Radar Coexistence Research Articles

A framework for co-existence of radar and communication with joint design

The integration of both sensing and communication functions is a crucial feature for future communication systems. This paper considers a novel scenario where a radar covers multiple small-cell base stations which operate in different spectra. Due to the limited spectra resource, the radar needs to reuse the spectra of one BS for tracking. To suppress interference and improve performance, we propose a framework including two stages and the corresponding communication and sensing algorithms. Specifically, at the detection stage, we aim to minimize the system transmit power while maintaining the performance of both radar and communication. At the tracking stage, our goal is to maximize the radar sensing performance under a given power budget, while ensuring communication quality. Due to the complexity of the original problem, we address it by introducing auxiliary variables and proposing a penalty dual decomposition-based algorithm, enabling us to solve a more tractable form of the problem. In the inner loop, we propose a concave–convex procedure-based algorithm to handle the optimization problem, while adopting the block coordinate descent algorithm to iteratively update the variables. In the outer loop, we update the penalty term or Lagrange multipliers. Furthermore, we propose a radar target parameter estimation algorithm based on successive interference cancellation, which aims to mitigate communication interference. Finally, numerical simulations demonstrate the effectiveness of the proposed system, and the superior performance of our proposed algorithms over benchmark algorithms.

Designing Sequences for the Coexistence of Radar With Extended Target and Communication Energy Harvesting

Designing Sequences for the Coexistence of Radar With Extended Target and Communication Energy Harvesting

Joint Secure Transmit Beamforming Designs for Integrated Sensing and Communication Systems

Integrated sensing and communication (ISAC), which allows individual radar and communication systems to share the same spectrum bands, is an emerging and promising technique for alleviating spectrum congestion problems. In this paper, we investigate how to exploit the inherent interference from strong radar signals to ensure the physical layer security (PLS) for the considered multi-user multi-input single-output (MU-MISO) communication and colocated multi-input multi-output (MIMO) radar coexistence system. In particular, with known eavesdroppers' channel state information (CSI), we propose to jointly design the transmit beamformers of communication and radar systems to minimize the maximum eavesdropping signal-to-interference-plus-noise ratio (SINR) on multiple legitimate users, while guaranteeing the communication quality-of-service (QoS) of legitimate transmissions, the requirement of radar detection performance, and the transmit power constraints of both radar and communication systems. When eavesdroppers' CSI is unavailable, we develop a joint artificial noise (AN)-aided transmit beamforming design scheme, which utilizes residual available power to generate AN for disrupting malicious receptions as well as satisfying the requirements of both legitimate transmissions and radar target detection. Extensive simulations verify the advantages of the proposed joint beamforming designs for ISAC systems on secure transmissions and the effectiveness of the developed algorithms.

Joint Rate Allocation and Power Control for RSMA-Based Communication and Radar Coexistence Systems

We consider a rate-splitting multiple access (RSMA)-based communication and radar coexistence (CRC) system. The proposed system allows an RSMA-based communication system to share spectrum with multiple radars, which significantly improves spectral efficiency, energy efficiency and quality of service (QoS) of communication users (CUs). Due to the spectrum sharing, the communication network and the radars cause interference to each other, which reduces the signal-to-interference-plus-noise ratio (SINR) of the radars as well as the data rate of the CUs. Therefore, a major problem is to maximize the sum rate of the CUs while guaranteeing their QoS requirements of data transmissions and the SINR requirements of multiple radars. To achieve the objective, we formulate a new problem that optimizes i) common rates of the CUs, ii) transmit power of the common message of the CUs, iii) transmit power of the private messages for the intended CUs, and iv) transmit power of the radar systems. The problem is non-convex, and thus we propose two algorithms. The first sequential quadratic programming (SQP) as the state-of-the-art in nonlinear programming method can quickly return a local optimal solution. The second is an additive approximation scheme (AAS) which solves the problem globally in a reasonable amount of time. Simulation results show the significant improvement of the AAS compared with the SQP in terms of sum rate. Furthermore, with the AAS, the sum rate of the CUs only slightly decreases when the radars' SINR is significantly increased. This implies that the AAS supports the RSMA-based communication system which allows to well coexist with the radars.

Joint antenna selection and waveform design for coexistence of MIMO radar and communications

As the problem of spectral congestion is becoming severe, the coexistence between two primary spectrum users, radar and communications, has spurred extensive research interest. To reduce the mutual interferences between the two functions, MIMO radar waveform design needs to consider the compatibility in both spectral and spatial domains, where the former is achieved by null forming in the frequency domain and the latter is achieved by shaped beampattern synthesis. Additionally, high power efficiency and low system overhead are two desirable characteristics for MIMO radar system design. To this end, we first introduce a new realistic waveform constraint, peak-to-valley-power-ratio (PVPR) constraint per antenna to improve the power efficiency. Then, combined with PVPR constraint, we propose a switchable individual antenna power control scheme to jointly optimize waveforms and antenna locations. We adopt a max–min beampattern matching criterion and impose the ell _{2,1}-norm penalty on the waveform matrix to promote the sparsity of the array. To solve the resultant non-smooth and non-convex problem, we develop a modified alternating directions method of multipliers, where a surrogate subproblem over primal variables is solved instead of the original problem, and its local convergence is analyzed. Finally, numerical experiments demonstrate the effectiveness and superiority of the proposed method over counterparts, especially obtaining the lowest sidelobe level and deeper spectral nulls using much fewer antennas.

FD-JCAS Techniques for mmWave HetNets: Ginibre Point Process Modeling and Analysis

In this paper, we study the co-design of full-duplex (FD) radio with joint communication and radar sensing (JCAS) techniques in millimeter-wave (mmWave) heterogeneous networks (HetNets). Spectral co-existence of radar and communication systems causes mutual interference between the two systems, compromising both the data exchange and sensing capabilities. Focusing on the detection performance, we propose a cooperative detection technique, which exploits the sensing information from multiple base stations (BSs), aiming at enhancing the probability of successfully detecting an object. Three combining rules are considered, namely the <i>OR</i> , the <i>Majority</i> and the <i>AND</i> rule. In real-world network scenarios, the locations of the BSs are spatially correlated, exhibiting a repulsive behavior. Therefore, we model the spatial distribution of the BSs as a <inline-formula><tex-math notation="LaTeX">$\beta$</tex-math></inline-formula> -Ginibre point process ( <inline-formula><tex-math notation="LaTeX">$\beta$</tex-math></inline-formula> -GPP), which can characterize the repulsion among the BSs. By using stochastic geometry tools, analytical expressions for the detection performance of <inline-formula><tex-math notation="LaTeX">$\beta$</tex-math></inline-formula> -GPP-based FD-JCAS systems are expressed for each of the considered combining rule. Furthermore, by considering temporal interference correlation, we evaluate the probability of successfully detecting an object over two different time slots. Our results demonstrate that our proposed technique can significantly improve the detection performance when compared to the conventional non-cooperative technique.

Spectral-Compatible Transmit Beampattern Design With Minimum Peak Sidelobe for Narrowband MIMO Radar

Spectral-compatible radar emission has a paramount importance in realizing the coexistence of radar with wireless communications. In this paper, we deal with the design of spectral-compatible transmit beampattern with minimum peak sidelobe level for a narrowband multiple-input multiple-output(MIMO) radar. We also consider constraints that are imposed due to the practical high power amplifier(HPA) used in modern radars. The constraints are used to control the dynamic range on the magnitude of each signal, to control variations in the transmit power from the individual antennas and the total energy of the signals. The considered problem is challenging as it is non-convex. To this end, we propose an iterative solution that incorporates the majoriztion-minimization(MM) and alternating direction method of multipliers(ADMM) frameworks. Our solution avoids the computationally expensive operations such as matrix inverse and eigenvalue decomposition. We provide numerical results to validate the proposed solution. The results show that the method provides the intended spectral-compatible beampattern while maintaining a beampattern synthesize performance that is comparable to the state-of-the-art work.

Performance analysis of communications systems with radar interference and hardware impairment

The development of future wireless communications systems faces a big challenge of spectrum scarcity. Co-existence of radar and communications systems is thus of great interest. In this work, the performance of a communications system with hardware impairment (HWI) as well as interference from radar systems will be studied. The impact of radar interference, I/Q imbalance coefficients as well as channel state information (CSI) will be evaluated in terms of outage probability and symbol error rate. Simulation results prove that the proposed detectors provide explicit and conducive insights for further exploration of joint radar-communications designs.

RIS-Assisted Communication Radar Coexistence: Joint Beamforming Design and Analysis

Integrated sensing and communication (ISAC) has been regarded as one of the most promising technologies for future wireless communications. However, the mutual interference in the communication radar coexistence system cannot be ignored. Inspired by the studies of reconfigurable intelligent surface (RIS), we propose a double-RIS-assisted coexistence system where two RISs are deployed for enhancing communication signals and suppressing mutual interference. We aim to jointly optimize the beamforming of RISs and radar to maximize communication performance while maintaining radar detection performance. The investigated problem is challenging, and thus we transform it into an equivalent but more tractable form by introducing auxiliary variables. Then, we propose a penalty dual decomposition (PDD)-based algorithm to solve the resultant problem. Moreover, we consider two special cases: the large radar transmit power scenario and the low radar transmit power scenario. For the former, we prove that the beamforming design is only determined by the communication channel and the corresponding optimal joint beamforming strategy can be obtained in closed-form. For the latter, we minimize the mutual interference via the block coordinate descent (BCD) method. By combining the solutions of these two cases, a low-complexity algorithm is also developed. Finally, simulation results show that both the PDD-based and low-complexity algorithms outperform benchmark algorithms.

Precoder and Decoder Co-Designs for Radar and Communication Spectrum Sharing.

The coexistence of radar and communication systems is necessary to facilitate new wireless systems and services due to the shortage of the useful radio spectrum. Moreover, changes in spectrum regulation will be introduced in which the spectrum is allocated in larger chunks and different radio systems need to share the spectrum. For example, 5G NR, LTE and Wi-Fi systems have to share the spectrum with S-band radars. Managing interference is a key task in coexistence scenarios. Cognitive radio and radar technologies facilitate using the spectrum in a flexible manner and sharing channel awareness between the two subsystems. In this paper, we propose a nullspace-based joint precoder–decoder design for coexisting multicarrier radar and multiuser multicarrier communication systems. The maximizing signal interference noise ratio (max-SINR) criterion and interference alignment (IA) constraints are employed in finding the precoder and decoder. By taking advantage of IA theory, a maximum degree of freedom upper bound for the -radar-communication-user interference channel can be achieved. Our simulation studies demonstrate that interference can be practically fully canceled in both communication and radar systems. This leads to improved detection performance in radar and a higher rate in communication subsystems. A significant performance gain over a nullspace-based precoder-only design is also obtained.

Joint waveform and precoding design for coexistence of MIMO radar and MU‐MISO communication

The joint design problem for the coexistence of multiple-input multiple-output (MIMO) radar and multi-user multiple-input-single-output (MU-MISO) communication is investigated. Different from the conventional design schemes, which require defining the primary function, we consider designing the transmit waveform, precoding matrix and receive filter to maximize the radar SINR and the minimal SINR of communication users, simultaneously. By doing so, the promising overall performance for both sensing and communication is achieved without requiring parameter tuning for the threshold of communication or radar. However, the resulting optimization problem which contains the maximin objective function and the unit sphere constraint, is highly nonconvex and hence difficult to attain the optimal solution directly. Towards this end, the epigraph-form reformulation is first adopted, and then an alternating maximisation (AM) method is devised, in which the Dinkelbach’s algorithm is used to tackle the nonconvex fractional-programing subproblem. Simulation results indicate that the proposed method can achieve improved performance compared with the benchmarks.

Editorial: Introduction to the Issue on Joint Communication and Radar Sensing for Emerging Applications

The papers in this special section focuses on the exploitation of the radar spectrum for use of commercial wireless communication, as well as emerging applications requiring joint communication and sensing designs. The integration of radar and communication systems has recently attracted a lot of research and commercial interest. The emergence of spectrum-hungry applications have necessitated the exploitation of the permanently allocated, but potentially under-utilized spectral resources, and sharing the frequency bands between radar and communication systems has attracted substantial attention. Below 10 GHz, a large portion of spectral resources are primarily allocated to radar systems, which have seen increasing cohabitation with wireless communication systems. At the higher frequencies such as the millimeter-wave bands, the communication and radar platforms are also expected to coexist harmoniously. Nevertheless, with the allocation of the available frequency bands to the above wireless technologies, the interference in the radar bands is on the rise, and has raised concerns both from governmental and military organizations for the safeguarding of critical radar operations. With achieving spectral coexistence as one of its goals, research effort is well underway to address the issue of the spectral coexistence of communication and radar. Recognising the opportunities arising beyond coexistence, there has been a recent surge in research in designing joint communication and radar (JCR) systems, that go beyond managing interference between the two transmissions, to designing multi-functional transmissions that simultaneously serve the sensing and the communications functionalities.

A view on radar and communication systems coexistence and dual functionality in the era of spectrum sensing

In this paper, we discuss the state of radio frequency (RF) coexistence and how it benefits from dynamic spectrum sensing. We categorize coexistence of radar and communications in terms of their cooperation and non-cooperation in using the spectrum as well as their roles as primary, secondary, and dual users of the frequency bands. We describe the ways the radar can alter its parameters in response to the sensed spectrum through the completion of the cognitive perception-action cycle. The paper takes a broad view of the field and puts in context coordination of the two RF services through co-design, dual function, signal as well as system of opportunities. We present possible future research directions which will enable further innovations and progress in spectrum sharing and RF interference avoidance and mitigation.

FD-JCAS Techniques for mmWave HetNets: Ginibre Point Process Modeling and Analysis

In this paper, we study the co-design of full-duplex (FD) radio with joint communication and radar sensing (JCAS) techniques in millimeter-wave (mmWave) heterogeneous networks (HetNets). Spectral co-existence of radar and communication systems causes mutual interference between the two systems, compromising both the data exchange and sensing capabilities. Focusing on the detection performance, we propose a cooperative detection technique, which exploits the sensing information from multiple base stations (BSs), aiming at enhancing the probability of successfully detecting an object. Three combining rules are considered, namely the \textit{OR}, the \textit{Majority} and the \textit{AND} rule. In real-world network scenarios, the locations of the BSs are spatially correlated, exhibiting a repulsive behavior. Therefore, we model the spatial distribution of the BSs as a $\beta$-Ginibre point process ($\beta$-GPP), which can characterize the repulsion among the BSs. By using stochastic geometry tools, analytical expressions for the detection performance of $\beta$-GPP-based FD-JCAS systems are expressed for each of the considered combining rule. Furthermore, by considering temporal interference correlation, we evaluate the probability of successfully detecting an object over two different time slots. Our results demonstrate that our proposed technique can significantly improve the detection performance when compared to the conventional non-cooperative technique.

A Brief Introduction on Joint Radar and Communication Systems

Joint radar and communication (JRC) technology is gradually becoming an essential approach to alleviating spectral congestion. Radar and communications systems were designed with common spectral and hardware resources to reduce size, improve performance, reduce cost, and decongest the spectrum. Various approaches have been proposed to achieve the coexistence of radar and communication systems. This paper mainly focuses on the research directions of radar communication coexistence (RCC) and dual-function radar communication systems (DFRC) in JRC technology. We summarize and analyze the existing research problems in the JRC era. According to the characteristics and advantages of JRC technology, we highlight several potentials in military and commercial applications.

Constraint Waveform Design for Spectrum Sharing Under Coexistence of Radar and Communication Systems

Waveform design and spectrum sharing between Multiple Input Multiple Output (MIMO) radar and MIMO communication system is an optimization problem that has been typically addressed in literature with two-dimensional formalism involving radius and azimuth angles. In this paper, we address the problem and associated spectrum sharing constraints by the inclusion of an additional elevation angle. The design uses Finite Alphabet Constant Envelope (FACE) Binary Phase Shift Keying (BPSK) waveforms to formulate the covariance matrices. Through machine learning, a nonlinear optimization problem with constraints is converted to an optimization problem without constraints. The design criteria for the radar waveform does not interfere with the communication system. This is done by carefully selecting the base station (BS) and steering nulls towards it, which guarantees the least degradation in the radar's performance. We designed BPSK waveforms for spectral coexistence between MIMO radar and MIMO cellular communication system through different relaying protocols. Probability of detection and signal to noise ratio is formulated for different relaying protocols. The radar is capable of detecting a target in the air through azimuth as well as by elevation angle. We also showed that the desired covariance matrix is positive semi definite and radar can share the spectrum while detecting the target. We also showed a minimum square error for both angles based on the algorithm.

Robust Interference Cancellation for Vehicular Communication and Radar Coexistence

Spectrum sharing of wireless vehicle-to-vehicle (V2V) communication and automotive radar in intelligent transportation systems (ITS) can provide higher spectrum utilization efficiency. However, spectrum sharing between two systems might bring severe interference, which needs to be well solved. To address the communication-radar spectrum sharing (CRSS) and inter-system interference issue, we first model the radar interference estimation as an off-grid compressed sensing problem. Then, we propose an interference cancellation algorithm based on the atomic norm (AN) minimization theory. Simulation results show that the proposed algorithm facilitates the coexistence between radar and communication and improves the V2V communication performance efficiently in the presence of automotive radar interference.

Communication‐awareness joint beams and power allocation scheme of radar network for manoeuvring targets tracking

The coexistence of radar and communication system is a crucial task owing to the shortage of spectrum resources. In this study, the authors consider a multiple manoeuvring targets tracking problem via a radar network in the presence of several non-cooperative, spatially random, and spectral overlapped communication areas (CAs). Instead of costly inner pattern optimisation, a communication awareness joint beam and power allocation (CJBPA) scheme of radar network is proposed to achieve high flexibility in coexistence. In CJBPA, radars and CAs treat the signals from each other as interference, which are formulated and discussed from the perspective of spectrum and space. The CJBPA optimises the overall tracking performance, which is characterised by the posterior Cramer-Rao lower bound under the consideration of coexistence. The resultant non-convex problem is relaxed and decoupled as an integrated two-staged optimisation. To accelerate the numerical procedures of the optimisations, custom-built primal dual interior point methods are derived by the structure information of the problems. The effectiveness of the proposed CJBPA scheme is assessed through simulations, showing that by using spatial and spectral information of undesired signals, the tracking performance can be optimised while the impacts of interference on both radars and CAs are restricted.

Simultaneous Radar-Communication Systems Using Controlled Chaos-Based Frequency Modulated Waveforms

With the increase in demand for spectral resources and bandwidth constraints, efficient solutions for the coexistence of radar and communication systems are needed. Simultaneously, the development of multifunctional radio frequency (RF) systems with less hardware have received considerable attention. Most previous work on coexistence has focused on hardware design and mitigation of interference between radar and communication systems. This work proposes, a novel method for controlling a chaotic trajectory, which allows for the coexistence of both radar and communication systems. Binary information can be encoded in a chaotic state by adjusting its trajectory. In this approach, a state variable is selected to control the trajectory and generate a controlled chaos-based frequency modulated (CCBFM) waveform for joint radar-communication system signal transmission. We also design a communication receiver to decode the information and a radar receiver that extracts the signature of the target are designed accordingly. The performance of the controlled chaotic communication system is assessed in terms of the bit error ratio (BER). The analysis of the communication system shows that the CCBFM receiver performs reasonably well compared to a half-sine pulse frequency modulated (HSPFM) receiver. Analysis of the radar system performance is assessed using the entropy of the target's signature. The use of a CCBFM waveform leads to accurate target detection and classification for a signal-to-noise ratio as low as -30 dB. These analyses demonstrate that a CCBFM waveform can be successfully used for joint radar-communication systems in a shared spectrum.

Joint Power Allocation for Radar and Communication Co-Existence

Co-existence of radar and communication systems based on cooperative spectrum sharing is of significant interest in recent years. This letter proposes two joint power allocation schemes for radar and communication spectrum sharing, where both systems use the same bandwidth with cross interference between them. The proposed joint design maximizes a performance metric of one system while meeting a service constraint requirement for the other, i.e., throughput for the communication system or signal-to-interference-plus-noise ratio (SINR) for the radar. For both designs, we show that either the radar or the communication system needs to transmit at peak power to achieve the optimum solution, depending on the relation among the peak power constraint, channel conditions, and service constraints.