International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 12 Issue: 05 | May 2025 www.irjet.net p-ISSN:2395-0072
Successive Interference Cancellation-based Channel Estimation for FullDuplex Systems
H.Raseena Barwin 1 , Dr.Geetha M.R , 2 , R.Rathi3 , N.K.Arul raj4
1PG Scholar, Communication and networking, Ponjesly college of engineeringy, Kanyakumari.
2Professor Electronics & Communication department, Ponjesly college of engineering, Kanyakumari
3Assistant Professor Electronics & Communication department, Ponjesly college of engineering, Kanyakumari.
4 Assistant Professor Electronics & Communication department, Ponjesly college of engineering, Kanyakumari ***
Abstract - A possible method for fusing sensing and communication capabilities to transmit data and detect the physical environment at the same time is the integrated sensing and communications (ISAC) system. It nevertheless need sustainable high-data transmission with effective spectrum usage, even though its goal is to comprehend the communication environment and channel situation with sensing capabilities. Increasing spectrum efficiency while supporting high data transmission may be feasible with the in-band full-duplex (IBFD) system. We must look into potential methods to address IBFD's self interference problem, which is one of the major causes that degrades its performance. In this research, we propose an enhanced selfimpedance cancellation receiver for the IBFD system that uses channel estimates based on successive interference cancellation (SIC). Our suggested approach incorporated SIC to the channel estimation for the performance gain since it seeks to reduce the effects of various interferences. Our findings demonstrate that the IBFD bit error rate (BER) of the new radio (NR) for the ISAC system is enhanced by SI cancellation combined with SIC-based channelestimation.
KeyWords: Channel estimation, in-band full-duplex (IBFD),integratedsensinginterference(SI)cancellation (SIC). and communications (ISAC), self-cancellation, successiveinterference
1. INTRODUCTION
Acommunicationsystem'sprimarygoalistotransferdata in an adequate and dependable way. The development of cellular communication and heavily data-driven services has altered this perception. Wireless communication systemsshouldhavemorefunctionsandusesbeyondonly datatransport,asdemonstratedbytherecentrolloutof5G and the technical roadmap for 5G and 6G [1]. Numerous communication and signal processing strategies could be includedinnewwirelesscommunicationsystemssince5G
and6Gareonthehorizon.Thein-bandfull-duplex(IBFD) technology receives a lot of interest and is a promising design. With simultaneous transmission and reception on thesamefrequencyrange,thistechnologycansignificantly improve spectral efficiency. Numerous applications and interests, such as network capacity and throughput, bidirectional communication delay, spectrum utilization, relay network performance, and effective cognitive radio systems, can also be greatly enhanced by the IBFD. Given its importance, IBFD may be a crucial enabler for new applications like Integrated Sensing and Communications (ISAC) systems, which seek to accomplish data transmissionandsensingatthesametime[2].
IBFD can enable simultaneous environmental sensing and high-speed data transfer for vehicle localization and high datatransmissioninISACscenarios,includingautonomous driving, increasing system efficiency overall [2], [3]. Even though the IBFD system can solve a number of problems and use all of its capacity by transmitting and receiving simultaneously,thetransmitsignal'shighself-interference power leads to the IBFD system's low signal-tointerference-plus-noise ratio (SINR), which severely impairs receiver performance [4]. IBFD systems in multiple mobility devices can cause these specific low SINRissuesbydoublingmultipleinterferencesignalswith significant high-power presence on the spectrum, as illustratedinFig.1.Thisisespeciallytrueinamobilityasa service (MaaS) scenario where multiple small mobility devices are present in indoororurban environments. The low SINR scenario at the IBFD system was mitigated by a number of remedies. Self-interference (SI) cancellation strategies have been proposed to improve SINR in the IBFD system, particularly in light of the low SINR of the data symbols produced by the transmit signal's selfinterference [5]–[7]. Using a variety of techniques, the literature now in publication also suggests potential fixes fortheIBFDsystemandself-interferencecancellation.One
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 12 Issue: 05 | May 2025 www.irjet.net p-ISSN:2395-0072
antenna can be used for both transmit and receive, for example, by shifting the phase angle at the antenna for self-interference cancellation using the analog circuit technique with balanced feed networks [8]. Learning approaches using convolutional neu ral network (CNN) and simple neural networks were also proposed to minimize self-interference and noises in inter tower communication[9],[10].
Possible mobility-as-a-service scenario with multiple IBFD-equipped mobility devices
2.METHODOLOGIES
A system type that combines IBFD communication methods, which have been popular recently, with an NR system. IBFD systems are capable of simultaneous signal transmission and reception at the same time and frequency resources. The forms of IBFD can be separated into two categories based on the antenna connection method used between the transmit and receive radio frequency (RF) chains: antenna sharing and antenna separation. A circuit is needed to segregate the sent and received signals when using this antenna-sharing technique.Byusingfilteringtechnologieslikeaduplexer,it was feasible to differentiate between a transmitted signal and a received signal in an antenna-sharing approach in the traditional frequency division duplexing (FDD)-based communication system. However, the conventional duplexer device cannot differentiate between the broadcast and received signals due to the IBFD's simultaneous transmission and reception in the same frequencyband,necessitatingtheSIcancellationapproach. The antenna-sharing method's IBFD can be configured using a circulator with three input/output ports, as illustrated in Fig. 2. The circulator element in the radar system limits the send signal's direct f low from the transmit RF chain to the receive RF chain. Therefore, this systemcanrestricttheflowofthetransmissionsignalinto the reception RF chain when it is applied to the IBFD system of the antenna-sharing technique employing this
circulator characteristic. But compared to the ideal situation, the typical circulator's performance is significantlyworse.
Therearevariousoperationalandperformancebenefitsto UL and DL time alignment. When UL and DL timings are aligned bytimingadvance,some base stationsarealready deployed in real deployments. As a result, we looked into SIC-basedchannel estimationforanISAC systeminanNR system under time-aligned conditions. In an existing NR system, it is common for UL and DL DMRS to employ distinctsymboltimeshiftvaluesinordertopreventDMRS collisions. For improved channel estimation quality, our approach suggested aligning the DMRS positions with the SIC-based channel estimate at the same symbol time. The DMRSs of UL and DL are received in the same resource element under these circumstances. Therefore, it is plausible to assume that only additive white Gaussian noise (AWGN) and DMRSs from UL and DL exist in that particularresourceelement.
2.1 Receiver Structure
The receiver calculates the block, noise, and channel responses after a fast Fourier transform (FFT). The receiver uses SIC-based channel estimation and SI cancellationtoreducetheSI.Thereceiveralsodecodesthe signal in a Decoding & De-rate matching block after demodulating it in a MIMO processing & Demodulation block.IftheSIincludedintheDMRSisreducedbySIC,the receiver can obtain an accurate channel estimate because the SI cancellation performance is heavily reliant on the accuracy of the channel estimation. Accurate channel estimate can significantly enhance SI cancelation performance.
2.2 Channel Estimation
The block for channel estimation. Channel estimation consists of cross-producting the received signal and the
Fig 1:
Fig 1: IBFD System with RF chain by antenna sharing.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 12 Issue: 05 | May 2025 www.irjet.net p-ISSN:2395-0072
reference signal (RS), frequency filtering, and interpolation. 1) Mapping to physical resource of DMRS: The UE shall assume the DMRS being mapped to physical resources according to configuration type 1. The UE shall assumetheRSsequence��(��)isscaledbya factor ���������� to conform with the transmission power specified, where ���������� = 1 is assumed. Mapped to resource elements �� (��,) located in the ��th frequency domain and ��th time domainaccordingto
where��=4��+2��′+Δ,Δ=0,1,��′=0,1,��=0,1,·,��/2,and�� isthenumberofsubcarriers.
2.3 Encryption by MSNs
Medical Sensor Nodes (MSNs) are crucial for encrypting sensitivehealthdata usingtheir Partial Private Key.Using a pairing-free approach makes the encryption process more efficient and less demanding on the limited CPU capabilities of the MSNs. The encrypted data, also known asciphertext,isprotectedfromunauthorizedaccesswhile it is being transmitted. Health information is kept confidentialacrossthenetworkandanysecuritybreaches are prevented by encrypting data. As explained in the preceding section, the channel response for the resource block is approximated by merely extracting the RS from the received signal in accordance with a predetermined standard. Depending on the delay profile, an estimate of the number of RSs used on each side of the RS must be made.
2.3 Successive Interference Cancellation
In communication systems, SIC is used, especially when there is interference from several transmissions. SIC's main objective is to lessen the effects of interference and enhance system performance generally, particularly in situations where signals may overlap like in wireless communication. Several signals are sent across the same channel or frequency spectrum in a communication system.Thequalityofthereceivedsignalsmaydeteriorate as a result of these signals interfering with one another. The receiver receives the incoming signals, which include both the desired signal and interfering signals. Usually, these signals are received in a specific priority or order. Decoding or demodulating the signal with the highest priority, typically based on the SINR or decoding complexity levels, is the first step in the interference cancellation process. The whole received signal is then reducedoreliminatedbythedecodedsignal.Theprevious step is repeated. The remaining signals are processed in
the same way after the initial signal has been cancelled. This process keeps going until either a predetermined threshold is met or all of the major interference has been eliminated. The remaining signals, which now have less interference as a result of the sequential cancellation process, have finished their final decoding. When dealing withsituationswheretheinterferencepatternisknownor the signals have different intensities, SIC works well. It takes advantage of the fact that not all signals interfere withoneanotherinthesameway.Thesubsequentsignals can be deciphered more precisely if the more prevalent interference is eliminated first. While SIC can significantly improvetheperformanceofcommunicationsystemsinthe presence of interference, it is essential to note that it introduces complexity to the receiver, especially in terms of processing power and latency. The success of SIC depends on the accuracy of interference estimation and theorderinwhichsignalsareprocessed.
2.5 Proposed SIC-based Channel Estimation
The overall channel estimation is composed of multiple channel estimations and SICs from Step 1 to Step 2 as follows:
Step 1: A variable m, indicating the number of performed iterationsisinitializedtozero.
Step2:Thereceiverdeterminesthesignalwithastronger channel response between a desired signal and a SI. After operating ��-point FFT, the receiver composes the m-th estimated channel response ˆ ��(��) �� (��) of the desired signal and ˆ ��(��) �� of the transmit self-interference signal as (2)
where LPF(·) is a low pass filter used for a component channel estimation, ��(��) is the frequency domain representation of the received signal ��(��), and ����(��) and ����(��)aretheDMRSsofthedesiredsignalandthetransmit self-interferencesignal,respectively.
2.5 SI Cancellation
SI cancellation calculates the interference value by multiplyingthefinal estimatedchannel responseobtained bySICwiththetransmittedsignalinthefrequencydomain known to the receiver instead of the reference signal, and the received signal ˜ ����(��)with this value removed is obtainedas
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 12 Issue: 05 | May 2025 www.irjet.net p-ISSN:2395-0072
RESULT AND DISCUSSION
We present simulation results with the suggested SI cancellation receiver employing SIC-based channel estimation, taking into account the system model and SI Cancellationfeatures.WeusedanNRlinklevelsimulatorin accordance with NR requirements to assess the SI cancellationreceiver'sperformanceinareal-worldsetting. We created the interference signal in our simulator by changingthecellIDinoneofitsblockstosendthedesired signal. This ID can then contain DMRS, including the difference sequence signal.After creating the interference signal, we added AWGN noise and constructed a system that broadcast both the target signal and the interference signal in each fading channel. The simulator uses a lowrate, low-density parity check code (LDPC) and QPSK modulation since the IBFD system gets a desired signal with a high SI. component channel estimation using finite impulse response (FIR) low pass filters in the frequency and time domains. The receiver uses transmit diversity modetosenddataandhastworeceiverantennas.3.5GHz is chosen as the transmission and reception center frequency. The receiver's speed settings are set to 0, 30, 60, and 90 km/h, correspondingly. Additionally, using the Extended Typical Urban model (ETU), we choose the four channels, including two route fading channels with delays of1and5����
Fig.3. MSE performance comparison of conventional channel estimation and proposed SIC-based channel estimation in an one path Rayleigh fading channel.
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As shown in Fig.3, the MSE performance of the SIC-based channel estimation under one Rayleigh fading case is about 1/14 of the conventional channel estimation performanceat−4dBSINR.Also,weobservethattheMSE oftheSIC-basedcasepreservesunder0.1.Thisshowsthat SIC can mitigate substantial damages caused by one-path fadingchannel.
In Fig.4, the MSE performance of the SIC-based channel estimation is about one-third of the conventional channel estimation performance at −4 dB SINR. Also, the result showed that the MSE correction of SIC is worse than one path fading channel because the MSE of the conventional casedoesnotreducewelloverSINRcomparedtoonepath fading case. It indicates that SIC can improve different types of fading channel cases, but the improvement result depends on the types of fading channels and environments.
| Page1050 (3) by repeating this operation several times, the SIC method can remove much of the interference. However, as described in the previous section, the trade-off between performance and complexity depends on the number of componentICUsusedfortheoverallSIcancellation.
Fig 4: MSE performance comparison of conventional channel estimation and proposed SIC-based channel estimation in an equal-gain two path Rayleigh fading channel with 1 ���� tap delay login page.
CONCLUSION
A channel estimation technique for self-interference in an IBFD system based on SIC. In order to improve the estimation of the low-powered signal, this method recursively evaluated the channel response of the desired signalandSIcomponent,graduallycancelingoutthehighpowered signal at eachiteration. Our suggested SIC-based channel estimating approach considerably enhanced the MSE performance for the fading channel models resemblingEPAandRayleighchannelsbyupto5Dbwhen compared to traditional methods. To further validate its efficacyinreal-worldscenarios,suchascellularnetworks, cognitiveradiosystems,andautonomousdriving,wemust
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 12 Issue: 05 | May 2025 www.irjet.net p-ISSN:2395-0072
investigate the applicability and practicality of the SICbased estimation technique inparticularscenariosaswell as other self-interference cancellation techniques, not just ISAC systems. To create even more reliable and complete IBFD systems that can satisfy the many demands of nextgeneration wireless networks, we also need to look into the complexity analysis and improvement of this strategy withothercutting-edgesignalprocessingstrategies.
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