Impact of Inter-Operator Interference via Reconfigurable Intelligent Surfaces

A wireless communication system is studied that operates in the presence of multiple reconfigurable intelligent surfaces (RISs). In particular, a multi-operator environment is considered where each operator utilizes an RIS to enhance its communication quality. Although out-of-band interference does not exist (since each operator uses isolated spectrum resources), RISs controlled by different operators do affect the system performance of one another due to the inherently rapid phase shift adjustments that occur on an independent basis. The system performance of such a communication scenario is analytically studied for the practical case where discrete-only phase shifts occur at RIS. The proposed framework is quite general since it is valid under arbitrary channel fading conditions as well as the presence (or not) of the transceiver's direct link. Finally, the derived analytical results are verified via numerical and simulation trial as well as some novel and useful engineering outcomes are manifested.

Extreme Level Crossing Rate: A New Performance Indicator for URLLC Systems

Level crossing rate (LCR) is a well-known statistical tool that is related to the duration of a random stationary fading process \emph{on average}. In doing so, LCR cannot capture the behavior of \emph{extremely rare} random events. Nonetheless, the latter events play a key role in the performance of ultra-reliable and low-latency communication systems rather than their average (expectation) counterparts. In this paper, for the first time, we extend the notion of LCR to address this issue and sufficiently characterize the statistical behavior of extreme maxima or minima. This new indicator, entitled as extreme LCR (ELCR), is analytically introduced and evaluated by resorting to the extreme value theory and risk assessment. Capitalizing on ELCR, some key performance metrics emerge, i.e., the maximum outage duration, minimum effective duration, maximum packet error rate, and maximum transmission delay. They are all derived in simple closed-form expressions. The theoretical results are cross-compared and verified via extensive simulations whereas some useful engineering insights are manifested.

Next-Generation Full Duplex Networking System Empowered by Reconfigurable Intelligent Surfaces

Full duplex (FD) radio has attracted extensive attention due to its co-time and co-frequency transceiving capability. {However, the potential gain brought by FD radios is closely related to the management of self-interference (SI), which imposes high or even stringent requirements on SI cancellation (SIC) techniques. When the FD deployment evolves into next-generation mobile networking, the SI problem becomes more complicated, significantly limiting its potential gains.} In this paper, we conceive a multi-cell FD networking scheme by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to configure the radio environment proactively. To achieve the full potential of the system, we aim to maximize the sum rate (SR) of multiple cells by jointly optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and users and the phase shift matrix at RIS. Since the original problem is non-convex, we reformulate and decouple it into a pair of subproblems by utilizing the relationship between the SR and minimum mean square error (MMSE). The optimal solutions of TPC matrices are obtained in closed form, while both complex circle manifold (CCM) and successive convex approximation (SCA) based algorithms are developed to resolve the phase shift matrix suboptimally. Our simulation results show that introducing an RIS into an FD networking system not only improves the overall SR significantly but also enhances the cell edge performance prominently. More importantly, we validate that the RIS deployment with optimized phase shifts can reduce the requirement for SIC and the number of BS antennas, which further reduces the hardware cost and power consumption, especially with a sufficient number of reflecting elements. As a result, the utilization of an RIS enables the originally cumbersome FD networking system to become efficient and practical.

Zero Forcing Uplink Detection through Large-Scale RIS: System Performance and Phase Shift Design

A multiple-input multiple-output wireless communication system is analytically studied, which operates with the aid of a large-scale reconfigurable intelligent surface (LRIS). LRIS is equipped with multiple passive elements with discrete phase adjustment capabilities, and independent Rician fading conditions are assumed for both the transmitter-to-LRIS and LRIS-to-receiver links. A direct transceiver link is also considered which is modeled by Rayleigh fading distribution. The system performance is analytically studied when the linear yet efficient zero-forcing detection is implemented at the receiver. In particular, the outage performance is derived in closed-form expression for different system configuration setups with regards to the available channel state information (CSI) at the receiver. In fact, the case of both perfect and imperfect CSI is analyzed. Also, an efficient phase shift design approach at LRIS is introduced, which is linear on the number of passive elements and receive antennas. The proposed phase shift design can be applied on two different modes of operation; namely, when the system strives to adapt either on the instantaneous or statistical CSI. Finally, some impactful engineering insights are provided, such as how the channel fading conditions, CSI, discrete phase shift resolution, and volume of antenna/LRIS element arrays impact on the overall system performance.

Zero-Forcing Based Downlink Virtual MIMO-NOMA Communications in IoT Networks

To support massive connectivity and boost spectral efficiency for internet of things (IoT), a downlink scheme combining virtual multiple-input multiple-output (MIMO) and nonorthogonal multiple access (NOMA) is proposed. All the single-antenna IoT devices in each cluster cooperate with each other to establish a virtual MIMO entity, and multiple independent data streams are requested by each cluster. NOMA is employed to superimpose all the requested data streams, and each cluster leverages zero-forcing detection to de-multiplex the input data streams. Only statistical channel state information (CSI) is available at base station to avoid the waste of the energy and bandwidth on frequent CSI estimations. The outage probability and goodput of the virtual MIMO-NOMA system are thoroughly investigated by considering Kronecker model, which embraces both the transmit and receive correlations. Furthermore, the asymptotic results facilitate not only the exploration of physical insights but also the goodput maximization. In particular, the asymptotic outage expressions provide quantitative impacts of various system parameters and enable the investigation of diversity-multiplexing tradeoff (DMT). Moreover, power allocation coefficients and/or transmission rates can be properly chosen to achieve the maximal goodput. By favor of Karush-Kuhn-Tucker conditions, the goodput maximization problems can be solved in closed-form, with which the joint power and rate selection is realized by using alternately iterating optimization.Besides, the optimization algorithms tend to allocate more power to clusters under unfavorable channel conditions and support clusters with higher transmission rate under benign channel conditions.

Rate Splitting Multiple Access Aided Mobile Edge Computing in Cognitive Radio Networks

In this paper, we investigate rate splitting multiple access (RSMA) aided mobile edge computing (MEC) in a cognitive radio network. We propose a RSMA scheme that enables the secondary user to offload tasks to the MEC server utilizing dynamic rate splitting without deteriorating the primary user's offloading. The expressions for the optimal rate splitting parameters that maximize the achievable rate for the secondary user and successful computation probability of the proposed RSMA scheme are derived in closed-form. We formulate a problem to maximize successful computation probability by jointly optimizing task offloading ratio and task offloading time and obtain the optimal solutions in closed-form. Simulation results clarify that the proposed RSMA scheme achieves a higher successful computation probability than the existing non-orthogonal multiple access scheme.

Non-Linear Age of Information: An Energy Efficient Receiver-Centric Approach

The age of information (AoI) performance metric for point-to-point wireless communication systems is analytically studied under Rician-faded channels and when the receiver is equipped with multiple antennas. The general scenario of a non-linear AoI function is considered, which includes the conventional linear AoI as a special case. The stop-and-wait transmission policy is adopted, where the source node samples and then transmits new data only upon the successful reception of previous data. This approach can serve as a performance benchmark for any queuing system used in practice. New analytical and closed-form expressions are derived with respect to the average AoI and average peak AoI for the considered system configuration. We particularly focus on the energy efficiency of the said mode of operation, whereas some useful engineering insights are provided.

Backscatter Sensors Communication for 6G Low-powered NOMA-enabled IoT Networks under Imperfect SIC

The combination of non-orthogonal multiple access (NOMA) using power-domain with backscatter sensor communication (BSC) is expected to connect a large-scale Internet of things (IoT) devices in future sixth-generation (6G) era. In this paper, we introduce a BSC in multi-cell IoT network, where a source in each cell transmits superimposed signal to its associated IoT devices using NOMA. The backscatter sensor tag (BST) also transmit data towards IoT devices by reflecting and modulating the superimposed signal of the source. A new optimization framework is provided that simultaneously optimizes the total power of each source, power allocation coefficient of IoT devices and reflection coefficient of BST under imperfect successive interference cancellation decoding. The objective of this work is to maximize the total energy efficiency of IoT network subject to quality of services of each IoT device. The problem is first transformed using the Dinkelbach method and then decoupled into two subproblems. The Karush-Kuhn-Tucker conditions and Lagrangian dual method are employed to obtain the efficient solutions. In addition, we also present the conventional NOMA network without BSC as a benchmark framework. Simulation results unveil the advantage of our considered NOMA BSC networks over the conventional NOMA network.