Reconfigurable Intelligent Surface Aided Space Shift Keying With Imperfect CSI

In this paper, we investigate the performance of reconfigurable intelligent surface (RIS)-aided spatial shift keying (SSK) wireless communication systems in the presence of imperfect channel state information (CSI). Specifically, we analyze the average bit error probability (ABEP) of two RIS-SSK systems respectively based on intelligent reflection and blind reflection of RIS. For the intelligent RIS-SSK scheme, we first derive the conditional pairwise error probability of the composite channel through maximum likelihood (ML) detection. Subsequently, we derive the probability density function of the combined channel. Due to the intricacies of the composite channel formulation, an exact closed-form ABEP expression is unattainable through direct derivation. To this end, we resort to employing the Gaussian-Chebyshev quadrature method to estimate the results. In addition, we employ the Q-function approximation to derive the non-exact closed-form expression when CSI imperfections are present. For the blind RIS-SSK scheme, we derive both closed-form ABEP expression and asymptotic ABEP expression with imperfect CSI by adopting the ML detector. To offer deeper insights, we explore the impact of discrete reflection phase shifts on the performance of the RIS-SSK system. Lastly, we extensively validate all the analytical derivations using Monte Carlo simulations.Comment: arXiv admin note: text overlap with arXiv:2307.0199

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

Adaptive Transmission Schemes for Spectrum Sharing Systems: Trade-offs and Performance Analysis

Cognitive radio (CR) represents a key solution to the existing spectrum scarcity problem. Under the scenario of CR, spectrum sharing systems allow the coexistence of primary users (PUs) and secondary users (SUs) in the same spectrum as long as the interference from the secondary to the primary link stays below a given threshold. In this thesis, we propose a number of adaptive transmission schemes aiming at improving the performance of the secondary link in these systems while satisfying the interference constraint set by the primary receiver (PR). In the proposed techniques, the secondary transmitter (ST) adapts its transmission settings based on the availability of the channel state information (CSI) of the secondary and the interference links. In this context, these schemes offer different performance tradeoffs in terms of spectral efficiency, energy efficiency, and overall complexity. In the first proposed scheme, power adaptation (PA) and adaptive modulation (AM) are jointly used with switched transmit diversity in order to increase the capacity of the secondary link while minimizing the average number of antenna switching. Then, the concept of minimum-selection maximum ratio transmission (MS-MRT) is proposed as an adaptive variation of maximum ratio transmission (MRT) in a spectrum sharing scenario in order to maximize the capacity of the secondary link while minimizing the average number of transmit antennas. In order to achieve this performance, MS-MRT assumes that the secondary's CSI (SCSI) is perfectly known at the ST, which makes this scheme challenging from a practical point of view. To overcome this challenge, another transmission technique based on orthogonal space time bloc codes (OSTBCs) with transmit antenna selection (TAS) is proposed. This scheme uses the full-rate full-diversity Alamouti scheme in an underlay CR scenario in order to maximize the secondary's transmission rate. While the solutions discussed above offer a considerable improvement in the performance of spectrum sharing systems, they generally experience a high overall system complexity and are not optimized to meet the tradeoff between spectral efficiency and energy efficiency. In order to address this issue, we consider using spatial modulation (SM) in order to come with a spectrum sharing system optimized in terms spectral efficiency and energy efficiency. Indeed, SM can be seen as one of the emerging and promising new technologies optimizing the communication system while reducing the energy consumption thanks to the use of a single radio frequency (RF) chain for transmission. In this context, we propose the adaptive spatial modulation (ASM) scheme using AM in order to improve the spectral efficiency of SM. We also extend ASM to spectrum sharing systems by proposing a number of ASM-CR schemes aiming at improving the performance of these systems in terms of spectral efficiency and energy efficiency. While the use of a single RF-chain improves the energy efficiency of the above schemes, the RF-chain switching process between different transmissions comes with additional complexity and implementation issues. To resolve these issues, we use the concept of reconfigurable antennas (RAs) in order to improve the performance of space shift keying (SSK). In this context, employing RAs with SSK instead of conventional antennas allows for implementing only one RF chain and selecting different antenna-states for transmission without the need for RF switching. Moreover, the reconfigurable properties of RAs can be used as additional degrees of freedom in order to enhance the performance of SSK in terms of throughput, system complexity, and error performance. These RAs-based schemes are also extended to spectrum sharing systems in order to improve the capacity of the secondary link while reducing the energy consumption and the implementation complexity of the SU. In summary, we propose in this thesis several adaptive transmission schemes for spectrum sharing systems. The performance of each of these schemes is confirmed via Monte-Carlo simulations and analytical results and is shown to offer different tradeoffs in terms of spectral efficiency, energy efficiency, reliability, and implementation complexity. In this context, these proposed schemes offer different solutions in order to improve the performance of underlay cognitive radio systems

RIS-Assisted Generalized Receive Quadrature Spatial Modulation

In this paper, reconfigurable intelligent surface (RIS)-assisted generalized receive quadrature spatial modulation (RIS-GRQSM) is proposed to improve the spectral efficiency of RIS-aided quadrature spatial modulation (QSM) systems by utilizing the concept of generalized spatial modulation (GSM). That is, multiple antennas are activated at the receiver independently for both the real and imaginary parts. We propose a max-min optimization problem to adjust the phase shifts of all RIS elements to maximize the relevant signal-to-noise ratios (SNRs) at all activated receive antennas. Using Lagrange duality, the non-convex optimization problem involving the phase shifts of all RIS elements reduces to a convex optimization involving a number of variables equal to the number of activated receive antennas. A successive greedy detector (GD) can be used at the receiver to detect the active antennas, which simplifies the detection process. The numerical results show that the proposed scheme outperforms the benchmark schemes in terms of error rate performance, especially in systems with a larger number of receive antennas. In the special case where each receive antenna corresponds to a user and is activated, the RIS-GRQSM system becomes a multicast communication system. In this context, in contrast to existing phase shift optimization algorithms which exhibit an impractical level of complexity, our proposed solution offers the advantage of low complexity and practical feasibility of implementation.Comment: 6 pages (2-column), 5 figures, 1 table, Prepared for Globcom 2023 conferenc

Index modulation for next generation wireless communications.

Doctoral Degree. University of KwaZulu-Natal, Durban.A multicarrier index modulation technique in the form of quadrature spatial modulation (QSM) orthogonal frequency division multiplexing (QSM-OFDM) is proposed, in which transmit antenna indices are employed to transmit additional bits. Monte Carlo simulation results demonstrates a 5 dB gain in signal-to-noise ratio (SNR) over other OFDM schemes. Furthermore, an analysis of the receiver computational complexity is presented. A low-complexity near-ML detector for space-time block coded (STBC) spatial modulation (STBC-SM) with cyclic structure (STBC-CSM), which demonstrate near-ML error performance and yields significant reduction in computational complexity is proposed. In addition, the union-bound theoretical framework to quantify the average bit-error probability (ABEP) of STBC-CSM is formulated and validates the Monte Carlo simulation results. The application of media-based modulation (MBM), to STBC-SM and STBC-CSM employing radio frequency (RF) mirrors, in the form of MBSTBC-SM and MBSTBC-CSM is proposed to improve the error performance. Numerical results of the proposed schemes demonstrate significant improvement in error performance when compared with STBC-CSM and STBC-SM. In addition, the analytical framework of the union-bound on the ABEP of MBSTBC-SM and MBSTBC-CSM for the ML detector is formulated and agrees well with Monte Carlo simulations. Furthermore, a low-complexity near-ML detector for MBSTBC-SM and MBSTBC-CSM is proposed, and achieves a near-ML error performance. Monte Carlo simulation results demonstrate a trade-off between the error performance and the resolution of the detector that is employed. Finally, the application of MBM, an index modulated system to spatial modulation, in the form of spatial MBM (SMBM) is investigated. SMBM employs RF mirrors located around the transmit antenna units to create distinct channel paths to the receiver. This thesis presents an easy to evaluate theoretical bound for the error performance of SMBM, which is validated by Monte Carlo simulation results. Lastly, two low-complexity suboptimal mirror activation pattern (MAP) optimization techniques are proposed, which improve the error performance of SMBM significantly

Media-Based MIMO: A New Frontier in Wireless Communications

The idea of Media-based Modulation (MBM), is based on embedding information in the variations of the transmission media (channel state). This is in contrast to legacy wireless systems where data is embedded in a Radio Frequency (RF) source prior to the transmit antenna. MBM offers several advantages vs. legacy systems, including "additivity of information over multiple receive antennas", and "inherent diversity over a static fading channel". MBM is particularly suitable for transmitting high data rates using a single transmit and multiple receive antennas (Single Input-Multiple Output Media-Based Modulation, or SIMO-MBM). However, complexity issues limit the amount of data that can be embedded in the channel state using a single transmit unit. To address this shortcoming, the current article introduces the idea of Layered Multiple Input-Multiple Output Media-Based Modulation (LMIMO-MBM). Relying on a layered structure, LMIMO-MBM can significantly reduce both hardware and algorithmic complexities, as well as the training overhead, vs. SIMO-MBM. Simulation results show excellent performance in terms of Symbol Error Rate (SER) vs. Signal-to-Noise Ratio (SNR). For example, a $4\times 16$ LMIMO-MBM is capable of transmitting $32$ bits of information per (complex) channel-use, with SER $\simeq 10^{-5}$ at $E_b/N_0\simeq -3.5$dB (or SER $\simeq 10^{-4}$ at $E_b/N_0=-4.5$dB). This performance is achieved using a single transmission and without adding any redundancy for Forward-Error-Correction (FEC). This means, in addition to its excellent SER vs. energy/rate performance, MBM relaxes the need for complex FEC structures, and thereby minimizes the transmission delay. Overall, LMIMO-MBM provides a promising alternative to MIMO and Massive MIMO for the realization of 5G wireless networks.Comment: 26 pages, 11 figures, additional examples are given to further explain the idea of Media-Based Modulation. Capacity figure adde