Journal articles on the topic 'Higher-order MIMO detection'

In this paper, we investigate synchronization and equalization of 2 x 2 MIMO signals. We make a step further than that is described in our patent. In the patent, 3 PLLs and a four-channel adaptive filter was needed. Here we decrease the number of PLLs to two and use an adaptive filter of only four channels. In addition to that, we shortly introduce the filter method and the FFT method as well, for synchronization. False detection cancellation is also mentioned. The so-called 1-bit technique has been compared to our method. After briefly introducing the ideas, detailed Matlab or AWR analyses follow. Input data are real measurements, so the analyses serve also as experimental verifications. We take a glimpse on higher order MIMO and higher order modulations as well.

The multiple-input and multiple-output (MIMO) technology is a promising area of research to cope up with the demands of higher data rates and capacity. In the optical communication domain, the combination of space-division multiplexing (SDM) with higher-order modulation (HOM) formats over an optical MIMO system actively addresses these challenges. By allowing multi-level signaling with limited increment in the transmitter’s complexity, a jointly designed pre- and post-equalization (PPE) for an optical MIMO system with a multi-mode fiber (MMF) link is proposed. Cost-effectiveness of the system is incorporated by utilizing intensity modulation/direct detection (IM/DD) with HOM formats such as pulse-amplitude modulation (PAM) schemes. With the aid of a numerical optimization algorithm, the proposed joint-PPE filter coefficients are optimized with respect to the MMF channel and the transmit power constraint. In contrast to existing research on the single-mode fiber (SMF) based optical systems, the effectiveness of the proposed joint-PPE filter is analyzed on an MMF link, which is considerably degraded by the modal dispersion. In the analyzed experimental scenario, the proposed joint-PPE scheme confirms to be beneficial as compared to the post-equalization only (PE-only) in terms of bit-error rate (BER) performance. Furthermore, the required average received optical power to reach a BER 10−4 by the joint-PPE scheme is improved by 2 dB with comparison to the minimum mean-squared error (MMSE) PE-only.

As 5G communication networks are maturing, we have higher and higher requirements for the detection of communication signals. In this paper, for the Massive MIMO system signal detection problem, we mainly summarize the detection algorithms that can be used to replace the traditional ZF and MMSE, so as to avoid large-scale matrix inverse and reduce the computational complexity. It mainly includes the general iterative method, typically represented by SSOR, which makes the transmit signal matrix constantly close to the ideal value by iterating; the other is the level expansion class solution method, which takes the order expansion of the level as the initial value of the iteration to accelerate the convergence rate of the algorithm, typically represented by the MLI algorithm. However, today where the demand for communication is gradually increasing and the number of users is constantly getting larger, the performance of the above algorithms may degrade seriously, so the AI signal detection algorithm is a good alternative, which learns autonomously through deep neural networks, including model-driven and data-driven schemes.

Modulation detection techniques have received much attention in recent years due to their importance in the military and commercial applications, such as software-defined radio and cognitive radios. Most of the existing modulation detection algorithms address the detection dedicated to the non-cooperative systems only. In this work, we propose the detection of modulations in the multi-relay cooperative multiple-input multiple-output (MIMO) systems for 5G communications in the presence of spatially correlated channels and imperfect channel state information (CSI). At the destination node, we extract the higher-order statistics of the received signals as the discriminating features. After applying the principal component analysis technique, we carry out a comparative study between the random committee and the AdaBoost machine learning techniques (MLTs) at low signal-to-noise ratio. The efficiency metrics, including the true positive rate, false positive rate, precision, recall, F-Measure, and the time taken to build the model, are used for the performance comparison. The simulation results show that the use of the random committee MLT, compared to the AdaBoost MLT, provides gain in terms of both the modulation detection and complexity.

In recent years Multiple-input multiple-output (MIMO) Multi carrier code division multiple access (MCCDMA), which combines the advantage of diversities with high spectral efficiency has drawn great attention. In this paper we introduce a novel low-complexity multiple-input multiple-output (MIMO) MMSE detector tailored for MCDCDMA systems, suitable for frequency selective channel. The proposed detector begins with estimation of the minimum mean square error (MMSE) on less reliable symbols followed by iterative de-correlation as post-detection processing for mitigating multiple access interferences. Efficient high-throughput VLSI architecture is used to achieve superior performance compared to the conventional MMSE detectors. The performance of the proposed MMSE detector is close to the efficient maximum likelihood, with significant complexity reduction over higher order constellations. The efficiency of MIMO MCCDMA over high order constellations and its quality retentions are verified through MATLAB BER simulation.

As a key candidate technique for fifth-generation (5G) mobile communication systems, non-orthogonal multiple access (NOMA) has attracted considerable attention in the field of wireless communication. Successive interference cancellation (SIC) is the main NOMA detection method applied at receivers for both uplink and downlink NOMA transmissions. However, SIC is limited by the receiver complex and error propagation problems. Toward this end, we explore a high-performance, high-efficiency tool—deep learning (DL). In this paper, we propose a learning method that automatically analyzes the channel state information (CSI) of the communication system and detects the original transmit sequences. In contrast to existing SIC schemes, which must search for the optimal order of the channel gain and remove the signal with higher power allocation factor while detecting a signal with a lower power allocation factor, the proposed deep learning method can combine the channel estimation process with recovery of the desired signal suffering from channel distortion and multiuser signal superposition. Extensive performance simulations were conducted for the proposed MIMO-NOMA-DL system, and the results were compared with those of the conventional SIC method. According to our simulation results, the deep learning method can successfully address channel impairment and achieve good detection performance. In contrast to implementing well-designed detection algorithms, MIMO-NOMA-DL searches for the optimal solution via a neural network (NN). Consequently, deep learning is a powerful and effective tool for NOMA signal detection.

Radar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we employ a low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) imaging radar and derive the relationship between radar images and vibrations caused by human cardiopulmonary movements. The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars. We also apply the three-dimensional (3-D) higher-order cumulant (HOC) to locate multiple subjects and extract the phase sequence of the radar images as the vital signs signal. To monitor the cardiopulmonary activities, we further exploit the VMD algorithm with a proposed grouping criterion to adaptively separate the respiration and heartbeat patterns. A series of experiments have validated the localization and detection of multiple subjects behind a wall. The VMD algorithm is suitable for separating the weaker heartbeat pattern from the stronger respiration pattern by the grouping criterion. Moreover, the continuous monitoring of heart rate (HR) by the MIMO radar in real scenarios shows a strong consistency with the reference electrocardiogram (ECG).

This study explores the problem of maximizing the sum rate in uplink multi-user Multiple-Input Multiple-Output (MIMO) using Rate-Splitting Multiple Access (RSMA) systems. The investigation revolves around the scenario where the Users (UEs) are single-antenna nodes transmitting data to a multi-antenna Base Station (BS) through the RSMA technique. The optimization process encompasses determining parameters such as UEs’ transmit powers, decoding order, and detection vector at the BS. An approach based on Deep Reinforcement Learning (DRL) is introduced to address this challenge. This DRL framework involves an action-refined stage and applies a Deep Deterministic Policy Gradient (DDPG)-based strategy. Simulation outcomes effectively demonstrate the convergence of the proposed DRL framework, where it converges after approximately 1,800 episodes. Also, the results prove the superior performance of the proposed method when compared to established benchmark strategies, where it is up to 45% and 86% higher than the local search and random schemes, respectively.

Interferometric radars are widely used for monitoring civil structures. Bridges are critical structures that need to be constantly monitored for the safety of the users. In this work, a frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) radar was used for monitoring an arched bridge in Catanzaro, Italy. Two measurements were carried out; a first standard measurement was made in a monostatic configuration, while a subsequent measurement was carried out in a multimonostatic configuration in order to retrieve the components of the deck displacement. A method that is able to predict the measurement uncertainty as a function of the multimonostatic geometry is provided, thereby aiming to facilitate the operators in the choice of the proper experimental setup. The multimonostatic measurement revealed a displacement along the horizontal direction that was four times higher than the one along the vertical direction, while the values reported in the literature correspond to a ratio of at most around 0.2. This is the first time that such a large ratio detected by radar has been reported; at any rate, it is compatible with the arched structure of this specific bridge. This case study highlights the importance of techniques that are able to retrieve at least two components of the displacement.

PurposeA recent innovative technology used in wireless communication is recognized as multiple input multiple output (MIMO) communication system and became popular for quicker data transmission speed. This technology is being examined and implemented for the latest broadband wireless connectivity networks. Though high-capacity wireless channel is identified, there is still requirement of better techniques to get increased data transmission speed with acceptable reliability. There are two types of systems comprising of multi-antennas placed at transmitting and receiving sides, of which first is diversity technique and another is spatial multiplexing method. By making use of these diversity techniques, the reliability of transmitting signal can be improved. The fundamental method of the diversity is to transform wireless channel such as Rayleigh fading into steady additive white Gaussian noise (AWGN) channel which is devoid of any disastrous fading of the signal. The maximum transmission speed that can be achieved by spatial multiplexing methods is nearly equal to channel capacity of MIMO. Conversely, for diversity methods, the maximum speed of broadcasting is much lower than channel capacity of MIMO. With the advent of space–time block coding (STBC) antenna diversity technique, higher-speed data transmission is achievable for spatially multiplexed multiple input multiple output (SM-MIMO) system. At the receiving end, detection of the signal is a complex task for system which exhibits SM-MIMO. Additionally, a link modification method is implemented to decide appropriate coding and modulation scheme such as space diversity technique STBC to use two-way radio resources efficiently. The proposed work attempts to improve detection of signal at receiving end by employing STBC diversity technique for linear detection methods such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC) and maximum likelihood detection (MLD). The performance of MLD has been found to be better than other detection techniques.Design/methodology/approachAlamouti's STBC uses two transmit antennas regardless of the number of receiver antennas. The encoding and decoding operation of STBC is shown in the earlier cited diagram. In the following matrix, the rows of each coding scheme represent a different time instant, while the columns represent the transmitted symbols through each different antenna. In this case, the first and second rows represent the transmission at the first and second time instant, respectively. At a time t, the symbol s1 and symbol s2 are transmitted from antenna 1 and antenna 2, respectively. Assuming that each symbol has duration T, then at time t + T, the symbols –s2* and s1*, where (.)* denotes the complex conjugate, are transmitted from antenna 1 and antenna 2, respectively. Case of one receiver antenna: The reception and decoding of the signal depend on the number of receiver antennas available. For the case of one receiver antenna, the received signals are received at antenna 1 , hij is the channel transfer function from the jth transmit antenna and the ith receiver antenna, n1 is a complex random variable representing noise at antenna 1 and x (k) denotes x at time instant k ( at time t + (k – 1)T.FindingsThe results obtained for maximal ratio combining (MRC) with 1 × 4 scheme show that the BER curve drops to 10–4 for signal-to-noise (SNR) ratio of 10 dB, whereas for MRC 1 × 2 scheme, the BER drops down to 10–5 for SNR of 20 dB. Results obtained in Table 1 show that when STBC is employed for MRC with 1 × 2 scheme (one antenna at transmitter node and two antennas at receiver node), BER curve comes down to 0.0076 for Eb/N0 of 12. Similarly, when MRC with 1 × 4 antenna scheme is implemented, BER drops down to 0 for Eb/N0 of 12. Thus, it can be concluded from the obtained graph that the performance of MRC with STBC gives improved results. When STBC technique is used with 3 × 4 scheme, at SNR of 10 dB, BER comes nearer to 10–6 (figure 7.3). It can be concluded from the analytics observed between AWGN and Rayleigh fading channel that for AWGN channel, BER is found to be equal to 0 for SNR value of 13.5 dB, whereas for Rayleigh fading channel, BER is observed nearer to 10–3 for Eb/N0 = 15. Simulation results (in figure 7.2) from the analytics show BER drops to 0 for SNR value of 12 dB.Research limitations/implicationsOptimal design and successful deployment of high-performance wireless networks present a number of technical challenges. These include regulatory limits on useable radio-frequency spectrum and a complex time-varying propagation environment affected by fading and multipath. The effect of multipath fading in wireless systems can be reduced by using antenna diversity. Previous studies show the performance of transmit diversity with narrowband signals using linear equalization, decision feedback equalization, maximum likelihood sequence estimation (MLSE) and spread spectrum signals using a RAKE receiver. The available IC techniques compatible with STBC schemes at transmission require multiple antennas at the receiver. However, if this not a strong constraint at the base station level, it remains a challenge at the handset level due to cost and size limitation. For this reason, SAIC technique, alternative to complex ML multiuser demodulation technique, is still of interest for 4G wireless networks using the MIMO technology and STBC in particular. In a system with characteristics similar to the North American Digital mobile radio standard IS-54 (24.3 K symbols per sec. with an 81 Hz fading rate), adaptive retransmission with time deviation is not practical.Practical implicationsThe evaluation of performance in terms of bit error rate and convergence time which estimates that MLD technique outperforms in terms of received SNR and low decoding complexity. MLD technique performs well but when higher number of antennas are used, it requires more computational time and thereby resulting in increased hardware complexity. When MRC scheme is implemented for singe input single output (SISO) system, BER drops down to 10–2 for SNR of 20 dB. Therefore, when MIMO systems are employed for MRC scheme, improved results based on BER versus SNR are obtained and are used for detecting the signal; comparative study based on different techniques is done. Initially ZF detection method is utilized which was then modified to ZF with successive interference cancellation (ZFSIC). When successive interference cancellation scheme is employed for ZFSIC, better performance is observed as compared to the estimation of ML and MMSE. For 2 × 2 scheme with QPSK modulation method, ZFSIC requires more computational time as compared to ZF, MMSE and ML technique. From the obtained results, the conclusion is that ZFSIC gives the improved results as compared to ZF in terms of BER ratio. ZF-based decision statistics can be produced by the detection algorithm for a desired sub-stream from the received vector whichs consist of an interference which occurred from previous transmitted sub-streams. Consequently, a decision on the secondary stream is made and contribution of the noise is regenerated and subtracted from the vector received. With no involvement of interference cancellation, system performance gets reduced but computational cost is saved. While using cancellation, as H is deflated, coefficients of MMSE are recalculated at each iteration. When cancellation is not involved, the computation of MMSE coefficients is done only once, because of H remaining unchanged. For MMSE 4 × 4 BPSK scheme, bit error rate of 10–2 at 30 dB is observed. In general, the most thorough procedure of the detection algorithm is the computation of the MMSE coefficients. Complexity arises in the calculation of the MMSE coefficients, when the antennas at the transmitting side are increased. However, while implementing adaptive MMSE receivers on slow channel fading, it is probable to recover the signal with the complications being linear in the antennas of transmitter node. The performance of MMSE and successive interference cancellation of MMSE are observed for 2 × 2 and 4 × 4 BPSK and QPSK modulation schemes. The drawback of MMSE SIC scheme is that the first detected signal observes the noise interference from (NT-1) signals, while signals processed from every antenna later observe less noisy interference as the process of cancellation progresses. This difficulty could be overcome by using OSIC detection method which uses successive ordering of the processed layers in the decreasing power of the signal or by power allocation to the signal transmitted depending on the order of the processing. By using successive scheme, a computation of NT delay stages is desired to bring out the abandoned process. The work also includes comparison of BER with various modulation schemes and number of antennas involved while evaluating the performance. MLD determines the Euclidean distance among the vector signal received and result of all probable transmitted vector signals with the specified channel H and finds the one with the minimum distance. Estimated results show that higher order of the diversity is observed by employing more antennas at both the receiving and transmitting ends. MLD with 8 × 8 binary phase shift keying (BPSK) scheme offers bit error rate near to 10–4 for SNR (16 dB). By using Altamonti space ti.Social implicationsIt should come as no surprise that companies everywhere are pushing to get products to market faster. Missing a market window or a design cycle can be a major setback in a competitive environment. It should be equally clear that this pressure is coming at the same time that companies are pushing towards “leaner” organizations that can do more with less. The trends mentioned earlier are not well supported by current test and measurement equipment, given this increasingly high-pressure design environment: in order to measure signals across multiple domains, multiple pieces of measurement equipment are needed, increasing capital or rental expenses. The methods available for making cross-domain, time-correlated measurements are inefficient, reducing engineering efficiency. When only used on occasion, the learning curve to understand how to use equipment for logic analysis, time domain and RF spectrum measurements often requires an operator to re-learn each piece of separate equipment. The equipment needed to measure wide bandwidth, time-varying spectral signals is expensive, again increasing capital or rental expenses. What is needed is a measurement instrument with a common user interface that integrates multiple measurement capabilities into a single cost-effective tool that can efficiently measure signals in the current wide-bandwidth, time-correlated, cross-domain environments. The market of wireless communication using STBCs has large scope of expansion in India. Therefore, the proposed work has techno-commercial potential and the product can be patented. This project shall in turn be helpful for remote areas of the nearby region particularly in Gadchiroli district and Melghat Tiger reserve project of Amravati district, Nagjira and so on where electricity is not available and there is an all the time problem of coverage in getting the network. In some regions where electricity is available, the shortage is such that they cannot use it for peak hours. In such cases, stand-alone space diversity technique, STBC shall help them to meet their requirements in making connection during coverage problem, thereby giving higher data transmission rates with better QOS (quality of service) with least dropped connections. This trend towards wireless everywhere is causing a profound change in the responsibilities of embedded designers as they struggle to incorporate unfamiliar RF technology into their designs. Embedded designers frequently find themselves needing to solve problems without the proper equipment needed to perform the tasks.Originality/valueWork is original.

With the rapid development of wireless sensor networks (WSNs) technology, a growing number of applications and services need to acquire the states of channels or sensors, especially in order to use these states for monitoring, object tracking, motion detection, etc. A critical issue in WSNs is the ability to estimate the source parameters from the readings of a distributed sensor network. Although there are several studies on channel estimation (CE) algorithms, existing algorithms are all flawed with their high complexity, inability to scale, inability to ensure the convergence to a local optimum, low speed of convergence, etc. In this work, we turn to variational inference (VI) with tempering to solve the channel estimation problem due to its ability to reduce complexity, ability to generalize and scale, and guarantee of local optimum. To the best of our knowledge we are the first to use VI with tempering for advanced channel estimation. The parameters that we consider in the channel estimation problem include pilot signal and channel coefficients, assuming there is orthogonal access between different sensors (or users) and the data fusion center (or receiving center). By formulating the channel estimation problem into a probabilistic graphical model, the proposed Channel Estimation Variational Tempering Inference (CEVTI) approach can estimate the channel coefficient and the transmitted signal in a low-complexity manner while guaranteeing convergence. CEVTI can find out the optimal hyper-parameters of channels with fast convergence rate, and can be applied to the case of code division multiple access (CDMA) and uplink massive multi-input-multi-output (MIMO) easily. Simulations show that CEVTI has higher accuracy than state-of-the-art algorithms under different noise variance and signal-to-noise ratio. Furthermore, the results show that the more parameters are considered in each iteration, the faster the convergence rate and the lower the non-degenerate bit error rate with CEVTI. Analysis shows that CEVTI has satisfying computational complexity, and guarantees a better local optimum. Therefore, the main contribution of the paper is the development of a new efficient, simple and reliable algorithm for channel estimation in WSNs.

Soft rot causing Fusarium oxysporum is one of the most destructive diseases of Dendrobium officinale Kimura et Migo in China that reduces D. officinale yield and quality. A key challenge for an integrated management strategy for this disease is the rapid and accurate detection of F. oxysporum on D. officinale. Therefore, a new loop-mediated isothermal amplification (LAMP) assay was developed for this purpose. In this study, the primers were selected and designed using the translation elongation factor-1α (TEF-1α) gene region as the target DNA sequence in order to screen the best system of reaction of LAMP to detect F. oxysporum through optimizing different conditions of the LAMP reaction, including time, temperature, concentrations of MgSO4, and concentrations of inner and outer primers. The optimized system was able to efficiently amplify the target gene at 62 °C for 60 min with 1.2 μM internal primers, 0.4 μM external primers, 7 mM Mg2+, and 5 fg/µL minimum detection concentration of DNA for F. oxysporum. The amplified products could be detected with the naked eye after completion of the reaction with SYBR green I. We were better able to control the effect of soft rot in D. officinale using fungicides following a positive test result. Additionally, the control effect of synergism combinations against soft rot was higher than 75%. Thus, LAMP assays could detect F. oxysporum in infected tissues of D. officinale and soils in field, allowing for early diagnosis of the disease.

In Multiple Input Multiple Output (MIMO) systems, the complexities of detectors depend on the size of the channel matrix. In Massive MIMO systems, detection complexity becomes remarkably higher because the dimensions of the channel matrix get much larger. In order to recover the signals in the up-link of a Massive MIMO system at reduced complexities, we first divide the system into two sub-systems. After that, we apply the Minimum Mean Square Error (MMSE) and Bell Laboratory Layer Space Time (BLAST) detectors to each subsystem, resulting in the so-called MMSE-GD and BLAST-GD detectors, respectively. To further enhance the BER performance of Massive MIMO systems under the high-load conditions, we propose two additional detectors, called MMSE-IGD and BLAST-IGD by respectively applying the conventional MMSE and BLAST on the sub-systems in an iterative manner. It is shown via computer simulation and analytical results that the proposed detectors enable the system to achieve not only higher BER performance but also low detection complexities as compared to the conventional linear detectors. Moreover, the MMSE-IGD and BLAST-IGD can significantly improve BER performance of Massive MIMO systems.

Recent research shows that multiple antenna at both transmitter and receiver offers higher data rates compared to single antenna system. The information-theoretical capacity of MIMO grows linearly with the smaller of transmit and receive antenna in rich scattering environment with sufficient high SNR. In this paper, V-BLAST and maximum a-posteriori (MAP) is used improve the performance of the MIMO system. The original V-BLAST algorithm is a multi-layer symbol detection scheme, which detects symbols transmitted at different transmit antennas successively in a certain dataindependent order. The proposed V-BLAST-MAP algorithm differs from V-BLAST only in the ordering strategy of the symbols detected. The complexity of the V-BLAST-MAP is higher than that of V-BLAST. The performance improvement is also significant. In this paper, MATLAB Based simulation result are discussed .

Purpose In order to optimize BER and to substantiate performance measures, initially, the filter bank multicarrier (FBMC) quadrature amplitude modulation (QAM) performance metrics are evaluated with the cyclic prefix-orthogonal frequency division multiplexing (CP-OFDM) system. The efficiency of CP-OFDM, as well as FBMC/QAM that is transmitting over specific fading channels, is evaluated in terms of quality trade-off metrics over bit error rate (BER) as well as modulation order. When compared with the traditional FBMC systems, the proposed FBMC QAM system shows better performance. The performance metrics of FBMC/QAM with the inclusion of multiuser multiple-input-multiple-output (MUMIMO) is validated with worst case channel environment. The performance penalty gap that exists in CP- OFDM is compared with improved FBMC QAM in terms of both BER and OOB radiation measures. The BER trade off comparison between ML and MMSE optimally determine the prominent signal detection model for high performance FBMC QAM system. Design/methodology/approach The main objective of this research work is to provide perceptions about performance, co-channel interference avoidance as well as about the techniques that are used for minimizing the complexity of the system that is related to FBMC QAM structure for reducing intrinsic interference with higher spectral features as well as maximal likelihood (ML) detector systems. Findings This research work also looks at the efficiency of multiuser multiple-input-multiple-output (MU-MIMO) FBMC/QAM over nonlinear channels. Furthermore, when compared with OFDM, it also significantly reduces the penalty gap efficiency, thereby enabling the accessibility of the proposed FBMC QAM system from BER as well as implementation point of view. Finally, the signal detection is facilitated by the sub-detector and is achieved on the downlink side by making use of threshold-driven statistical measures that accurately minimize the complexity trade-off measures of the ML detector over modulation order. The computation of the proposed FBMC method’s BER performance measures was carried out through MATLAB simulation environments, as well as efficiency of the suggested work was demonstrated through detailed analyses. Originality/value This research work intend to combine the efficient MU-MIMO based transmission scheme with optimal FBMC/QAM for improved QoS over highly nonlinear channels which includes both delay spread and Doppler effects. And optimal signal detection model is facilitated at the downlink side by making use of threshold-driven statistical measures that accurately minimize the complexity trade-off measures of the ML detector over modulation order. The computation of the proposed FBMC method’s BER performance measures was carried out through MATLAB simulation environments, as well as efficiency of the suggested work was demonstrated through detailed analyses.

This paper presents the multiple-input multiple-output Interleave division multiple access (MIMO-IDMA) system with dual polarized division multiplexing (DPDM). Dual polarized antenna system replaces the uni-polarized antenna system availing cost and space features. We have considered dual- Polarized antennas at both the transmitter and the receiver ends to establish DPDM. For the purpose of accommodation, the users are separated with userspecific interleaver in combination with a low rate spreading sequence. In the receiver, we consider the minimum mean square error (MMSE) algorithm based successive interference cancellation (SIC) Multi-user detection (MUD) technique to diminish the effects of multi-stream interference (MSI). Furthermore, we implement Log-maximum a posteriori probability (MAPP) decoding algorithm at the mobile stations (MSs) to alleviate the effects of multi-user interference (MUI).We evaluate the effects of codedMIMO-IDMA system in the context of downlink (DL) communication pertaining to the Stanford University Interim (SUI) and Long-term Evolution (LTE) channel model specifications.We observe that our simulation results considered turbo coded Dual-PolarizedMIMO-IDMAsystem with iterative decoding algorithm provides a better bit error rate (BER) performance with less signal to noise ratio (SNR) when compared to uncoded system. Furthermore our simulation results show that MIMO-IDMA system with Dual-Polarized antenna requires higher SNR than uni-polarized antennas in order to achieve same BER. However, it provides the advantage of replacing two uni-polarized antennas by a single Dual-Polarized antenna which can therefore help achievement of a higher data rate with a reduced size of MS in the context of DL transmission.

In order to improve the communication performance between different equipment in the seismic detection system, a wireless network system with MIMO (Multiple Input and Multiple Output) characteristics was designed and applied in the paper. On the basis of 5G communication, a new data conversion and transmission model was built, which can improve the rate of signal transmission and reduce the bit error rate and power consumption. For the purpose of power optimization, the overall framework of the network system was improved, of which power characteristics and performance were verified. The conjugate beam was normalized, and the cumulative distribution function under different downlink rates was obtained based on the maximum minimum power control scheme. In order to verify the energy-saving effect of the design, the ADC (Analog-to-Digital Conversion) power model is introduced. Through simulation analysis, the change rules of spectrum efficiency and energy efficiency under different network nodes were obtained. The results show that the normalized conjugate beam can be less affected by the transmission nodes, and the power control is more reliable under the same conditions. The research and application of this subject can significantly improve the wireless communication performance of the seismic monitoring system, reduce the power consumption of network equipment, improve the data transmission efficiency, and provide strong technical support for seismic prediction and data analysis. Through the test of artificial earthquake, it is verified that the communication scheme designed in this paper has higher transmission efficiency and lower bit error rate, and is very suitable for the long-distance transmission of seismic signals.