Integrated sensing and communication (ISAC) has been recognized as one of the key technologies capable of simultaneously improving communication and sensing services in future wireless networks. Moreover, the introduction of recently developed movable antennas (MAs) has the potential to further increase the performance gains of ISAC systems. Achieving these gains can pose a significant challenge for MA-enabled ISAC systems operating in the near-field due to the corresponding spherical wave propagation. Motivated by this, in this paper we maximize the weighted sum rate (WSR) for communication users while maintaining a minimal sensing requirement in an MA-enabled near-field ISAC system. To achieve this goal, we propose an algorithm that optimizes the sensing receive combiner, the communication precoding matrices, the sensing transmit beamformer and the positions of the users' MAs in an alternating manner. Simulation results show that using MAs in near-field ISAC systems provides a substantial performance advantage compared to near-field ISAC systems with only fixed antennas. Additionally, we demonstrate that the highest WSR is obtained when larger weights are allocated to the users placed closer to the BS, and that the sensing performance is significantly more affected by the minimum sensing signal-to-interference-plus-noise ratio (SINR) threshold compared to the communication performance.

Reconfigurable intelligent surfaces (RISs) have huge potential to improve spectral and energy efficiency in future wireless systems at a minimal cost. However, early prototype results indicate that deploying hundreds or thousands of reflective elements is necessary for significant performance gains. Motivated by this, our study focuses onlarge-scaleRIS-assisted multi-user (MU) multiple-input multiple-output (MIMO) systems. In this context, we propose an efficient algorithm to jointly design the precoders at the base station (BS) and the phase shifts at the RIS to maximize the weighted sum rate (WSR). In particular, leveraging an equivalent lower-dimensional reformulation of the WSR maximization problem, we derive a closed-form solution to optimize the precoders using the successive convex approximation (SCA) framework. While the equivalent reformulation proves to be efficient for the precoder optimization, we offer numerical insights into why the original formulation of the WSR optimization problem is better suited for the phase shift optimization. Subsequently, we develop a scaled projected gradient method (SPGM) and a novel line search procedure to optimize RIS phase shifts. Notably, we show that the complexity of the proposed methodscales linearly with the number of BS antennas and RIS reflective elements. Extensive numerical experiments demonstrate that the proposed algorithm significantly reduces both time and computational complexity while achieving higher WSR compared to baseline algorithms.

We present a low-complexity algorithm for jointly designing active and passive beamforming to maximize the weighted sum-rate (WSR) in downlink RIS-assisted communication systems. We exploit an equivalent, lower-dimensional reformulation of the WSR maximization problem to derive a closed-form solution for active beamforming optimization using the successive convex approximation (SCA) framework. For passive beamforming, we propose a scaled projected gradient method (SPGM) algorithm and a novel line search technique to improve performance. Notably, we demonstrate that the complexity of the proposed method scales linearly with the number of BS antennas and RIS reflective elements. Extensive numerical experiments demonstrate that our proposed algorithm significantly reduces both run time and computational complexity, while enhancing WSR performance over known benchmarks.

In this paper, we propose a semi-analytical method to design polar codes for the reconfigurable intelligent surface (RIS)-assisted channel with Rayleigh fading on each wireless link, while also providing an approximate closed-form expression for its word error probability (WEP) as a function of the number of RIS elements. Conventional polar code design methods involve numerically evaluated values of the bit-channel transition probabilities used to obtain the WEP upper bound in which the impact of the number of RIS elements, signal-to-noise ratio (SNR), and code rate is challenging to analyze. In contrast, our approach uses exponential approximations to obtain approximate closed-form expressions for the bit-channel transition probabilities. These exponential terms can be succinctly characterized in terms of coefficient pairs (CPs) which can be tracked numerically during code design and are approximately independent of the SNR and the number of RIS elements. This allows for rapid design of polar codes for any combination of the RIS elements and SNR. Numerical and simulation results show that the proposed method efficiently predicts the required number of RIS elements for a target WEP within the range of$10^{\text {-}2}$and$10^{\text {-}6}$, and can also be used to optimize resource allocation in a multiuser context.

In this paper, we propose a novel transmission scheme, calledsparse layered MIMO(SL-MIMO), that combines non-orthogonal transmission and singular value decomposition (SVD) precoding. Non-orthogonality in SL-MIMO allows re-using of the eigen-channels which improves the spectral efficiency and error rate performance of the system through enhancing the coding gain and diversity gain. We also present a low-complexity message-passing (MP) detector for the proposed SL-MIMO system which performs quite close to maximum likelihood (ML). The joint moment generating function (MGF) of theorderedeigenvalues is calculated and used to derive a closed-form upper bound on the average word error probability (AWEP) of the SL-MIMO system, and this derived expression is then used to analyze the diversity gain of the system. We use our analytical results to design sub-optimal codebooks to minimize the error rate of the SL-MIMO system. Simulation results in$4\times 4$and$6\times 6$multiple-input multiple-output (MIMO) systems with 4-ary, 16-ary, and 64-ary constellations show that our proposed SL-MIMO scheme outperforms competing approaches such as X- and Y-codes in terms of system error rate performance. SL-MIMO has 5.6 dB advantage compared to X-codes and 4.7 dB advantage compared to Y-codes in$6\times 6$MIMO system with a 64-ary constellation.

Reconfigurable intelligent surfaces (RISs) represent a promising candidate for sixth-generation (6G) wireless networks, as the RIS technology provides a new solution to control the propagation channel in order to improve the efficiency of a wireless link through enhancing the received signal power. In this paper, we propose RIS-assisted receive quadrature space shift keying (RIS-RQSSK), which enhances the spectral efficiency of an RIS-based index modulation (IM) system by using the real and imaginary dimensions independently for the purpose of IM. Therefore, the error rate performance of the system is improved as all RIS elements reflect the incident transmit signal toward both selected receive antennas. At the receiver, a low-complexity but effective greedy detector (GD) can be employed which determines the maximum energy per dimension at the receive antennas. A max-min optimization problem is defined to maximize the received signal-to-noise ratio (SNR) components at both selected receive antennas; an analytical solution is provided based on Lagrange duality. In particular, the multi-variable optimization problem is shown to reduce to the solution of a single-variable equation, which results in a very simple design procedure. In addition, we investigate the average bit error probability (ABEP) of the proposed RIS-RQSSK system and derive a closed-form approximate upper bound on the ABEP. We also provide extensive numerical simulations to validate our derivations. Numerical results show that the proposed RIS-RQSSK scheme substantially outperforms recent prominent benchmark schemes. This enhancement considerably increases with an increasing number of receive antennas.

Multilevel coding (MLC) is a coded modulation technique which can achieve excellent performance over a range of communication channels. Polar codes have been shown to be quite compatible with communication systems using MLC, as the rate allocation of the component polar codes follows the natural polarization inherent in polar codes. MLC based techniques have not yet been studied in systems that use spatial modulation (SM). SM makes the polar code design difficult as the spatial bits actually select a channel index for transmission. To solve this problem, we propose a Monte Carlo based evaluation of the ergodic capacities for the individual bit levels under the capacity rule for a space-shift keying (SSK) system, where we also make use of a single antenna activation to approximate the transmission channel for the design of the multilevel polar code. Our simulation results show that the multilevel polar coded 16 × 1 SSK system outperforms the corresponding system that uses bit-interleaved polar coded modulation by 2.9 dB at a bit error rate (BER) of 10−4.

Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation in wireless networks and offers a great variety of possible performance and implementation gains. Motivated by this, we study the achievable rate optimization for multi-stream multiple-input multiple-output (MIMO) systems equipped with an RIS, and formulate a joint optimization problem of the covariance matrix of the transmitted signal and the RIS elements. To solve this problem, we propose an iterative optimization algorithm that is based on the projected gradient method (PGM). We derive the step size that guarantees the convergence of the proposed algorithm and we define a backtracking line search to improve its convergence rate. Furthermore, we introduce the total free space path loss (FSPL) ratio of the indirect and direct links as a first-order measure of the applicability of RISs in the considered communication system. Simulation results show that the proposed PGM achieves the same achievable rate as a state-of-the-art benchmark scheme, but with a significantly lower computational complexity. In addition, we demonstrate that the RIS application is particularly suitable to increase the achievable rate in indoor environments, as even a small number of RIS elements can provide a substantial achievable rate gain.

Indoor millimeter-wave (mmWave) environment channels are typically sparsely-scattered and dominated by a strong line-of-sight (LOS) path. Therefore, communication over such channels is in general extremely difficult when the LOS path is not present. However, the recent introduction of reconfigurable intelligent surfaces (RISs), which have the potential to influence the propagation environment in a controlled manner, has the potential to change the previous paradigm. Motivated by this, we study the channel capacity optimization utilizing RISs in indoor mmWave environments where no LOS path is present. More precisely, we propose two optimization schemes that exploit the customizing capabilities of the RIS reflection elements in order to maximize the channel capacity. The first optimization scheme exploits only the adjustability of the RIS reflection elements; for this scheme we derive an approximate expression which explains the connection between the channel capacity gains and the system parameters. The second optimization scheme jointly optimizes the RIS reflection elements and the transmit phase precoder; for this scheme, we propose a low-complexity technique called global co-phasing to determine the phase shift values for use at the RIS. Simulation results show that the optimization of the RIS reflection elements produces a significant channel capacity gain, and that this gain increases with the number of RIS elements.

We propose a novel scheme for downlink multiuser multiple-input multiple-output (MIMO) systems, called dual-layered transmit-receive generalized spatial modulation (DL-TR-GSM). The proposed scheme is based on the concept of dual-layered transmission (DLT) which uses two receive antenna power levels instead of receive antenna activation/inactivation to transmit data in the receive spatial domain. Hence, in order to minimize the bit error rate (BER) for DL-TR-GSM, the optimal ratio between the two power levels is determined. To further characterize DL-TR-GSM, we fully derive the computational complexity and show a significant computational complexity reduction as well as a required hardware complexity reduction of DL-TR-GSM, compared to a state-of-the-art benchmark scheme. Simulation results confirm the performance advantages of DL-TR-GSM.

In this paper, we study the capacity and symbol error probability (SEP) of generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) using measured channels that are obtained by channel sounding in an indoor office environment at 60GHz. Spatial modulation (SM) and GSM are emerging low-complexity MIMO schemes that have been extensively researched for low-GHz (below 6GHz) communications. Recently, they have been considered and shown to be promising also for (mmWave) communications. In the simplest possible case, they require only one RF chain both at the transmitter (TX) and receiver (RX), and thus, are especially attractive for mmWave communications, in which the number of RF chains needs to be as low as possible. Despite of some early works on the theoretical analysis of SM/GSM for mmWave communications, there have been no investigations using real-world channel data. We focus on the office line-of-sight (LOS) scenario and investigate three problems: 1) the performance of GSM using the extracted LOS component of measured channels; 2) the impact of non-LOS NLOS components on the performance of GSM; and 3) possible simple modulation and reception algorithms for GSM that rely only on the LOS component of the channel. The results being reported in this paper not only validate the main claims of previous studies based on ideal pure LOS channels, but also lead to novel findings. One major conclusion is that NLOS components are harmful to the SEP of GSM and should be avoided. As another important outcome, our results strongly motivate the use of precoding in GSM systems to simultaneously improve the channel capacity and reduce the physical size of MIMO arrays (thus eliminating one major issue of LOS GSM).

Spatial modulation (SM) and generalized spatial modulation (GSM) are emerging multiple input multiple output (MIMO) schemes that use transmitter (TX) antenna switching for data transmission. Their operating principle makes optimization of channel capacity and mutual information usually more difficult than for conventional MIMO schemes which are not based on antenna switching. We propose to use channel cut-off rate as a relevant and more tractable metric for performance optimization of spatial modulation (SM)/GSM systems, as it constitutes a practical lower-bound of channel capacity. In particular, we propose four TX precoding schemes for increasing the cut-off rate of SM/GSM systems. We show that those TX precoding schemes which are designed for increasing array gain provide the largest improvement of cut-off rate for low signal-to-noise ratio (SNR). On the other hand, the TX precoding schemes that are designed for increasing the minimum Euclidean distance of GSM symbols are more suitable for application to medium to high SNR setups and correlated channels. The proposed precoding schemes are shown to be able to enhance mutual information, and the gain is shown to be of the same order of magnitude as the gain of the corresponding channel cut-off rate.

In this paper Minimum Mean Square Error (MMSE) precoding for the Preprocessing aided Spatial Modulation (PSM) transmission scheme is investigated. PSM is capable to transmit data both in the spatial domain and in the modulation domain. We derive the upper bound for the Average Bit Error Probability (ABEP) for MMSE precoded PSM data transmission and we show by means of simulations that the bound is tight for a large signal to noise ratio (SNR) range. Also, the influence of the number of transmit and receive antennas on the ABEP is analyzed. It is shown that the increase of the number of transmit antennas will improve the ABEP. We demonstrated that the analytical ABEP for MMSE precoded PSM is considerably lower than for Zero-Forcing (ZF) precoded PSM. We determined that for constant bit rate, the lowest Bit Error Rate (BER) is achieved with a balanced number of bits in the spatial and modulation domain. The correlation at the receive antennas has a dominant influence on the BER.

In this paper we consider Generalized Pre-coding aided Spatial Modulation (GPSM), which was recently proposed as a promising alternative to conventional Multiple Input Multiple Output (MIMO) transmission schemes. In GPSM only a part of the receive antennas is activated with the aid of pre- coding at the transmitter. Hence, information bits are mapped to a spatial symbol, corresponding to a particular activation pattern, and to modulation symbols. Optimal performance is achieved with a Maximum Likelihood (ML) detector, but its exhaustive search leads to an intractable complexity. In this paper we present a novel detector, referred to as Soft MMSE with Exhaustive Search (SOMES) detector, that computes soft information for each symbol by employing a soft- output Minimum Mean Square Error (MMSE) detector. The soft information is used to determine the activation pattern using a small exhaustive search and to obtain the symbols in the particular activation pattern. Link level simulations show that the proposed algorithm possesses the near- optimal Bit Error Rate (BER) performance while achieving a remarkable reduction in complexity.

We propose a novel diversity combining method called local average gain combining (LAGC) that is based on the local average of channel gains. Compared with MRC, which requires the instantaneous complex channel coefficients, and EGC, which requires only the instantaneous channel phases, LAGC requires the instantaneous channel phases but the lo- cal average of the channel gains, implying an implementation complexity between those of MRC and EGC. The average bit error probability (ABEP) of LAGC is analyzed and derived in closed-form using a method that is based on the characteristic function (cf) and the Paserval's theorem, showing that LAGC approximates to MRC in slow fading and to EGC in balanced fast fading. Simulations are performed to validate the analysis. The channel phase estimation error is included in the simulation, and it turns out that LAGC and EGC significantly outperform MRC and SC. This is a distinct advantage of LAGC because in fast fading it is more difficult to track the channel coefficients and on average the channel phase error is larger.