X and Y.
[0010] Furthermore, the selection of encodings using the improved model includes: Each relay node calculates the channel quality based on the current channel gain and compares it with a preset threshold. If the channel quality is good, it selects either traditional direct forwarding or a simple coding strategy. If the channel quality is poor, it selects appropriate data packets for encoding and transmission based on the buffer status. Each relay node selects and encodes the two most promising data packets based on its current cache. The encoded data packet is transmitted to the receiving end, where the data is recovered using a decoding algorithm.
[0011] 3. Beneficial effects: (1) The present invention provides an improved opportunistic network coding model with dynamic selection coding, which dynamically adjusts the coding strategy of relay nodes through real-time channel assessment and buffer management, so as to improve transmission efficiency, reduce bit error rate and optimize resource utilization in complex wireless network environments.
[0012] (2) The present invention provides an improved opportunistic network coding model for dynamic selection coding. The model introduces a dual-criteria decision mechanism: (1) Channel condition criterion: The relay node monitors the channel gain in real time and compares it with a preset threshold to decide whether to start coding combination; (2) Buffer state criterion: Based on the combination potential and decoding possibility of data packets in the buffer, the optimal data packet pair is selected for coding.
[0013] (3) The present invention provides an improved opportunistic network coding model with dynamic selection coding, which adopts a dynamic feedback mechanism. When a relay node detects a change in channel state or buffer state, it adjusts the coding strategy in real time to adapt to the dynamic changes in the network. The model defines a dynamic coding function that selects direct forwarding or combined coding based on whether the channel gain exceeds a threshold, thereby achieving strategy self-adaptation.
[0014] (4) The present invention provides an improved opportunistic network coding model with dynamic selection coding. Through mathematical modeling and performance optimization, a closed-form expression for the overall successful transmission probability and bit error rate is derived, proving that it can significantly improve system performance in multi-relay scenarios. In simulation experiments, the model achieves a transmission efficiency improvement of about 25%, a bit error rate reduction of 15%, and a resource utilization improvement of 18% under low channel gain conditions (such as 10 dB), verifying its effectiveness and superiority in actual cooperative communication scenarios. Attached Figure Description
[0015] Figure 1 A comparison of the transmission efficiency of the improved model for traditional opportunistic network coding and verification under different channel gains; Figure 2 A comparison of the bit error rate of the improved model of traditional opportunistic network coding and verification under different channel conditions; Figure 3 A comparison chart of resource utilization for the improved model of traditional opportunistic network coding and verification examples. Detailed Implementation
[0016] The present invention will now be described in detail with reference to embodiments and verification examples.
[0017] An improved opportunistic network coding model with dynamic selection coding is characterized by: real-time channel assessment and buffer management improvements to opportunistic network coding; selecting the optimal coding strategy based on the assessed channel state information and buffer state, thereby improving transmission performance in complex multi-user, multi-relay environments; wherein channel gain is used to assess the channel quality when forwarding different data packets, and the appropriate data packet corresponding to high channel quality is selected to be transmitted to the next process; in the buffer management improvement, the optimal coding strategy is to select the data packet with the most potential stored in the buffer for coding.
[0018] Furthermore, in the improved opportunistic network coding model, each relay node monitors the status of its connected channel in real time and evaluates the channel quality based on channel gain; each relay node is based on channel gain... Determine the quality of the corresponding channel conditions; when the channel gain is lower than a preset threshold... At that time, the corresponding relay node will select appropriate data packets for encoding and combination based on a preset selection method to improve the channel quality; the channel gain is the ratio between the received signal strength and noise, including signal-to-noise ratio or signal-to-noise ratio; wherein the preset selection method is a method of selecting data packets that can improve the probability of successful decoding by the receiver after encoding and combination.
[0019] Furthermore, in the improved opportunistic network coding model, each relay node selects and encodes the two most promising data packets based on the data packets stored in its buffer, thereby increasing the decoding opportunities at the receiver. Specifically, the relay node... Check the cache capacity of the relay node. When the cache capacity is lower than the preset cache capacity, its core task is to quickly clear the inventory and select the data packets with the highest deterministic decoupling as the two most promising data packets for encoding. The data packets with the highest deterministic decoupling are those that the relay node is certain, based on feedback information from the receiving end, that at least one receiving end can immediately decode a brand new and required data packet after receiving this encoded packet. When the cache capacity is higher than the preset cache capacity, its core task is global performance optimization; that is, from different combinations of data packets, select the data packet pair that can generate the greatest positive benefit to the entire network cooperation at the current moment; the basis for the greatest positive benefit includes: whether the downstream node can determine whether the data packet can be decoded, the utility value of the data packet after decoding, the transmission cost of the channel, and the impact on the network structure.
[0020] Furthermore, the improved opportunistic network coding model also includes a dynamic feedback mechanism, specifically: at each relay node, whenever the channel state or buffer state changes, the relay node adjusts the coding strategy based on real-time information.
[0021] Furthermore, in the improved opportunistic network coding model, the coding function of each relay node... for: In the above formula, This refers to the data packet encoded with X and Y.
[0022] Furthermore, the selection of encodings using the improved model includes: Each relay node calculates the channel quality based on the current channel gain and compares it with a preset threshold. If the channel quality is good, it selects either traditional direct forwarding or a simple coding strategy. If the channel quality is poor, it selects appropriate data packets for encoding and transmission based on the buffer status. Each relay node selects and encodes the two most promising data packets based on its current cache. The encoded data packet is transmitted to the receiving end, where the data is recovered using a decoding algorithm.
[0023] I. The working principle of traditional opportunistic network coding: Opportunistic Network Coding (ONC) is an improved form of network coding. Its core idea is to dynamically select a suitable coding strategy based on network conditions (such as channel conditions and buffer status). By utilizing opportunistic data interactions between nodes, ONC achieves more flexible coding operations in dynamic environments.
[0024] Its working principle is as follows: During the encoding phase, after receiving multiple data packets, the relay node selects a suitable encoding method based on the current network state, such as simple superposition of the data packets (e.g., XOR operation) or complex linear encoding. During the transmission phase, the relay node sends the encoded data packets to the target node. During the decoding phase, the receiving node recovers the original data by reverse decoding based on its stored known data packets and the received encoded data packets.
[0025] Through this process, ONC effectively reduces the number of transmissions and channel occupancy time, and demonstrates excellent performance, especially in multi-user cooperative communication.
[0026] 1. Mathematical description of basic encoding operations In opportunistic network coding, the most basic operation is the combination and encoding of data packets. Suppose a relay node receives two data packets A and B, which can be encoded as follows: (1) XOR Coding C = A⊕B (1); In the above formula, This represents a bitwise XOR operation. The expression indicates that if the receiving node knows A, it can perform the reverse operation. , Restore B.
[0027] (2) Linear Coding C = αA + βB (2; In the above formula, α and β are coding coefficients, which are usually chosen over the finite field GF(q). Linear coding can handle more complex scenarios, especially in multi-user environments where it has greater flexibility, but its computational complexity is higher.
[0028] 2. Decision-making mechanism of relay nodes In cooperative communication systems, the primary task of relay nodes is to determine how to combine and encode received data packets. In traditional opportunistic network coding models, the decision-making mechanism includes the following two parts: (1) Channel State Judgment: The relay node selects the coding strategy based on the real-time Channel State Information (CSI). When the channel quality is high, directly forwarding the original data packet may be the best choice; while when the channel quality is poor, combining multiple data packets through coding to enhance anti-interference capability becomes a better strategy.
[0029] (2) Utilization of buffer state: The state of the relay node's buffer determines the types and number of data packets that can be combined. For example, when the buffer only stores two data packets, A and B, the relay node can choose the encoding method. The larger the cache, the more encoding combinations are available, thereby improving transmission efficiency.
[0030] Despite the significant advantages of the traditional ONC model, it still faces the following challenges in practical applications: In multi-relay and multi-user environments, nodes need to quickly determine coded combinations, which places high demands on computational power. Due to channel instability, ONC may result in some coded data failing to be decoded correctly, thus increasing the transmission error rate. The traditional model lacks comprehensive consideration of buffer and channel resources, leading to low resource utilization.
[0031] To address the aforementioned issues, this application proposes an improved opportunistic network coding model based on dynamic selection coding. This model improves transmission performance in complex multi-user, multi-relay environments by combining channel state information (CSI) and buffer state to select the optimal coding strategy through real-time channel assessment and buffer management.
[0032] II. Bit error rate of this application: In cooperative communication, the decoding success rate at the receiver is affected by channel conditions and the choice of relay nodes. Assuming the channels between relay nodes are independent and follow a Rayleigh distribution, the channel gain... probability density function It can be represented as: (4); In the above formula, This represents the average channel gain. It is calculated by superimposing the values from each relay node M. i The probability of successful transmission, the overall probability of successful transmission. for: (5); According to the properties of the Rayleigh distribution This can be further deduced as follows: (6) therefore, The expression is: (7) In cooperative communication, the bit error rate (BER) is primarily determined by channel conditions and node selection decisions. Let... The bit error rate of a single relay node is given by the overall bit error rate, which can be approximated as: (8) For the improved opportunistic network coding model in this application, since the relay nodes select the optimal coding combination, the overall bit error rate is reduced. It is assumed that... For the traditional model but: (9) Through the above derivation process, the improved model proposed in this invention can achieve efficient and flexible coding decisions, and significantly improve the transmission performance of cooperative communication systems in complex environments.
[0033] III. Verification Example: To verify the effectiveness of the proposed improved opportunistic network coding model based on dynamic selection coding, this paper designs a series of simulation experiments. The experiments mainly include the following aspects: experimental design, dataset (simulation environment) selection, simulation parameter setting, comparative analysis with traditional methods, and quantitative analysis of the results.
[0034] 1. Experimental Design The experiment used the NS-3 (Network Simulator 3) simulation platform, which is commonly used in simulation environments. This platform provides extensive support for network communication modules and is particularly suitable for performance evaluation of wireless communication and network coding.
[0035] Simulation environment settings: Node configuration: The network is configured with 5 source nodes, 10 relay nodes and 1 receiver node. Communication between nodes is based on a wireless channel model.
[0036] Channel model: The AWGN (Additive White Gaussian Noise) channel model is adopted to take into account the noise and interference of the wireless channel.
[0037] Channel gain: Each relay node dynamically adjusts its coding strategy based on channel gain and channel state information (CSI).
[0038] Cache management: The cache size of the relay node is set to 10 data packets, and the cache status is dynamically monitored to select the optimal combination of data packets.
[0039] 2. Simulation parameter settings During the simulation, the following main parameters were set: channel bandwidth: 20 MHz, transmission power: 20 dBm, channel gain threshold: set to 10 dB, 15 dB, and 20 dB according to different experimental scenarios. Node mobility: static node positions were used.
[0040] Simulation duration: Each simulation lasts 500 seconds.
[0041] Throughput: Calculates the amount of data successfully transmitted per unit time in each simulation scenario.
[0042] Bit error rate (BER): The bit error rate is calculated from the decoding results at the receiving end.
[0043] 1) Transmission efficiency As attached Figure 1 The results show that the improved model can significantly improve data transmission efficiency under low channel gain conditions. Specifically, the improved model improves transmission efficiency by about 20% when the channel gain is 10 dB, and by 30% when the channel gain is 15 dB. This is mainly due to the dynamic selection coding strategy, which prioritizes combined data transmission when the channel is poor, thus reducing the probability of transmission failure.
[0044] 2) Bit error rate As attached Figure 2 Experimental results show that under poor channel conditions, the traditional opportunistic network coding model has a high bit error rate, while the improved model can effectively reduce the bit error rate. In particular, when the channel gain is less than 15 dB, the bit error rate of the improved model is significantly lower than that of the traditional model, achieving a reduction of about 15%.
[0045] 3) Resource utilization rate As attached Figure 3 Resource utilization measures the use of channel bandwidth and buffer space. The improved dynamic selection coding model is more efficient in utilizing network resources, especially under low channel gain conditions, and can better balance the load on channel bandwidth and node buffers, thereby optimizing resource utilization. Because the dynamic selection coding strategy can reduce redundant transmissions, resource utilization is improved by 15% in multi-user scenarios.
[0046] Experimental results show that the improved opportunistic network coding model proposed in this invention can effectively improve transmission efficiency and resource utilization, and reduce the bit error rate in complex cooperative communication scenarios. The dynamic selection coding strategy exhibits excellent adaptability when facing different channel conditions.
[0047] Although the present invention has been disclosed above with reference to preferred embodiments, these are not intended to limit the invention. Any person skilled in the art can make various changes or modifications without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention should be defined by the scope of the claims of this application.
Claims
1. An improved opportunistic network coding model with dynamic selection coding, characterized in that: Real-time channel assessment and buffer management are improved for opportunistic network coding. The optimal coding strategy is selected based on the assessed channel state information and buffer state, thereby improving the transmission performance in complex multi-user and multi-relay environments. Among them, channel gain is used to evaluate the channel quality when forwarding different data packets, and the appropriate data packets corresponding to high channel quality are selected to be sent to the next process. In improving cache management, the optimal encoding strategy is to select the most promising data packet stored in the cache for encoding.
2. The improved opportunistic network coding model design for dynamic selection coding according to claim 1, characterized in that: In the improved opportunistic network coding model, each relay node monitors the status of its connected channel in real time and evaluates the channel quality based on channel gain; each relay node is based on channel gain. Determine the quality of the corresponding channel conditions; when the channel gain is lower than a preset threshold... At that time, the corresponding relay node will select appropriate data packets for encoding and combination based on a preset selection method to improve the channel quality; the channel gain is the ratio between the received signal strength and noise, including signal-to-noise ratio or signal-to-noise ratio; wherein the preset selection method is a method of selecting data packets that can improve the probability of successful decoding by the receiver after encoding and combination.
3. The improved opportunistic network coding model design for dynamic selection coding according to claim 1, characterized in that: In the improved opportunistic network coding model, each relay node selects and encodes the two most promising data packets based on the data packets stored in its buffer, thereby increasing the decoding opportunities at the receiver. Specifically: Relay nodes... Check the cache capacity of the relay node. When the cache capacity is lower than the preset cache capacity, its core task is to quickly clear the inventory and select the data packets with the highest deterministic decoupling as the two most promising data packets for encoding. The data packets with the highest deterministic decoupling are those that the relay node is certain, based on feedback information from the receiving end, that at least one receiving end can immediately decode a brand new and required data packet after receiving this encoded packet. When the cache capacity is higher than the preset cache capacity, its core task is global performance optimization; that is, selecting the data packet pair that can generate the greatest positive benefit to the entire network cooperation at the current moment from different data packet combinations. The criteria for the maximum positive benefit include: whether the downstream node can decode the data packet, the utility value of the decoded data packet, the transmission cost of the channel, and the impact on the network structure.
4. The design of an improved opportunistic network coding model for dynamic selection coding according to claim 2 or 3, characterized in that: The improved opportunistic network coding model also includes a dynamic feedback mechanism, specifically: at each relay node, whenever the channel state or buffer state changes, the relay node adjusts the coding strategy based on real-time information.
5. The improved opportunistic network coding model design for dynamic selection coding according to claim 1, characterized in that: In the improved opportunistic network coding model, the coding function of each relay node... for: In the above formula, This refers to the data packet encoded with X and Y.
6. The improved opportunistic network coding model design for dynamic selection coding according to claim 1, characterized in that: Encoding selection using improved models includes: Each relay node calculates the channel quality based on the current channel gain and compares it with a preset threshold. If the channel quality is good, it selects either traditional direct forwarding or a simple coding strategy. If the channel quality is poor, it selects appropriate data packets for encoding and transmission based on the buffer status. Each relay node selects and encodes the two most promising data packets based on its current cache. The encoded data packet is transmitted to the receiving end, where the data is recovered using a decoding algorithm.