A communication waveform design method

Abstract

The present invention discloses a communication waveform design method, which builds a high-efficiency spectrum efficiency and low bit error rate communication system transmission model based on time domain overlapping multiplexing waveform coding technology, improves spectrum efficiency with limited spectrum resources, and can effectively increase communication rate, reduce bit error rate, and realize efficient and secure transmission of communication.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a communication waveform design method. Background Art

[0002] With the development of mobile communication technology, the amount of communication data has increased dramatically. However, this raises the question of how to achieve efficient and secure communication in this massive data environment. As is well known, existing mobile communication technologies can increase signal bandwidth to increase the amount of data transmitted per unit time, improve spectral efficiency by using higher frequency bands, and increase signal constellation size through higher-order modulation to improve spectral efficiency.

[0003] However, given limited spectrum resources, simply shifting the spectrum to a higher frequency band cannot significantly improve spectrum efficiency. Therefore, time division multiple access (TDMA) was proposed. This technology divides time into periodic signal frames, each of which is further divided into several non-overlapping time slots. Different users communicate in different time slots, and guard intervals are set within the time slots to prevent overlap between adjacent time slots. TDMA technology significantly improves spectrum utilization, increases system capacity, overcomes the near-far effect, and provides better confidentiality. However, it also has some drawbacks, such as the system's over-reliance on synchronization. When the symbol transmission rate is too high, multipath delay spread significantly increases inter-symbol interference at the receiving end.

[0004] Building on TDMA technology, code division multiple access (CDMA) was developed. This technology leverages code sequence correlation to achieve multiple access communications and relies on different address codes to distinguish addresses, further improving spectrum efficiency. TD-SCDMA (Time Division Synchronous Code Division Multiple Access) combines the advantages of both CDMA and TDMA technologies, offering high system capacity, high spectrum efficiency, and strong anti-interference capabilities. While this technology significantly improves spectrum efficiency and enables efficient communication transmission, it also increases network complexity. Therefore, for efficient communication transmission, there is an urgent need for technologies that reduce complexity and significantly improve spectrum efficiency. Summary of the Invention

[0005] In order to overcome the shortcomings of the existing technology, the present invention provides a communication waveform design method, which builds a high-efficiency spectrum efficiency and low bit error rate communication system transmission model based on time-domain overlapping multiplexing waveform coding technology, thereby improving spectrum efficiency with limited spectrum resources, and can effectively increase communication rate, reduce bit error rate, and realize efficient and secure transmission of communication.

[0006] The technical solutions adopted by the present invention to solve the technical problems are as follows:

[0007] Step 1: Assume that the source sends a memoryless information sequence s with equal probability l×k, after LDPC encoding;

[0008] Step 2: The sequence after LDPC encoding is x l×n ; for x l×n A row sequence, assuming x=(x0,x1…x N-1 ), after QPSK modulation, the length is The I and Q paths of the binary sequence are and where u n ∈[1,-1], v n ∈[1,-1],

[0009] Step 3: For the I-channel information sequence, after passing through the shaping filter, time-domain overlapping multiplexing coding is performed. The symbol transmission period is shortened by K times, and the interval between adjacent symbols becomes T / K. Due to the shortened symbol interval, K adjacent symbols are shifted and overlapped, and the overlapped signals are superimposed as the encoded output.

[0010] The coded output signal obtained by weighting the multiplexed waveform in the shaping filter with the transmitted information sequence and shifting and superimposing is:

[0011]

[0012] Where h(t) is called the multiplexing function, which is the impulse response function of the shaping filter. The pulse shaping function of the shaping filter is evenly divided into K parts, and each waveform is denoted as a sub-multiplexing waveform h i (t), i=1,2…K, as shown below:

[0013]

[0014] The duration of each sub-multiplexing waveform function is T / K; wherein K represents the overlapping multiplexing number of the communication system;

[0015] Step 4: After the encoded output signal s(t) passes through the AWGN channel, the received signal at the receiving end is expressed as:

[0016]

[0017] Where n(t) represents additive Gaussian white noise;

[0018] The received signal y(t) at the receiving end is sampled at time t=nT / K to obtain the discrete signal:

[0019]

[0020] in:

[0021]

[0022] Among them, h i Indicates the pair multiplexing waveform h i The sampling value of (t), n n represents the sample value of additive white Gaussian noise n(t);

[0023] Step 5: y n Decoding;

[0024] In the AWGN channel, the conditional probability of receiving the signal at the nth moment is expressed as:

[0025]

[0026] Among them S n Indicates the status of the register;

[0027] Then the conditional probability of the overall received signal is expressed as:

[0028]

[0029] Taking the logarithm of the above formula is:

[0030]

[0031] The second term in the above formula is the Euclidean distance between path u and the received signal. When path u is the maximum likelihood path, its corresponding conditional probability is the largest and the Euclidean distance is the smallest. In this case, the path is the maximum likelihood path.

[0032] Step 6: After decoding, perform QPSK demodulation on the decoded I and Q information sequences to obtain r n , and then perform LDPC decoding to obtain the final destination output information sequence R n .

[0033] Preferably, the LDPC code is a linear block code, a linear block code with a code length of n and a number of information bits of k is generated by a generator matrix G k×n To define, the information sequence s l×k It is mapped to the codeword x=s·G through G; the linear block code can also be represented by a parity check matrix H (n-k)×n To describe equivalently, all codewords satisfy x·H T =0.

[0034] Preferably, the impulse response function h(t) of the shaping filter is a time-limited signal with a finite duration.

[0035] Preferably, the pair y nThe decoding adopts the optimal decoding algorithm based on maximum likelihood sequence detection - Viterbi decoding algorithm.

[0036] The beneficial effects of the present invention are as follows:

[0037] Compared with the traditional communication system coding model, the present invention has higher spectrum utilization and lower bit error rate under the use of limited spectrum resources, thus realizing efficient and secure transmission of communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of a communication system coding model based on time-domain overlapping multiplexing waveform coding technology used in the method of the present invention.

[0039] Figure 2 This is a schematic diagram of generating a coded signal when K=3 according to an embodiment of the present invention.

[0040] Figure 3 This is a schematic diagram of the time domain overlapping multiplexing coding structure according to an embodiment of the present invention.

[0041] Figure 4 Schematic diagram of spectrum utilization of the communication system coding model under the signal-to-noise ratio [0, 15dB] according to an embodiment of the present invention.

[0042] Figure 5 Schematic diagram of the communication rate of the communication system coding model under a transmission power of 30-45dBm according to an embodiment of the present invention.

[0043] Figure 6 Schematic diagram of the bit error rate of the communication system coding model under the signal-to-noise ratio of 0 to 14 dB according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The present invention will be further described below with reference to the accompanying drawings and examples.

[0045] Time-domain overlapping multiplexing waveform coding technology utilizes the principle of overlapping multiplexing to shift and overlap transmitted symbols, destroying the orthogonality between symbols and achieving improved spectral efficiency. Therefore, the present invention proposes a time-domain overlapping multiplexing waveform coding technology and establishes a high-efficiency spectral efficiency and low bit error rate communication system transmission model based on time-domain overlapping multiplexing waveform coding technology. This technology improves spectral efficiency with limited spectrum resources, effectively increases communication rates, reduces bit error rates, and achieves efficient and secure communication transmission.

[0046] The present invention proposes a communication waveform design method, based on which a corresponding communication system waveform coding model is built. Figure 1As shown in Figure 2, time-domain overlap multiplexing (TDOC) coding essentially compresses the symbol period based on the Nyquist system to increase the information rate at the transmitter. This results in a regular overlap between K adjacent symbols, where K is defined as the overlap multiplexing multiplier. By incorporating TDOC into the communication system coding model, the system's spectral efficiency and throughput can be improved.

[0047] Assume that the source sends a memoryless information sequence s with equal probability l×k , after LDPC coding, LDPC coding is a linear block code. A linear block code with a code length of n and the number of information bits k can be generated by a generator matrix G k×n To define, the information sequence s l×k It is mapped to the codeword x=s·G through G. Linear block codes can also be represented by a parity check matrix H (n-k)×n To describe equivalently, all codewords satisfy x·H T =0.

[0048] The sequence after LDPC encoding is x l×n , with x l×n As an example, let x=(x0,x1…x N-1 ), after QPSK modulation, the length is The I and Q paths of the binary sequence are and where u n ∈[1,-1], v n ∈[1,-1], Since the I-path and Q-path only differ in sequence, the subsequent steps are similar. Therefore, taking the I-path information sequence as an example, the information sequence is subjected to time-domain overlapping multiplexing encoding after passing through a shaping filter, where the impulse response function h(t) of the shaping filter is a time-limited signal with a finite duration.

[0049] In this communication system, the symbol transmission period is shortened by K times, and the interval between adjacent symbols becomes T / K. Due to the shortened symbol interval, K adjacent symbols are shifted and overlapped, and the overlapped signals are superimposed as the coded output. The system shift-and-address coding process is as follows: Figure 2 shown.

[0050] like Figure 2 and Figure 3 As shown, in this communication system, the coded output signal obtained by weighting the multiplexed waveform in the shaping filter with the transmitted information sequence and shifting and superimposing is:

[0051]

[0052] Where h(t) is called the multiplexing function, which is the impulse response function of the shaping filter. Here, the pulse shaping function of the shaping filter is evenly divided into K parts, and each waveform is recorded as a sub-multiplexing waveform h i (t)(i=1,2…K), as shown below:

[0053]

[0054] The duration of each sub-multiplexing waveform function is T / K, where K represents the overlapping multiplexing multiplicity of the communication system.

[0055] After the encoded output signal s(t) passes through the AWGN channel, the received signal at the receiving end can be expressed as:

[0056]

[0057] Where n(t) represents additive white Gaussian noise. The received signal y(t) at the receiving end is sampled at time t = nT / K to obtain the discrete signal:

[0058]

[0059] in:

[0060]

[0061] Among them, h i Indicates the pair multiplexing waveform h i The sampling value of (t), n n Represents the sampled values ​​of additive white Gaussian noise n(t).

[0062] Then, for y n The corresponding decoding is performed using the optimal decoding algorithm based on maximum likelihood sequence detection - the Viterbi decoding algorithm. Under the AWGN channel, the conditional probability of receiving the signal at the nth moment can be expressed as:

[0063]

[0064] Among them S n Indicates the status of the register.

[0065] Then the conditional probability of the overall received signal can be expressed as:

[0066]

[0067] Taking the logarithm of the above formula is:

[0068]

[0069] The second term in the above formula is the Euclidean distance between path u and the received signal. When path u is the maximum likelihood path, its corresponding conditional probability is the largest and the Euclidean distance is the smallest. At this time, the path is the maximum likelihood path.

[0070] After decoding, the decoded I and Q information sequences need to be demodulated by QPSK to obtain r n , and then perform LDPC decoding to obtain the final destination output information sequence R n .

[0071] Figure 1 is the spectrum utilization of the communication system coding model under the signal-to-noise ratio [0,15dB], Figure 2 The communication rate of the communication system coding model at a transmission power of 30 to 45 dBm. Figure 3 The bit error rate of the communication system model under the signal-to-noise ratio of 0 to 14dB is compared with the bit error rate under the time domain overlapping multiplexing coding and the bit error rate without time domain overlapping multiplexing coding. When the signal-to-noise ratio is 12dB, the bit error rate can reach 10 -5 .

Claims

1. A communication waveform design method, characterized in that: The steps include: Step 1: Assume that the source sends a memoryless information sequence s with equal probability l×k , after LDPC encoding; Step 2: The sequence after LDPC encoding is x l×n ; for x l×n A row sequence, assuming x=(x0,x1…x N-1 ), after QPSK modulation, the length is The I and Q paths of the binary sequence are and in Step 3: For the I-channel information sequence, after passing through the shaping filter, time-domain overlapping multiplexing coding is performed. The symbol transmission period is shortened by K times, and the interval between adjacent symbols becomes T / K. Due to the shortened symbol interval, K adjacent symbols are shifted and overlapped, and the overlapped signals are superimposed as the encoded output. The coded output signal obtained by weighting the multiplexed waveform in the shaping filter with the transmitted information sequence and shifting and superimposing is: Where h(t) is called the multiplexing function, which is the impulse response function of the shaping filter. The pulse shaping function of the shaping filter is evenly divided into K parts, and each waveform is denoted as a sub-multiplexing waveform h i (t), i=1,2…K, as shown below: The duration of each sub-multiplexing waveform function is T / K; where K represents the overlapping multiplexing number of the communication system; Step 4: After the encoded output signal s(t) passes through the AWGN channel, the received signal at the receiving end is expressed as: Where n(t) represents additive Gaussian white noise; The received signal y(t) at the receiving end is sampled at time t=nT / K to obtain the discrete signal: in: Among them, h i Indicates the pair multiplexing waveform h i The sampling value of (t), n n represents the sample value of additive white Gaussian noise n(t); Step 5: y n Decoding; In the AWGN channel, the conditional probability of receiving the signal at the nth moment is expressed as: Among them S n Indicates the status of the register; Then the conditional probability of the overall received signal is expressed as: Taking the logarithm of the above formula is: The second term in the above formula is the Euclidean distance between path u and the received signal. When path u is the maximum likelihood path, its corresponding conditional probability is the largest and the Euclidean distance is the smallest. In this case, the path is the maximum likelihood path. Step 6: After decoding, perform QPSK demodulation on the decoded I and Q information sequences to obtain r n , and then perform LDPC decoding to obtain the final destination output information sequence R n .

2. A communication waveform design method according to claim 1, characterized in that: The LDPC code is a linear block code. A linear block code with a code length of n and a number of information bits of k is generated by a generator matrix G k×n To define, the information sequence s l×k It is mapped to the codeword x=s·G through G; the linear block code can also be represented by a parity check matrix H (n-k)×n To describe equivalently, all codewords satisfy x·H T =0.

3. A communication waveform design method according to claim 1, characterized in that: The impulse response function h(t) of the shaping filter is a time-limited signal of finite duration.

4. A communication waveform design method according to claim 1, characterized in that: The pair n The decoding adopts the optimal decoding algorithm based on maximum likelihood sequence detection - Viterbi decoding algorithm.

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