Compressed sensing improves the performance of subcarrier index-modulation assisted OFDM

In orthogonal frequency division multiplexing relying on subcarrier index modulation (OFDM-SIM), the information is conveyed by both the indices of the activated subcarriers and the conventional amplitude-phase modulated (APM) symbols. It has been shown that OFDM-SIM is capable of striking a tradeoff between the attainable spectral efficiency (SE) and energy efficiency (EE). In order to further increase the EE of the OFDM-SIM system, while potentially increasing its SE, we propose a compressed sensing (CS) assisted signalling strategy for the family of OFDM-SIM systems. Correspondingly, we first consider the joint maximum likelihood (JML) detection of the CS assisted index-modulated (CSIM) and of the classic APM symbols, despite its high complexity. Then, we propose a low complexity detection algorithm, which is termed as the iterative residual check (IRC) based detector. This is based on the Greedy Pursuit concept of CS, which makes locally optimal choices at each step. Finally, both analytical and simulation results are provided for characterizing the attainable system performance of our proposed OFDM-CSIM system. We demonstrate that in comparison to the conventional OFDM-SIM system, the proposed OFDM-CSIM arrangement is capable of achieving both a higher SE as well as an increased EE. We also show that the diversity gain provided by the OFDM-CSIM system is much higher than that of the OFDM-SIM system. Furthermore, our investigation of the detection performance shows that the proposed IRC detector is capable of providing an attractive detection performance at a low complexity

Multidimensional Index Modulation for 5G and Beyond Wireless Networks

This study examines the flexible utilization of existing IM techniques in a comprehensive manner to satisfy the challenging and diverse requirements of 5G and beyond services. After spatial modulation (SM), which transmits information bits through antenna indices, application of IM to orthogonal frequency division multiplexing (OFDM) subcarriers has opened the door for the extension of IM into different dimensions, such as radio frequency (RF) mirrors, time slots, codes, and dispersion matrices. Recent studies have introduced the concept of multidimensional IM by various combinations of one-dimensional IM techniques to provide higher spectral efficiency (SE) and better bit error rate (BER) performance at the expense of higher transmitter (Tx) and receiver (Rx) complexity. Despite the ongoing research on the design of new IM techniques and their implementation challenges, proper use of the available IM techniques to address different requirements of 5G and beyond networks is an open research area in the literature. For this reason, we first provide the dimensional-based categorization of available IM domains and review the existing IM types regarding this categorization. Then, we develop a framework that investigates the efficient utilization of these techniques and establishes a link between the IM schemes and 5G services, namely enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communication (URLLC). Additionally, this work defines key performance indicators (KPIs) to quantify the advantages and disadvantages of IM techniques in time, frequency, space, and code dimensions. Finally, future recommendations are given regarding the design of flexible IM-based communication systems for 5G and beyond wireless networks.Comment: This work has been submitted to Proceedings of the IEEE for possible publicatio

Multidimensional Index Modulation in Wireless Communications

In index modulation schemes, information bits are conveyed through indexing of transmission entities such as antennas, subcarriers, times slots, precoders, subarrays, and radio frequency (RF) mirrors. Index modulation schemes are attractive for their advantages such as good performance, high rates, and hardware simplicity. This paper focuses on index modulation schemes in which multiple transmission entities, namely, {\em antennas}, {\em time slots}, and {\em RF mirrors}, are indexed {\em simultaneously}. Recognizing that such multidimensional index modulation schemes encourage sparsity in their transmit signal vectors, we propose efficient signal detection schemes that use compressive sensing based reconstruction algorithms. Results show that, for a given rate, improved performance is achieved when the number of indexed transmission entities is increased. We also explore indexing opportunities in {\em load modulation}, which is a modulation scheme that offers power efficiency and reduced RF hardware complexity advantages in multiantenna systems. Results show that indexing space and time in load modulated multiantenna systems can achieve improved performance

Carrier Aggregation Enabled Integrated Sensing and Communication Signal Design and Processing

The future mobile communication systems will support intelligent applications such as Internet of Vehicles (IoV) and Extended Reality (XR). Integrated Sensing and Communication (ISAC) is regarded as one of the key technologies satisfying the high data rate communication and highly accurate sensing for these intelligent applications in future mobile communication systems. With the explosive growth of wireless devices and services, the shortage of spectrum resources leads to the fragmentation of available frequency bands for ISAC systems, which degrades sensing performance. Facing the above challenges, this paper proposes a Carrier Aggregation (CA)-based ISAC signal aggregating high and low-frequency bands to improve the sensing performance, where the CA-based ISAC signal can use four different aggregated pilot structures for sensing. Then, an ISAC signal processing algorithm with Compressed Sensing (CS) is proposed and the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) is used to solve the reconfiguration convex optimization problem. Finally, the Cram'er-Rao Lower Bounds (CRLBs) are derived for the CA-based ISAC signal. Simulation results show that CA efficiently improves the accuracy of range and velocity estimation

圧縮サブキャリアIQインデックス変調とその効率的復調法に関する研究

圧縮センシングを用いたサブキャリアインデックス変調(CS-SIM: Compressed-Sensing-aided Subcarrier Index Modulation)では，サブキャリアインデックス変調(SIM: SubcarrierIndex Modulation)信号の疎性を用いた効率的な復調を行なっておらず，圧縮信号からSIM信号を再構成するために多くの演算量を要する．信号の疎性のみならず離散性を考慮した低演算量の再構成アルゴリズムとして，離散性を考慮した高速反復縮退アルゴリズム(DFISTA: Discreteness-aware Fast Iterative Shrinkage-Thresholding Algorithm)が提案されているが，DFISTAは実数信号に対してのみ有効であるため，実軸・虚軸成分に強い相関を持つSIM信号の再構成には適さない．そこで本研究では，実軸・虚軸成分をそれぞれ独立にSIMを施すサブキャリアIQインデックス変調(SIQIM: Subcarrier In-phase/Quadrature-phase Index Modulation)に対してCSを適用した圧縮サブキャリアIQインデックス変調(CS-SIQIM)を提案する．SIQIM信号は実軸・虚軸成分が独立であるため，劣化なしで等価実数表現することが可能であり，DFISTAによる効率的な再構成を行うことが可能である．さらに，DFISTAの再構成特性を向上させるために，複数のSIQIM信号を一括して圧縮を行う一括圧縮サブキャリアIQインデックス変調(AC-SIQIM:Aggregate-Compression aided SIQIM)を提案する．また，DFISTAのハイパーパラメータの最適化のために，差分進化法に基づく最適化手法を提案する．本論文では，従来のCS-SIMと比較して，CS-SIQIMが低演算量でありながらほぼ同等のビット誤り率(BER:Bit-Error Rate)を持ち，一括圧縮(AC: Aggregate-Compression)によって，CS-SIQIMのBER特性が改善可能であることを計算機シミュレーションより示す．電気通信大学201

Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201