Interference Channel Research Articles

Attosecond dynamics of multi-channel single photon ionization

Photoionization of atoms and molecules is one of the fastest processes in nature. The understanding of the ultrafast temporal dynamics of this process often requires the characterization of the different angular momentum channels over a broad energy range. Using a two-photon interferometry technique based on extreme ultraviolet and infrared ultrashort pulses, we measure the phase and amplitude of the individual angular momentum channels as a function of kinetic energy in the outer-shell photoionization of neon. This allows us to unravel the influence of channel interference as well as the effect of the short-range, Coulomb and centrifugal potentials, on the dynamics of the photoionization process.

Simulating Spectral Kurtosis Mitigation against Realistic Radio Frequency Interference Signals

We investigate the effectiveness of the statistical radio frequency interference (RFI) mitigation technique spectral kurtosis () in the face of simulated realistic RFI signals. estimates the kurtosis of a collection of M power values in a single channel and provides a detection metric that is able to discern between human-made RFI and incoherent astronomical signals of interest. We test the ability of to flag signals with various representative modulation types, data rates, duty cycles, and carrier frequencies. We flag with various accumulation lengths M and implement multiscale , which combines information from adjacent time-frequency bins to mitigate weaknesses in single-scale . We find that signals with significant sidelobe emission from high data rates are harder to flag, as well as signals with a 50% effective duty cycle and weak signal-to-noise ratios. Multiscale with at least one extra channel can detect both the center channel and sideband interference, flagging greater than 90% as long as the bin channel width is wider in frequency than the RFI.

Capacity Bounds for the Two-User IM/DD Interference Channel

This paper studies the capacity of the two-user intensity-modulation/direct-detection (IM/DD) interference channel (IC), which is relevant in the context of multi-user optical wireless communications. Despite some known single-letter capacity characterizations for general discrete-memoryless ICs, a computable capacity expression for the IM/DD IC is missing. In this paper, we provide tight and easily computable inner and outer bounds for a general two-user IM/DD IC under peak and average optical intensity constraints. The bounds enable characterizing the asymptotic sum-rate capacity in the strong and weak interference regimes, as well as the generalized degrees of freedom (GDoF) in the symmetric case. Using the obtained bounds, the GDoF of the IM/DD IC is shown to have a ‘W’ shape similar to the Gaussian IC with power constraints. The obtained bounds are also evaluated numerically in different interference regimes to show their tightness, and used to study the performance of on-chip and indoor OWC systems.

On Rate-Splitting With Non-Unique Decoding in Multi-Cell Massive MIMO Systems

We consider the downlink of a multi-cell massive MIMO system suffering from asymptotic rate saturation due to pilot contamination. As opposed to treating pilot contamination interference as noise (TIN), we study the performance of decoding the pilot contamination interference. We model pilot-sharing users as an interference channel (IC) and study the performance of schemes that decode this interference partially based on rate-splitting (RS), and compare the performance to schemes that decode the interference in its entirety based on simultaneous unique decoding (SD) or non-unique decoding (SND). For RS, we non-uniquely decode each layer of the pilot contamination interference and use one common power splitting coefficient per IC. Additionally, we establish an achievable region for this RS scheme. Solving a maximum symmetric rate allocation problem based on linear programming (LP), we show that for zero-forcing (ZF) with spatially correlated/uncorrelated channels and with a practical number of BS antennas, RS achieves significantly higher spectral efficiencies than TIN, SD and SND. Furthermore, we numerically examine the impact of increasing the correlation of the channel across antennas, the number of users as well as the degree of shadow fading. In all cases, we show that RS maintains significant gain over TIN, SD and SND.

On the Generalized Degrees of Freedom of the Noncoherent Interference Channel

We study the generalized degrees of freedom (gDoF) of the block-fading <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">noncoherent</i> 2-user interference channel (IC) with a coherence time of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> symbol durations and symmetric fading statistics. We demonstrate that a standard training-based scheme for the noncoherent IC is suboptimal in several regimes. We study and analyze several alternate schemes: the first is a new noncoherent scheme using rate-splitting. We also consider a scheme that treats interference-as-noise (TIN) and a time division multiplexing (TDM) scheme. We show that a standard training-based scheme for the noncoherent IC is outperformed by one of these schemes in several regimes: our results demonstrate that in the very weak interference regime, the TIN scheme is the best; in the strong interference regime, the TDM scheme and the noncoherent rate-splitting scheme give better performance; in other cases either of the TIN, TDM or noncoherent rate-splitting scheme could be preferred. We also study the noncoherent IC with feedback and propose another noncoherent rate-splitting scheme. Again for the feedback case, our results demonstrate that a standard training-based scheme can be outperformed by other schemes.

Benchmarking and Interpreting End-to-End Learning of MIMO and Multi-User Communication

End-to-end autoencoder (AE) learning has the potential of exceeding the performance of human-engineered transceivers and encoding schemes, without a priori knowledge of communication-theoretic principles. In this work, we aim to understand to what extent and for which scenarios this claim holds true when comparing with fair benchmarks. Our particular focus is on memoryless multiple-input multiple-output (MIMO) and multi-user (MU) systems. Four case studies are considered: two point-to-point (closed-loop and open-loop MIMO) and two MU scenarios (MIMO broadcast and interference channels). For the point-to-point scenarios, we explain some of the performance gains observed in prior work through the selection of improved baseline schemes that include geometric shaping as well as bit and power allocation. For the MIMO broadcast channel, we demonstrate the feasibility of a novel AE method with centralized learning and decentralized execution. Interestingly, the learned scheme performs close to nonlinear vector-perturbation precoding and significantly outperforms conventional zero-forcing. Lastly, we highlight potential pitfalls when interpreting learned communication schemes. In particular, we show that the AE for the considered interference channel learns to avoid interference, albeit in a rotated reference frame. After de-rotating the learned signal constellation of each user, the resulting scheme corresponds to conventional time sharing with geometric shaping.

Cost-Efficient Resources Scheduling for Mobile Edge Computing in Ultra-Dense Networks

With the development of 5G communication technologies and smart mobile devices, various computation-intensive and delay-sensitive tasks continue to increase. The combination of Mobile Edge Computing (MEC) and Ultra-Dense Networks (UDN) increases the network capacity and improves the computing capability of mobile devices, which effectively meets the transmission and computing demands of tasks. However, the ultra-dense deployment of network infrastructures causes energy shortage and channel interference, making it challenging to reduce the system cost. In this paper, we investigate the task offloading and resources scheduling problem in UDN with MEC. In order to minimize the total system cost including delay and energy consumption in the intensive deployment environment of edge servers and base stations (BSs) simultaneously, we design the strategy of task offloading, BS selection and resources scheduling of mobile devices. Because of the complex coupling of decision variables, the original problem is decomposed into two sub-problems. We propose Newton-IPM based Computing Resource Allocation (NICRA) algorithm and Genetic Algorithm based BS Selection and Resources Scheduling (GABSRS) algorithm to solve these two sub-problems, respectively. Then, we prove the number of iterations can be reduced effectively by the GABSRS algorithm while reaching the optimal solution through mathematical analysis. Through experiments analysis, the effectiveness of the GABSRS algorithm is validated.

Decentralized Event-Triggered Scheduling and Control for Multiagent Linear Systems Over Wireless Interference Channels

In this article, we consider a multiagent linear control system, where multiple actuators are tightly coupled with an unstable dynamic plant and connected with a couple of geographically scattered remote controllers over wireless interference channels. We propose a novel decentralized dynamic scheduling and control scheme for multiple control agents, where the associated solutions are fully decentralized with an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">event-triggered</i> structure in the sense that the structure depends on the instantaneous plant state and local channel state for each controller. We establish the closed-form sufficient requirements on the communication resources needed to achieve stabilization of the multiagent system using the Lyapunov drift analysis approach. Numerical results show that our proposed scheme can achieve significant performance gain over various state-of-the-art baselines for scheduling and control of the multiagent system.

Achievable Rate Analysis of Two-Hop Interference Channel With Coordinated IRS Relay

Intelligent reflecting surface (IRS) is a promising 6G technology that can improve wireless communication capacity in a cost-effective and energy-efficient manner, by adjusting a large number of passive reflectors to appropriately change the signal propagation. In this study, we identified the achievable rate region of a two-hop interference channel with distributed multiple IRS relays. To do so, we formulated a non-convex problem that characterizes the rate-profile, and found its solution using successive convex approximation (SCA). We then proposed an alternating direction method of multipliers (ADMM) and alternating optimization (AO) based distributed and low-complex IRS control that maximizes the achievable sum-rate, and proved its convergence and optimality. We then compared the proposed IRS control with semi-definite relaxation (SDR)-, random phase-, deep reinforcement learning (DRL)- based IRS controls, and optimal amplify-and-forward (AF)-, interference neutralization (IN)-, and decode-and-forward (DF) based relaying schemes. We demonstrated that the proposed control with multiple IRS elements outperforms the benchmark controls in terms of the achievable rate region, achievable sum-rate, and energy efficiency under same power budget. We also confirmed that the discrete phase approximation of the proposed control provides near-optimal performance with fewer bits, and the proposed control is robust under imperfect CSI condition. The proposed controls can be efficiently applied to large-scale multi-pair multihop device-to-device and machine-type device communications in the interference-limited or low-powered dense networks of 5G and 6G environments.

Robust Transceiver Design for IRS-Assisted Cascaded MIMO Communication Systems.

Intelligent reconfigurable surfaces (IRSs) have gained much attention due to their passive behavior that can be a successor to relays in many applications. However, traditional relay systems might still be a perfect choice when reliability and throughput are the main concerns in a communication system. In this work, we use an IRS along with a decode-and-forward relay to provide a possible solution to address one of the main challenges of future wireless networks which is providing reliability. We investigate a robust transceiver design against the residual self-interference (RSI), which maximizes the throughput rate under self-interference channel uncertainty-bound constraints. The yielded problem turns out to be a non-convex optimization problem, where the non-convex objective is optimized over the cone of semidefinite matrices. We propose a novel mathematical method to find a lower bound on the performance of the IRS that can be used as a benchmark. Eventually, we show an important result in which, for the worst-case scenario, IRS can be helpful only if the number of IRS elements are at least as large as the size of the interference channel. Moreover, a novel method based on majorization theory and singular value decomposition (SVD) is proposed to find the best response of the transmitters and relay against worst-case RSI. Furthermore, we propose a multi-level water-filling algorithm to obtain a locally optimal solution iteratively. We show that our algorithm performs better that the state of the art in terms of time complexity as well as robustness. For instance, our numerical results show that the acheivable rate can be increased twofold and almost sixfold, respectively, for the case of small and large antenna array at transceivers.

Robust resource allocation for IRS‐assisted secure cognitive radio networks

In this paper, a robust resource allocation problem in an intelligent reflecting surface (IRS) assisted artificial noise (AN)-aided cognitive radio network is investigated. Considering that the channel state information (CSI) of the eavesdropper channel and interference channel cannot be perfectly known in practice, the aim is to minimise the power consumption of the secondary user transmitter (SU-TX) by jointly optimising the transmit beamforming and covariance matrix of AN at the SU-TX as well as the phase shifts of the IRS. The formulated problem is non-convex and challenging to tackle due to the coupling among multiple variables. An efficient alternative optimisation algorithm to solve it by exploiting the S-procedure and semi-definite relaxation. Simulation results demonstrate that the IRS helps in reducing the power consumption significantly even under imperfect CSI conditions.

Multimode Strong Coupling in Cavity Optomechanics

Optomechanical systems show great potential as quantum transducers and information storage devices for use in future hybrid quantum networks. In this context, optomechanical strong coupling can enable efficient, high-bandwidth, and deterministic transfer of quantum states. While optomechanical strong coupling has been realized at optical frequencies, it has proven difficult to identify a robust optomechanical system that features the low loss and high coupling rates required for more sophisticated control of mechanical motion. In this paper, we demonstrate strong coupling in a Brillouin-based bulk cavity optomechanical system in both the single-mode and the multimode strong-coupling regime, which leads to a useful device both for applications in quantum information and for investigating decoherence phenomena in bulk acoustic wave resonators. Using nontrivial mode hybridizations in the strong-coupling regime, we create hybridized photonic-phononic modes with lifetimes that are significantly longer than those of the uncoupled system. This surprising lifetime enhancement, which results from the interference of decay channels, showcases the use of multimode strong coupling as a general strategy to control extrinsic decoherence mechanisms. Moreover, phonons supported by such bulk-acoustic-wave resonators have a collection of properties, including high frequencies, long coherence times, and robustness against thermal decoherence, that make this optomechanical system particularly enticing for applications such as quantum transduction and memories. Hence, this system provides access to phenomena in a previously unexplored regime of optomechanical interactions and could serve as an important building block for future quantum devices.

Modeling of NOMA-MIMO-Based Power Domain for 5G Network under Selective Rayleigh Fading Channels

The integration of multiple-input multiple-output (MIMO) and non-orthogonal multiple access (NOMA) technologies is a hybrid technology that overcomes a myriad of problems in the 5G cellular system and beyond, including massive connectivity, low latency, and high dependability. The goal of this paper is to improve and reassess the bit error rate (BER), spectrum efficiency (SE) of the downlink (DL), average capacity rate, and outage probability (OP) of the uplink (UL) in a 5G network using MIMO. The proposed model utilizes QPSK modulation, four users with different power location coefficients, SNR, transmit power, and two contrasting bandwidths 80 and 200 MHz under selective frequency Rayleigh fading channels. The proposed model’s performance is evaluated using the MATLAB software program. The DL results found that the BER and SE against transmitted power showed the MIMO-NOMA enhanced the BER performance for the best user U4 from 10−1.7 to 10−5.2 at 80 MHz bandwidth (BW), and from 10−1.5 to 10−5 at 200 MHz for transmitting power of 40 dBm. In contrast, the SE performance for the best user U4 is enhanced from 24 × 10−3 to 25 × 10−3 bits/second/Hz at 80 MHz BW and from 19.8 × 10−3 to 20 × 10−3 bps/Hz at 200 MHz BW. Although the outcomes for the UL were obtained in terms of average capacity rate and OP versus SNR at 80, and 200 MHz BW, the MIMO-NOMA result showed that the average capacity rate for the best user U4 performance improves by 12 bps/Hz for 1 dB SNR and the OP is reduced by 15 × 10−3 for 80 MHz BW and by 12 × 10−3 for 200 MHz BW at an SNR of 0.17 dB. As the BW increased the BER, the average capacity rate increased while the SE and OP decreased. For both DL/UL NOMA with and without MIMO, closed-form expressions for BER, SE, average capacity rate, and OP were obtained. All users’ performance, even those whose connections were affected by interference or Rayleigh fading channels significantly improved, when MIMO-NOMA was implemented.

Degrees of Freedom of a K-User Interference Channel in the Presence of an Instantaneous Relay.

In this paper, we study the degrees of freedom (DoF) of a frequency-selective K-user interference channel in the presence of an instantaneous relay (IR) with multiple receiving and transmitting antennas. We investigate two scenarios based on the IR antennas’ cooperation ability. First, we assume that the IR receiving and transmitting antennas can coordinate with each other and that the transmitted signal of each transmitting antenna can depend on the received signals of all receiving antennas, and we derive lower and upper bounds for the sum DoF of this model. In an interference alignment scheme, we divide receivers into two groups called clean and dirty receivers. We design our scheme such that a part of the messages of clean receivers can be de-multiplexed at the IR. Thus, the IR can use these message streams for an interference cancellation at the clean receivers. Next, we consider an IR, the antennas of which do not have coordination with each other and where the transmitted signal of each transmitting antenna depends only on the received signal of its corresponding receiving antenna. We also derive lower and upper bounds for the sum DoF for this model of IR. We show that the achievable sum DoF decreases considerably compared with the coordinated case. In both of these models, our schemes achieve the maximum K sum DoF if the number of transmitting and receiving antennas is more than a finite threshold.

Suppression of crosstalk in multielectrode arrays with local shielding.

Electrical crosstalk can constrain the performance of multielectrode arrays in electro- and neurophysiology, in terms of both stimulation and recording. This is especially so at high electrode density, desirable for spatiotemporal mapping of bioelectrical signals from multiple cells. Channel interference due to crosstalk is currently only partially addressed, via continuous interleaved sampling or post-data acquisition spike sorting. Here, we show that a locally-shielded electrode architecture significantly suppresses crosstalk, and enables multi-site recording at high electrode density without the need for spike sorting. Arrays of shielded electrodes, prepared by micro- and nanofabrication techniques in a vertically-oriented coaxial geometry, demonstrate at least a 400 times improvement in spatial density over the unshielded case.

Another Perspective on Interference Channels for Non-Orthogonal Multiple Access Communications

In this letter, a new perspective on non-orthogonal multiple access (NOMA) is given, relying on the established model of interference channels (IC) from information theory. Establishing links with studies on ICs enables a new framework for the application of NOMA, especially in the context of distributed antenna systems. Thanks to this common framework, a fair and comprehensive evaluation of single antenna NOMA and IC-based NOMA is provided first. Then, a simple transmit coordination scheme, termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">antenna switching</i> , is proposed to switch the IC scenario from strong to weak IC leading to an increase in the achievable capacity under some system and channel conditions. Finally an application example is provided to show the advantage of the proposed approach that enables to match the type of NOMA to the deployment context according to the desired trade off between system throughput and user fairness.

Remote State Estimation of Nonlinear Systems Over Fading Channels via Recurrent Neural Networks

In this article, we consider the remote state estimation for nonlinear dynamic systems with known linear dynamics and unknown nonlinear perturbations. The nonlinear dynamic plant is monitored by multiple distributed sensors over a random access wireless network with shared common radio channel. We focus on the communication strategy and remote state estimation algorithm design so as to achieve a remote state estimation stability subject to unknown nonlinearities in plant and various wireless impairments, such as multisensor interference, wireless fading, and additive channel noise. By exploiting the additive properties of the physical wireless channels, we propose a novel information fusion over-the-air mechanism to address the signal collision and interference among the sensors. Utilizing the partial knowledge on the linear dynamics of the plant, we also propose a novel recurrent neural network (RNN)-based remote state estimator aided by a virtual state estimation mean-square-error (MSE) process. We further propose a novel online training algorithm such that the RNN at the remote estimator can effectively learn the unknown plant nonlinearities. Using the Lyapunov drift analysis approach, we establish closed-form sufficient requirements on the communication resources needed to achieve almost sure stability of both state estimation and RNN online training in high signal-to-noise ratio (SNR) regime. As a result, our proposed scheme is asymptomatic optimal for large SNR in the sense that both the plant state and the unknown plant nonlinearities can be perfectly recovered at the remote estimator. The proposed scheme is also compared with various baselines and we show that significant performance gains can be achieved.

Estimation of Covariance Matrix of Interference for Secure Spatial Modulation Against a Malicious Full-Duplex Attacker

In secure spatial modulation with a malicious full-duplex attacker, how to obtain the interference subspace or channel state information (CSI) is very important for Bob to reduce or even completely cancel the interference from Mallory. In this paper, different from existing work with perfect CSI, the covariance matrix of malicious interference (CMMI) from Mallory is estimated to construct the interference subspace. To improve the estimation accuracy, a CMMI rank detector relying on the Akaike information criterion (AIC) is derived first. To achieve a high-precision CMMI estimation, two methods, principal component analysis-eigenvalue decomposition (PCA-EVD) and joint diagonalization (JD) are proposed. The proposed PCA-EVD is a rank deduction method whereas the JD method is a joint optimization method with improved performance in the low jamming-to-noise ratio (JNR) region at the expense of increased complexity. Simulation results show that the proposed PCA-EVD performs much better than existing methods like sample estimated covariance matrix (SCM) and EVD in terms of normalized mean square error (NMSE) and secrecy rate (SR). Additionally, the proposed JD has achieved a better NMSE performance than PCA-EVD in the low JNR region (JNR <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\leq$</tex-math></inline-formula> 0 dB) while the proposed PCA-EVD performs better than JD in the high JNR region.

Integer programming‐based non‐uniform window decoding schedules for spatially coupled low‐density parity‐check codes

Spatially coupled low-density parity-check (SC-LDPC) codes generally use a window decoding scheme, which is known to yield a near-optimal decoding, compared to full block decoding. Recently, a non-uniform schedule has been proposed to eliminate unnecessary updates of variable nodes within a window: this schedule is generated based on the behaviour of variable node updates analysed by density evolution. Here, the authors present a new non-uniform schedule based on integer programming, whereby the objective functions and constraints are derived from a protograph-based extrinsic information transfer chart. Our design is more flexible than the previous design, because the integer programming-based design allows reduction of update numbers and performance losses through the constraints function, whereas the previous design requires observation of variable node update behaviour. The authors report the performance of their designs of non-uniform schedules in additive white Gaussian noise (AWGN) and inter-symbol interference (ISI) channels. Particularly, in the ISI channel, the authors’ non-uniform schedules are designed with cooperative decoding between a Bahl-Cocke-Jelinek-Raviv (BCJR) detector and an SC-LDPC decoder.

Measurement technology in hypersonic wind tunnel

Integrated airframe/propulsion aerodynamic tests in a hypersonic wind tunnel are critical for developing an air-breathing hypersonic vehicle. Spurred by the shortcomings of traditional wind tunnel testing technology, this paper proposes a new aerodynamic testing technology called the balance-support integrated device (BSD). Additionally, we suggest a BSD optimization design method to improve BSD’s test performance. To reduce the impact of various interference signals on BSD‘s test accuracy, this study proposes an aerodynamic identification technology that effectively eliminates the influence of the model’s inertia force and the impact force generated by the joint BSD. We evaluate BSD’s performance by conducting several calibration tests, which reveal that the sensitivity of each BSD’s test channel is 2.3525 N/μV (drag test channel), 1.2691 N/μV (lift test channel), 9.7386 N.m/μV (pitching moment test channel). The test channel interference of lift to drag is less than 6.3 %, and drag to lift is less than 2.5 %, demonstrating that the wind tunnel force measurement system has an appealing sensitivity and less interference between the channels. Finally, we further challenge BSD’s test accuracy against the mature box balance technology on aerodynamic tests under Ma5.5, Ma6.0, and Ma6.5 conditions considering a 2-meter vehicle model in the Φ600mm pulse combustion wind tunnel. The test results highlight that the maximum test error of the lift test channel, drag test channel, and pitching moment Mz is 1.60 %, 6.45 %, and 4.99 %, respectively, proving that BSD can accurately measure the aerodynamic force during the test.