RIS-Enabled Integrated Anti-Jamming Covert Communication and Sensing Systems

In this paper, we explore the use of reconfigurable intelligent surface (RIS) in unmanned aerial vehicle (UAV) based multiuser downlink communications, where a flying UAV serves multiple single antenna users through multiple RISs mounted on various buildings. More specifically, we consider the selection of RISs based on the outdated and imperfect channel state information (CSI) of the composite UAV-RIS-User channels at the UAV. After selection process, the UAV communicates to the user via the selected RISs and also with the direct link. Particularly, we derive an infinite series based expression for selection probability of RISs under both the outdated and imperfect CSI of composite channels based selection scheme. We also derive the statistical distribution of instantaneously received signal-to-noise ratio (SNR) under outdated and imperfect CSI conditions of both the direct and composite links at the user. Next, using the derived statistics, we analyze the network’s performance in terms of the average coverage probability (ACP) and average bit error rate (ABER) over the complete UAV flight time. Moreover, we discuss the behavior of ACP and ABER for very small and very large values of UAV transmit power, respectively. It is depicted through numerical results that selecting more RISs from a group of small-sized RISs may not be as advantageous as selecting fewer RISs from a group of large-sized RISs. Moreover, we also demonstrate the effect of several system parameters such as number of RIS reflecting elements, number of selected RISs, the severity of UAV-RIS and RIS-User links, and the severity of imperfect and outdated CSI on the network’s performance. The analytical results are corroborated with Monte-Carlo simulations.

The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) has been deemed a promising paradigm to provide ubiquitous communication and computing services for the Internet of Things (IoT). Besides, by intelligently reflecting the received signals, the reconfigurable intelligent surface (RIS) can significantly improve the propagation environment and further enhance the service quality of the UAV-enabled MEC. Motivated by this vision, in this paper, we consider both the amount of completed task bits and the energy consumption to maximize the energy efficiency of the RIS-assisted UAV-enabled MEC systems with non-orthogonal multiple access (NOMA) protocol, where the bit allocation, transmit power, phase shift, and UAV trajectory are jointly optimized by an iterative algorithm with a double-loop structure based on the Dinkelbach’s method and block coordinate decent (BCD) technique. Simulation results demonstrate that: 1) our proposed algorithm can achieve higher energy efficiency than baseline schemes while satisfying the task tolerance latency; 2) the energy efficiency first increases and then decreases with the increase of the mission period and the total amount of task-input bits of IoT devices; 3) the energy efficiencies of schemes with imperfect channel state information (CSI) are lower than corresponding schemes with perfect CSI, and the performance gain of NOMA over OMA diminishes under the imperfect CSI.

Reconfigurable Intelligent Surface (RIS) is an emerging technology that can improve the spectrum and energy efficiency of next-generation wireless networks. However, attaining accurate channel state information (CSI) for the cascaded RIS channel is particularly challenging. Imperfect CSI is a major bottleneck to achieving the spectral efficiency benefit of RIS-assisted networks. Rate splitting (RS), a promising multiple access technology, has been shown to be able to achieve an improved spectrum efficiency and be robust to channel uncertainties. This paper investigates the interplay between RIS and RS by considering a RIS-assisted RS beamforming problem. Active beamforming at the base station (BS) and passive beamforming at the RIS are jointly considered to maximize the minimum user rate under both the perfect CSI case and the imperfect CSI case. A block coordinate descent (BCD) algorithm is developed to solve this non-convex problem. Compared with the conventional semi-definite relaxation (SDR) approach, the proposed method does not require that the covariance matrix of the common beamforming vector be rank-one. Moreover, we present theoretical results to help reveal the impact of the system parameters and explain the performance gain resulting from the integration of RIS and RS. Extensive simulation results are also provided to show that RIS-assisted RS can improve the max-min rate performance significantly compared with conventional multiple access technologies, such as non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) with/without RIS, especially in overloaded systems. With the proposed method, RS shows great potential in combating realistic CSI errors in RIS-assisted networks.

In this paper, a comprehensive comparison analysis in terms of outage probability and average symbol error ratio (SER) is presented for cooperative cognitive multiple-input and multiple-output (CC-MIMO) multiuser systems with amplify-and-forward (AF) protocol. Specially, we consider two scenarios where the CC-MIMO multiuser systems have the perfect and imperfect channel state information (CSI). The CC-MIMO multiuser systems consist of one multi-antenna source, one single-antenna relay, and multiple multi-antenna destinations. At the secondary source and destinations, the maximal ratio transmission (MRT) and maximal ratio combining (MRC) are employed, respectively. For such CC-MIMO multiuser systems, we first obtain the exact closed-form expressions of outage probability under the two cases where the CC-MIMO multiuser systems have the perfect and imperfect CSI. Then, to reduce the implementation complexity, the tight lower bounds of outage probability and average SER are derived. Finally, to obtain insight, by using the high signal-to-noise ratio (SNR) approximation, the asymptotic estimations of outage probability are achieved. The numerical results show that the derivations are agreed with the simulations, which validate our derivations. At the same time, the results show that, for the systems without perfect CSI, the achievable diversity order reduces to one, regardless of the number of antennas at the cognitive source and destinations as well as the number of the cognitive destinations. Nevertheless, these key parameters affect the coding gain of the CC-MIMO multiuser systems. When the systems have the perfect CSI (or without feedback delay), the achievable diversity gain is determined by the minimum between the number of source’s antennas and the product of the number of destinations and the number of destination’s antennas. For the effect of PU’s parameters, our results indicate that primary systems only affect the coding gain but not the diversity gain.

Reconfigurable intelligent surface (RIS) has recently been regarded as a potential technique to enhance the performance of wireless communication systems by creating additional communication links. However, it is almost impossible to get the perfect channel state information (CSI) from the base station (BS) to the Internet of Things Devices (IoTDs) and the RIS-related channels. Furthermore, residual transceiver hardware impairments inevitably affect the performance of wireless communication systems. Hence, we study the robust design for an RIS-aided wireless communication system based on the imperfect CSI and hardware impairments. Minimizing the power consumption of BS is formulated by ensuring the minimum signal-to-interference-plus-noise ratio (SINR) demands of the IoTDs and the unit-modulus constraints of the RIS. Specifically, after approximating the nonconvex constraints by using the S-procedure and the successive convex approximation (SCA) methods, we adopt the block coordinate descent (BCD) technique to iteratively optimize one set of variables while keeping the other variables fixed in various channel uncertainty scenarios. Simulation results demonstrate that the influence of transceiver hardware impairments can be effectively decreased by deploying RIS even with channel uncertainty, which is more advantageous than increasing the number of BS’s antennas.

In this letter, we study the robust beamforming design for the reconfigurable intelligent surface (RIS)-assisted communication systems from a multi-antenna access point (AP) to a single-antenna user under imperfect channel state information (CSI), where the RIS has only a finite number of phase shifts at each element. In particular, considering the cascaded AP-RIS-user channel estimation error, we aim to jointly optimize the transmit beamforming at the AP and discrete phase shifts of RIS to minimize the transmission power of AP, subject to a signal-to-noise ratio constraint at the user. To tackle the non-convex optimization problem, we decouple it into two subproblems and propose a novel alternative optimization framework. More specifically, the robust beamforming of AP is first obtained through S-Procedure and semidefinite relaxation. Then we recast the discrete phase shift constraint at RIS into an equivalent convex one, and propose an efficient algorithm to obtain a near optimal solution. Finally, the two subproblems are iteratively optimized to obtain joint robust beamforming. Simulation results show that the proposed scheme can approach the performance of the perfect CSI counterpart and substantially outperform traditional non-robust methods.

In this paper, unmanned aerial vehicle (UAV) and reconfigurable intelligent surfaces (RIS) are combined together to further enhance the covert communication system. In particular, a multi-antenna transmitter Alice transmits information to Bob, through UAV-RIS in the presence of an adversarial warden, whose channel state information (CSI) is not perfectly known at Alice. To simultaneously guarantee the covertness and the robustness, the minimum worst-case average covert transmission rate is maximized by jointly optimizing the beamforming vector, the phase shift vector and UAV trajectory. Moreover, the robust design of beamforming, phase shift and three-dimensional (3D) trajectory is formulated as a non-convex problem. To deal with the intractable optimization problem, an alternative optimization algorithm consisting of three subproblems is designed to deal with the joint optimization problem. The general sign-definiteness is utilized to transform the CSI uncertainty and successive convex approximation (SCA) methods are proposed to transform non-convex constraints. Besides, considering the high complexity of the proposed SCA based algorithm, we further develop a low-complexity algorithm for a special case of perfect CSI scenario, where analytical expressions of the beamforming and phase shift are derived. Finally, simulation results demonstrate that the noise uncertainty for hiding legitimate communication is not necessarily as high as possible for a large equivalent receiving power threshold β and the proposed scheme outperforms the state-of-the-art schemes.

Reconfigurable intelligent surfaces (RIS) have emerged as a promising approach to enhance the secrecy performance of wireless networks from a physical layer security perspective. However, its effectiveness critically depends on the availability of accurate instantaneous channel state information (CSI) at the RIS controller. This work evaluates the impact of outdated CSI on the secrecy performance of a multiple RIS-aided wireless network. To this end, a closed-form expression for the secrecy outage probability (SOP) is derived assuming the availability of an outdated CSI at the RIS controller. The obtained results demonstrate the network’s secrecy degradation level due to the CSI outdatedness, while the increase in the number of RISs can compensate for such a secrecy loss. For instance, incorporating three RISs improves the SOP by two orders of magnitude with respect to a single RIS for 25% of CSI outdatedness. Furthermore, the results reveal that, under specific scenarios of several channel outdatedness, a baseline single RIS with a perfect CSI can outperform multiple RISs with outdated CSI. These findings highlight a critical limitation in incorporating multiple RISs in a wireless network with severe channel aging, requiring the increase of the RISs size or the number of RISs to combat its effect.

In this paper, with the aid of new analytical method, we present a new closed-form expression for the ergodic capacity of full-duplex relaying (FDR) systems, with multiple antenna amplify-and-forward (AF) cooperative networks and imperfect channel state information (CSI). At the relay, the loopback self-interfernce (LI) is mitigated by using receive zero-forcing (ZF) precoding scheme, then steering the signal to the destination by using the maximum-ratio transmission (MRT) technique. To facilitate comparison, a closed-form expression for the ergodic capacity of half-duplex relaying (HDR) systems with multiple antenna AF cooperative networks is also addressed, when maximum-ratio combining (MRC)/MRT precoding schemes are performed at the relay input/output, respectively. Therefore, since perfect CSI is not available in practice, this paper investigates the impact of channel estimation errors on the performance of receive ZF/MRT and MRC/MRT schemes. These expressions are exact in the case of perfect CSI and form a very tight indistinguishable lower-bound in the case of imperfect CSI. Numerical results sustained by Monte-Carlo simulations show the exactness of the proposed analytical expressions in perfect CSI and the tightness of the lower-bounds in imperfect CSI. In addition, it is seen here that the FDR AF cooperative systems outperforms the HDR AF cooperative systems in terms of capacity. Furthermore, in contrast to perfect CSI, in the presence of imperfect CSI, an ergodic capacity ceiling is seen as SNR increases. Besides, it is seen that the ergodic capacity degradation due to imperfect CSI is higher in the FDR case because of the extra LI estimation errors.

Reconfigurable intelligent surface (RIS) can serve as a passive relay to maintain communication between a transceiver in severe scenarios of no direct link between them. In addition, harvesting energy from radio frequency (RF) signals can meliorate significantly energy efficiency. In this research, we propose RIS-aided communication systems with energy harvesting (RISwEH) which combine both RIS and RF energy harvesting to improve energy efficiency as well as communication reliability. To evaluate realistically and quickly the performance of the RISwEH, we propose the explicit formulas of the system throughput and the outage probability under the realistic scenario of Nakagami-m fading and imperfect channel state information (CSI). Moreover, we propose an optimization algorithm relied upon a Golden section search to attain the optimum value of the time splitting factor of energy harvester to obtain the best system performance. Various results corroborate the theoretical derivations, confirm the efficacy of the proposed optimization algorithm, and illustrate the influence of innumerable system settings on the system performance. Particularly, the imperfect CSI deteriorates considerably the system performance. Nonetheless, the performance of the RISwEH can be enhanced by accreting the quantity of the elements of the RIS as well as with the lower fading severity. Furthermore, the time splitting factor also impacts dramatically the outage performance of the RISwEH and its optimal value mitigates significantly the outage probability.

For the next generation of wireless communication network, a heterogeneous network architecture with macro cells, small cells, and relays offers numerous advantages, such as higher spectrum efficiency, better fairness in resource allocation, and energy efficient usage as well as optimal coverage. However, this approach encounters various network management challenges, including interference mitigation techniques. In this paper, we consider a multi-user half-duplex amplify-and-forward-MIMO relay system, where a macro basis station communicates with edge cell users via relays and each node has multiple antennas. In this context, we propose two interference alignment (IA) schemes, for which a hybrid approach of the problem formulation based on zero-forcing (ZF) and minimum-mean-square-error optimization criteria was developed to deal with interferences in perfect and imperfect channel state information (CSI) cases. In the case of perfect CSI, simulation results show that this approach provides a SNR gain of about 4 dB regarding BER performance in comparison to that achieved by the reference approach, where all filters are determined solely based on ZF criterion. Furthermore, the achieved capacity and effective signal-to-interference-plus-noise ratio at each edge node are improved by around 5 dB. Having CSI errors, the system performance is significantly improved using the robust design IA approach by minimizing the expected value of cost functions.

SummaryIn this paper, we analyze the performance of maximum‐ratio combining (MRC) receivers for single‐input multiple‐output (SIMO) non‐orthogonal multiple access (NOMA) system. We explore the aforesaid system performance in presence of impairments like imperfect channel state information (CSI) and successive interference cancellation (SIC) errors. In general, receive diversity provides diversity gain and helps to maintain quality of service (QoS), while the NOMA system achieves higher spectral efficiency compared to orthogonal multiple access (OMA). Power‐domain NOMA system transmits superimposed‐coded signal, which utilize SIC detection method at the receiving users. Here, we derive the closed‐form expression of the average bit error rate (BER) for the MRC‐based NOMA system. We also analyze the performance of the system in high signal‐to‐noise ratio (SNR) regime through derived asymptotic expression. Furthermore, the outage probability, diversity order, and sum rate comparison between NOMA and OMA system are also presented. Simulation results also validate the derived theoretical expressions and confirm the diversity gain achieved for the considered system.

This paper studies robust transmission schemes for MISO wiretap channels with imperfect channel state information (CSI) for the eavesdropper link. Both the cases of direct transmission and cooperative jamming with a helper are investigated. The error in the eavesdropper's CSI is assumed to be norm-bounded, and robust transmit covariance matrices are obtained based on worst-case secrecy rate maximization, under both individual and global power constraints. Numerical results show the advantage of the proposed robust design. In particular, under a global power constraint, although cooperative jamming is not necessary for optimal transmission with perfect eavesdropper's CSI, we show that robust jamming support can increase the secrecy rate in the presence of channel mismatch.

Interference alignment (IA) is a multi-user wireless communication strategy that enables several transmitters simultaneous communicate with their paired receivers without interfering each other. IA is a multiplexing gain optimal strategy at the expense of requiring the global channel state information (CSI) at the transmitters. Most previous works assume the availability of perfect CSI which is not possible in practice. The performance of IA algorithms based on perfect CSI drop dramatically in circumstance where CSI errors exist. In this paper we propose a robust minimum mean square error (MMSE) IA algorithm with imperfect CSI. Based on a Gaussian statistic channel error model, we give the mean square error objective function with per transmitter power constraint. The objective function is not joint convex in precoders and decoders, but convex in precoders with fixed decoders and vice versa. We convert the problem to two convex sub problems and iteratively find the solutions. Numerical results are presented to validate the effectiveness of proposed algorithm when CSI errors exist.

In the presence of perfect channel state information (CSI), the achievable degrees of freedom (DoF) in wireless interference networks can be linearly scaled up with the number of users. Achievability is based on the idea of interference alignment (IA). However, in the presence of imperfect CSI, the sum rate becomes degraded, and full DoF may no longer be achievable. In this paper, the authors propose novel least squares (LS)- and minimum mean square error (MMSE)-based IA schemes that adaptively design beamformers by relying on the availability of imperfect CSI and knowledge of the channel estimation error variance in advance. Interestingly and unlike the other robust algorithms, the proposed adaptive schemes do not impose extra computational complexity compared to their nonadaptive counterparts. It is shown that the LS-based IA is able to outperform interference leakage minimization algorithms under both perfect and imperfect CSI. Furthermore, the authors compare the performance of the proposed MMSE-based IA with maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. The authors show that while under perfect CSI, the MMSE-based IA achieves the same performance as that of Max-SINR, the former outperforms the latter under CSI mismatch. Meanwhile, it is shown that the proposed MMSE-based IA needs less CSI to be available and has less computational complexity compared to Max-SINR.