Multi-user cross-layer allocation design for LP-OFDM high-rate UWB

International audienceIn this paper, we investigate a cross-layer design for the packet scheduling and the resource allocation in UWB systems. This design considers the combination of queuing and channel state information (CSI) which provides QoS support for multimedia applications in UWB. For the physical layer, the use of a linear precoded orthogonal division multiplexing (LPOFDM) waveform is proposed because of its significant performance increase compared to the WiMedia proposal. For the medium access control layer, scheduling is performed in order to differentiate between the different users and to satisfy their quality of service constraints. This cross-layer approach optimizes the system spectral efficiency and solves the problem in the WiMedia solution of cohabitation of more than three users sharing the three sub-bands of the same channel. Simulation results show that the proposed scheme leads to a considerable improvement in resource allocation and can guarantee the required quality of service

딥러닝과 최적화를 활용한 무선 통신 시스템 설계

학위논문(박사) -- 서울대학교대학원 : 공과대학 전기·정보공학부, 2021.8. 캄포싸이.최근 5G 시스템의 등장으로 고신뢰 저지연 통신(ultra reliable low-latency communications, URLLC)과 대규모 사물 통신(massive machine-type communications, mMTC)이 주목을 받고 있다. 의료 서비스, 커넥티드 카, 로봇 공학, 제조업, 자유 시점 비디오 등 다양한 서비스들이 저지연 통신에서 예상되고, 이들은 1 ms 정도의 극도로 낮은 지연 시간을 요구한다. 한편, 대규모 사물 통신은 기지국에서 많은 기기(예를 들어 센서, 로봇, 자동차, 기계)의 방대한 연결성에 관한 것이다. 기존 통신 시스템(예를 들어 Long-Term Evolution (LTE))은 저지연 통신과 대규모 사물 통신의 요구 사항을 만족하기 어렵기에 이 통신 환경에 적합한 새로운 기술이 필요하다. 본 학위논문에서는 대규모 사물 통신과 저지연 통신을 위한 세 가지 기술을 제안한다. 논문의 첫 부분에서는 많은 기기가 비직교 확산 시퀀스를 사용해 기지국에 접속하는 대규모 사물 통신을 지원하는 딥러닝 기반의 확산 시퀀스 설계 및 활성 사용자 검출(active user detection, AUD) 방법을 제안한다. 검출 오류를 최소화하는 전체 통신 시스템을 설계하기 위해, 종단 간 심층 신경 네트워크(deep neural network, DNN)를 활용한다. 이 신경 네트워크에서 확산 네트워크는 송신기를 모델링하고 검출 네트워크는 활성 기기를 추정한다. 검출 오류를 손실 함수로 사용함으로써, 확산 시퀀스를 포함한 네트워크 변수들은 검출 오류를 최소화하도록 학습된다. 시뮬레이션 결과에서는 제안한 방법으로 얻어진 확산 시퀀스가 압축센싱 기반의 검출 기법과 제안한 검출 기법 모두에서 기존의 시퀀스보다 더 좋은 검출 성능을 달성하는 것을 보여준다. 논문의 두 번째 부분에서는 직교 주파수 분할 다중 방식(orthogonal frequency division multiplexing, OFDM) 시스템에서 프리코딩된 채널의 RMS (root mean square) 지연 확산을 줄이는 프리코딩 기법을 제안한다. OFDM 시스템에서 오버헤드를 증가시키지 않으면서 지연을 줄이기 위해서는 채널의 지연 확산과 그로 인한 CP (cyclic prefix)의 길이를 줄이는 것이 무엇보다 중요하다. 제안하는 기법에서는 RMS 지연 확산의 상한을 목적 함수로 하고 각 부반송파의 신호 대 잡음비를 제약조건으로 하는 최적화 문제를 설정한다. 최적화된 프리코딩을 찾을 수 있도록 원래 문제를 볼록 문제로 변환하기 위해 SDR (semi-definite relaxation) 기법을 사용한다. 시뮬레이션 결과에서는 제안한 프리코딩 설계가 특히 기지국에서 안테나의 수가 많을 때 RMS 지연 확산을 크게 줄이는 것을 보여준다. 논문의 마지막 부분에서는 저지연 OFDM 시스템에서 전송률 최대화를 위한 선형 프리코딩 설계를 다룬다. 저지연 통신에서 짧아지는 심볼 주기로 인한 CP의 오버헤드를 완화하기 위해 5G 무선 시스템은 짧은 CP를 사용할 필요가 있다. 채널의 지연 확산은 CP 길이보다 짧아야 하므로 먼저 실질적인 RMS 지연 확산과 달성 가능한 전송률을 제로 포싱 조건을 사용하여 유도한다. 다음으로 지연 확산 제약조건을 만족하는 전송률 최적화 문제를 사용자마다 정립하고 SDR 기법으로 해결 가능한 볼록 문제로 변환한다. 모든 사용자에 대해 최적화 문제를 푸는 것으로 전체 프리코딩 행렬을 얻는다. 시뮬레이션 결과에서는 제안한 기법이 작은 RMS 지연 확산과 함께 기존의 전송률 최적화보다 월등한 성능을 달성하는 것을 보여준다.With the advent of 5G wireless systems, ultra reliable low-latency communications (URLLC) and massive machine-type communications (mMTC) have recently attracted growing attention. Applications in health care, connected cars, robotics, manufacturing, and free-viewpoint video are expected in low-latency communications, and they demand extremely short round-trip latency levels as low as 1 ms. On the other hand, mMTC mainly concerns the massive connectivity of a large number of devices (e.g. sensors, robots, vehicles, and machines) to the base station (BS). Since conventional communications systems (e.g. Long-Term Evolution (LTE)) are difficult to meet the requirements of low-latency communications or mMTC, novel techniques suitable for these communications environments are required. This dissertation proposes three techniques for mMTC or low-latency communications. In the first part of the dissertation, we propose a deep learning-based spreading sequence design and active user detection (AUD) to support mMTC where a large number of devices access the base station using non-orthogonal spreading sequences. To design the whole communications system minimizing AUD error, we employ an end-to-end deep neural network (DNN) where the spreading network models the transmitter side and the AUD network estimates active devices. By using the AUD error as a loss function, network parameters including the spreading sequences are learned to minimize the AUD error. Numerical results reveal that the spreading sequences obtained from the proposed approach achieve higher AUD performance than the conventional spreading sequences in the compressive sensing-based AUD schemes, as well as in the proposed AUD scheme. In the second part of the dissertation, a precoding scheme to reduce the root mean square (RMS) delay spread of precoded channels in a orthogonal frequency division multiplexing (OFDM) system is proposed. In order to reduce latency in OFDM systems while not increasing the overhead, it is of primary importance to reduce the effective delay spread of the channel and thus the length of the cyclic prefix (CP). We formulate an optimization problem with an upper bound of the RMS delay spread as the objective function and a signal-to-noise ratio for each subcarrier as constraints. Semi-definite relaxation (SDR) technique is used to convert the problem into a convex problem so as to find the optimal precoding vector. Numerical results confirm that the proposed precoding design provides a significant reduction in the RMS delay spread, especially when there are a large number of antennas at the base station. In the last part of the dissertation, we addresses linear precoding design for sum rate maximization in low-latency OFDM systems. In order to mitigate the overhead of CP originating from shortened symbol duration for low-latency communications, 5G wireless systems need to adopt short CP lengths. As channel delay spread must be less than the CP length, we first derive the effective RMS delay spread and the achievable rate using the zero-forcing assumption. We construct a sum rate optimization problem for each user subject to delay spread constraints and then convert the problem into a solvable convex problem along with a SDR technique. The precoding matrix is finally obtained by solving optimization problems for all users. Numerical results reveal that the proposed scheme attains superior performance to the conventional sum rate optimization, as well as small RMS delay spread.1 INTRODUCTION 1 1.1 Deep Learning-based Spreading Sequence Design and Active User Detection for Massive Machine-Type Communications 2 1.2 Precoding Design for Cyclic Prefix Overhead Reduction in a MISO-OFDM System 5 1.3 Sum Rate Maximization with Shortened Cyclic Prefix in a MIMO-OFDM System 6 2 DEEP LEARNING-BASED SPREADING SEQUENCE DESIGN AND ACTIVE USER DETECTION FOR MASSIVE MACHINE-TYPE COMMUNICATIONS 8 2.1 System Model 8 2.2 DNN-based Spreading Sequence Design and Active User Detection 10 2.2.1 SN Architecture 13 2.2.2 AUDN Architecture 15 2.2.3 Operation 17 2.3 Numerical Results 18 2.3.1 Simulation Setup 18 2.3.2 Homogeneous Activities 19 2.3.3 Heterogeneous Activities 21 3 PRECODING DESIGN FOR CYCLIC PREFIX OVERHEAD REDUCTION IN A MISO-OFDM SYSTEM 26 3.1 System Model 26 3.2 Precoding Design 27 3.2.1 Effective RMS Delay Spread and SNR 28 3.2.2 Precoding Optimization 29 3.3 Numerical Results 31 4 SUM RATE MAXIMIZATION WITH SHORTENED CYCLIC PREFIX IN A MIMO-OFDM SYSTEM 37 4.1 System Model 37 4.2 Preliminaries for Precoding Design 38 4.2.1 Zero-Forcing Conditions 38 4.2.2 Effective RMS Delay Spread 40 4.2.3 Achievable Rate 41 4.3 Precoding Optimization 42 4.4 Numerical Results 43 5 CONCLUSION 53 5.1 Deep Learning-based Spreading Sequence Design and Active User Detection for Massive Machine-Type Communications 53 5.2 Precoding Design for Cyclic Prefix Overhead Reduction in a MISO-OFDM System 54 5.3 Sum Rate Maximization with Shortened Cyclic Prefix in a MIMO-OFDM System 54 Abstract (In Korean) 60 Acknowledgments 62박

New Iterative Frequency-Domain Detectors for IA-Precoded MC-CDMA Systems

The aim of this paper is to design new multi-user receivers based on the iterative block decision feedback equalization concept for MC-CDMA systems with closed-form interference alignment (IA) at the transmitted side. IA is a promising technique that allows high capacity gains in interfering channels. On the other hand, iterative frequency-domain detection receivers based on the IB-DFE concept can efficiently exploit the inherent space-frequency diversity of the MIMO MC-CDMA systems. In IA-precoded based systems the spatial streams are usually separated by using a standard linear MMSE equalizer. However, for MC-CDMA based systems, linear equalization is not the most efficient way of separating spatial streams due to the residual inter-carrier interference (ICI). Therefore, we design new non-linear iterative receiver structures to efficiently remove the aligned interference and separate the spatial streams in presence of residual ICI. Two strategies are considered: in the first one the equalizer matrices are obtained by minimizing the mean square error (MSE) of each individual data stream at each subcarrier, while in the second approach the matrices are computed by minimizing the overall MSE of all data streams at each subcarrier. We also propose an accurate analytical approach for obtaining the performance of the proposed receivers. Our schemes achieve the maximum degrees of freedom provided by the IA precoding, while allowing close-to-optimum space-diversity gain, with performance approaching the matched filter bound

Spectrum Adaptation in Cognitive Radio Systems with Operating Constraints

The explosion of high-data-rate-demanding wireless applications such as smart-phones and wireless Internet access devices, together with growth of existing wireless services, are creating a shortage of the scarce Radio Frequency (RF) spectrum. However, several spectrum measurement campaigns revealed that current spectrum usage across time and frequency is inefficient, creating the artificial shortage of the spectrum because of the traditional exclusive command-and-control model of using the spectrum. Therefore, a new concept of Cognitive Radio (CR) has been emerging recently in which unlicensed users temporarily borrow spectrum from the licensed Primary Users (PU) based on the Dynamic Spectrum Access (DSA) technique that is also known as the spectrum sharing concept. A CR is an intelligent radio system based on the Software Defined Radio platform with artificial intelligence capability which can learn, adapt, and reconfigure through interaction with the operating environment. A CR system will revolutionize the way people share the RF spectrum, lowering harmful interference to the licensed PU of the spectrum, fostering innovative DSA technology and giving people more choices when it comes to using the wireless-communication-dependent applications without having any spectrum congestion problems. A key technical challenge for enabling secondary access to the licensed spectrum adaptation is to ensure that the CR does not interfere with the licensed incumbent users. However, incumbent user behavior is dynamic and requires CR systems to adapt this behavior in order to maintain smooth information transmission. In this context, the objective of this dissertation is to explore design issues for CR systems focusing on adaptation of physical layer parameters related to spectrum sensing, spectrum shaping, and rate/power control. Specifically, this dissertation discusses dynamic threshold adaptation for energy detector spectrum sensing, spectrum allocation and power control in Orthogonal Frequency Division Multiplexing-(OFDM-)based CR with operating constraints, and adjacent band interference suppression techniques in turbo-coded OFDM-based CR systems

Pulse shaping approach to PAPR reduction for OFDM communication systems

One of the main drawbacks of the OFDM communication system is the high peak-to-average-power ratio (PAPR) of the transmitted signal. In this thesis: (i ) Optimal pulse shaping filter design is proposed to reduce the PAPR of the OFDM signal; (ii ) The level crossing rate theorem is used to derive an upper bound for the CCDF of PAPR of OFDM signal with pulse shaping; (iii ) The multiple filter design is proposed to reduce the PAPR of multiuser OFDM signal

Space-time-frequency block codes for MIMO-OFDM in next generation wireless systems

In this thesis the use of space-frequency block codes (SFBC) and space-time-frequency block codes (STFBC) in wireless systems are investigated. A variety of SFBC and STFBC schemes are proposed for particular propagation scenarios and system settings where each has its own advantages and disadvantages. The objective is to pro-pose coding strategies with improved flexibility, feasibility and spectral efficiency,and reduce the decoding complexity in an MIMO-OFDM system. Firstly an efficient SFBC with improved system performance is proposed for MIMO-OFDM systems. The proposed SFBC incorporates the concept of matched rotation precoding (MRP) to achieve full transmit diversity and optimal system performance foran arbitrary numberoftransmitantennas,subcarrierinterval andsubcarriergrouping. The MRP is proposed to exploit the inherent rotation and repetition properties of SFBC, arising from the channel power delay profile, in order to fully capture both space and frequency diversity of SFBC in a MIMO-OFDM system. It is able to relax restrictions on subcarrier interval and subcarrier grouping, making it ideal for adaptive/time-varying systems or multiuser systems. The SFBC without an optimization process is unstable in terms of achievable system performance and diversity order, and also risks diversity loss within a specific propagation scenario. Such loss or risk is prominent while wireless propagation channel has a limited number of dominant paths, e.g. relatively close to transmitters or relatively flat topography. Hence in orderto improve the feasibility of SFBC in dynamic scenarios, the lower bound of the coding gain for MRP is derived. The SFBC with MRP is proposed for more practical scenarios when only partial channel power delay profile information is known at the transmit end, for example the wireless channel has dominant propagation paths. The proposed rate one MRP has a relatively simple optimization process that can be transformed into an explicit diagram and hence an optimal result can be derived intuitively without calculations. Next, a multi-rate transmission strategy is proposed for both SFBCand STFBC to balance the system performance and transmission rate. A variety of rate adaptive coding matrices are obtained by a simple truncation of the coding matrix, or by parameter optimization for coding matrices for a given transmission rate and constellation. Pro-posed strategy can easily and gradually adjust the achievable diversity order. As a result it is capable of achieving a relatively smooth balance between system performance and transmission rate in both SFBC and STFBC, without a significant change of coding structure or constellation size. Such tradeoff would be useful to maintain stable Quality of Service (QoS) for users by providing more scalability of achievable performance in a time-varying channel. Finally the decoding procedure of space-time block code (STBC), SFBCand STFBC is discussed. The decoding of all existing STBC/SFBC/STFBC is unified at first, in order to show a concise procedure and make fair comparisons. Then maximum likelihood decoding (MLD) and arbitrary sphere decoding (SD) can be adopted. To reduce the complexity of decoding further, a novel decoding method called compensation de-coding (CD) is presented for a given space-time-frequency coding scheme. By taking advantage of the simplicity of zero-forcing decoding (ZFD) we are able to calculate a compensation vector for the output of ZFD. After modification by utilizing the com-pensation vector, the BER performance can be improved significantly. The decoding procedure is relatively simple and is independent of the constellation size. The per-formance of the proposed decoding method is close to maximum-likelihood decoding for low to medium SNR. A low complexity detection scheme, classifier based decoding (CBD), is further proposed for MIMO systems incorporating spatial multiplexing. The CBD is a hybrid of an equalizer-based technique and an algorithmic search stage. Based on an error matrix and its probability density functions for different classes of error, a particular search region is selected for the algorithmic stage. As the probability of occurrence of error classes with larger search regions is small, overall complexity of the proposed technique remains low, whilst providing a significant improvement in the bit error rate performance

Enabling Technology and Algorithm Design for Location-Aware Communications

Location-awareness is emerging as a promising technique for future-generation wire­ less network to adaptively enhance and optimize its overall performance through location-enabled technologies such as location-assisted transceiver reconfiguration and routing. The availability of accurate location information of mobile users becomes the essential prerequisite for the design of such location-aware networks. Motivated by the low locationing accuracy of the Global Positioning System (GPS) in dense multipath environments, which is commonly used for acquiring location information in most of the existing wireless networks, wireless communication system-based po­sitioning systems have been investigated as alternatives to fill the gap of the GPS in coverage. Distance-based location techniques using time-of-arrival (TOA) mea­surements are commonly preferred by broadband wireless communications where the arrival time of the signal component of the First Arriving Path (FAP) can be con­verted to the distance between the receiver and the transmitter with known location. With at least three transmitters, the location of the receiver can be determined via trilatération method. However, identification of the FAP’s signal component in dense multipath scenarios is quite challenging due to the significantly weaker power of the FAP as compared with the Later Arriving Paths (LAPs) from scattering, reflection and refraction, and the superposition of these random arrival LAPs’ signal compo­ nents will become large interference to detect the FAP. In this thesis, a robust FAP detection scheme based on multipath interference cancellation is proposed to im­ prove the accuracy of location estimation in dense multipath environments. In the proposed algorithm, the signal components of LAPs is reconstructed based on the estimated channel and data with the assist of the communication receiver, and sub­ sequently removed from the received signal. Accurate FAP detection results are then achieved with the cross-correlation between the interference-suppressed signal and an augmented preamble which is the combination of the original preamble for com­ munications and the demodulated data sequences. Therefore, more precise distance estimation (hence location estimation) can be obtained with the proposed algorithm for further reliable network optimization strategy design. On the other hand, multiceli cooperative communication is another emerging technique to substantially improve the coverage and throughput of traditional cellular networks. Location-awareness also plays an important role in the design and imple­mentation of multiceli cooperation technique. With accurate location information of mobile users, the complexity of multiceli cooperation algorithm design can be dra­matically reduced by location-assisted applications, e.g., automatic cooperative base station (BS) determination and signal synchronization. Therefore, potential latency aroused by cooperative processing will be minimized. Furthermore, the cooperative BSs require the sharing of certain information, e.g., channel state information (CSI), user data and transmission parameters to perform coordination in their signaling strategies. The BSs need to have the capabilities to exchange available information with each other to follow up with the time-varying communication environment. As most of broadband wireless communication systems are already orthogonal frequency division multiplexing (OFDM)-based, a Multi-Layered OFDM System, which is spe­cially tailored for multiceli cooperation is investigated to provide parallel robust, efficient and flexible signaling links for BS coordination purposes. These layers are overlaid with data-carrying OFDM signals in both time and frequency domains and therefore, no dedicated radio resources are required for multiceli cooperative networks. In the final aspect of this thesis, an enhanced channel estimation through itera­ tive decision-directed method is investigated for OFDM system, which aims to provide more accurate estimation results with the aid of the demodulated OFDM data. The performance of traditional training sequence-based channel estimation is often lim­ ited by the length of the training. To achieve acceptable estimation performance, a long sequence has to be used which dramatically reduces the transmission efficiency of data communication. In this proposed method, the restriction of the training se­quence length can be removed and high channel estimation accuracy can be achieved with high transmission efficiency, and therefore it particular fits in multiceli coopera­tive networks. On the other hand, as the performance of the proposed FAP detection scheme also relies on the accuracy of channel estimation and data detection results, the proposed method can be combined with the FAP detection scheme to further optimize the accuracy of multipath interference cancellation and FAP detection

Intelligent genetic algorithms for next-generation broadband multi-carrier CDMA wireless networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This dissertation proposes a novel intelligent system architecture for next-generation broadband multi-carrier CDMA wireless networks. In our system, two novel and similar intelligent genetic algorithms, namely Minimum Distance guided GAs (MDGAs) are invented for both peak-to-average power ratio (PAPR) reduction at the transmitter side and multi-user detection (MUD) at the receiver side. Meanwhile, we derive a theoretical BER performance analysis for the proposed MC-CDMA system in A WGN channel. Our analytical results show that the theoretical BER performance of synchronized MC-CDMA system is the same as that of the synchronized DS-CDMA system which is also used as a theoretical guidance of our novel MUD receiver design. In contrast to traditional GAs, our MDGAs start with a balanced ratio of exploration and exploitation which is maintained throughout the process. In our algorithms, a new replacement strategy is designed which increases significantly the convergence rate and reduces dramatically computational complexity as compared to the conventional GAs. The simulation results demonstrate that, if compared to those schemes using exhaustive search and traditional GAs, (1) our MDGA-based P APR reduction scheme achieves 99.52% and 50+% reductions in computational complexity, respectively; (2) our MDGA-based MUD scheme achieves 99.54% and 50+% reductions in computational complexity, respectively. The use of one core MDGA solution for both issues can ease the hardware design and dramatically reduce the implementation cost in practice

Performance enhancement for LTE and beyond systems

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyWireless communication systems have undergone fast development in recent years. Based on GSM/EDGE and UMTS/HSPA, the 3rd Generation Partnership Project (3GPP) specified the Long Term Evolution (LTE) standard to cope with rapidly increasing demands, including capacity, coverage, and data rate. To achieve this goal, several key techniques have been adopted by LTE, such as Multiple-Input and Multiple-Output (MIMO), Orthogonal Frequency-Division Multiplexing (OFDM), and heterogeneous network (HetNet). However, there are some inherent drawbacks regarding these techniques. Direct conversion architecture is adopted to provide a simple, low cost transmitter solution. The problem of I/Q imbalance arises due to the imperfection of circuit components; the orthogonality of OFDM is vulnerable to carrier frequency offset (CFO) and sampling frequency offset (SFO). The doubly selective channel can also severely deteriorate the receiver performance. In addition, the deployment of Heterogeneous Network (HetNet), which permits the co-existence of macro and pico cells, incurs inter-cell interference for cell edge users. The impact of these factors then results in significant degradation in relation to system performance. This dissertation aims to investigate the key techniques which can be used to mitigate the above problems. First, I/Q imbalance for the wideband transmitter is studied and a self-IQ-demodulation based compensation scheme for frequencydependent (FD) I/Q imbalance is proposed. This combats the FD I/Q imbalance by using the internal diode of the transmitter and a specially designed test signal without any external calibration instruments or internal low-IF feedback path. The instrument test results show that the proposed scheme can enhance signal quality by 10 dB in terms of image rejection ratio (IRR). In addition to the I/Q imbalance, the system suffers from CFO, SFO and frequency-time selective channel. To mitigate this, a hybrid optimum OFDM receiver with decision feedback equalizer (DFE) to cope with the CFO, SFO and doubly selective channel. The algorithm firstly estimates the CFO and channel frequency response (CFR) in the coarse estimation, with the help of hybrid classical timing and frequency synchronization algorithms. Afterwards, a pilot-aided polynomial interpolation channel estimation, combined with a low complexity DFE scheme, based on minimum mean squared error (MMSE) criteria, is developed to alleviate the impact of the residual SFO, CFO, and Doppler effect. A subspace-based signal-to-noise ratio (SNR) estimation algorithm is proposed to estimate the SNR in the doubly selective channel. This provides prior knowledge for MMSE-DFE and automatic modulation and coding (AMC). Simulation results show that this proposed estimation algorithm significantly improves the system performance. In order to speed up algorithm verification process, an FPGA based co-simulation is developed. Inter-cell interference caused by the co-existence of macro and pico cells has a big impact on system performance. Although an almost blank subframe (ABS) is proposed to mitigate this problem, the residual control signal in the ABS still inevitably causes interference. Hence, a cell-specific reference signal (CRS) interference cancellation algorithm, utilizing the information in the ABS, is proposed. First, the timing and carrier frequency offset of the interference signal is compensated by utilizing the cross-correlation properties of the synchronization signal. Afterwards, the reference signal is generated locally and channel response is estimated by making use of channel statistics. Then, the interference signal is reconstructed based on the previous estimate of the channel, timing and carrier frequency offset. The interference is mitigated by subtracting the estimation of the interference signal and LLR puncturing. The block error rate (BLER) performance of the signal is notably improved by this algorithm, according to the simulation results of different channel scenarios. The proposed techniques provide low cost, low complexity solutions for LTE and beyond systems. The simulation and measurements show good overall system performance can be achieved