1
Introduction to Joint Communications and Sensing (JCAS)

1.1 Background

Wireless communications and radar sensing have been advancing in parallel for decades. Numerous new system architectures and algorithms have been developed in the names of new generation wireless communications systems and modern radar, respectively. However, despite the fact that they share many commonalities in terms of signal processing algorithms, devices and, to certain extent, system architecture, there have been very limited intersections between the designs and the deployment of the two systems. Chiefly motivated by spectrum and cost sharing and energy saving, we are witnessing a rapidly growing interest in the coexistence, cooperation, and, most importantly, joint design of the two systems recently [1-5].

The coexistence of communication and radar systems is not new, and the issue has been extensively studied in the past decade. The focus was on developing efficient interference management techniques in order for the two individually deployed systems to operate simultaneously without interfering with each other [6]. In this setup, radar and communication systems may be colocated and or spatially separated, and they may transmit two different signals overlapped in time and/or frequency domains. They can operate simultaneously by sharing the same resources cooperatively, with a goal of minimizing interference to each other. Great efforts have been devoted to mutual interference cancelation in this case, using, for example, beamforming design, cooperative spectrum sharing, opportunistic primary-secondary spectrum sharing, and dynamic coexistence. However, effective interference cancelation typically has stringent requirements on the mobility of nodes and information exchange between them. The spectral efficiency improvement is hence limited in such schemes.

Since the interference in coexisting systems is caused by transmitting two separate signals, it is natural to ask whether it is possible to use one single transmitted signal for both communications and radar sensing. Radar systems typically use specially designed waveforms such as short pulses and chirps, which enable high-power radiation and simple receiver processing. However, these waveforms are not necessarily required for radar sensing. Passive radar or passive sensing is a good example of exploring diverse radio signals for sensing [7, 8]. In principle, the objects to be sensed or detected can be illuminated by any radio signals of sufficient power, such as TV signals, Wi-Fi signals, and mobile (cellular) signals. This is because the propagation of radio signals is always affected by the static and dynamic environments such as transceiver movement, surrounding objects' movement and profile variation, and even weather changes. Hence, the environmental information is embedded in the received radio signals and can be extracted by using passive radar techniques. However, there are two major limitations with passive sensing. First, the clock phases between transmitter and receiver are not synchronized in passive sensing, and there are always unknown and possibly time-varying timing, frequency, and phase offsets between the transmitted and received signals. This leads to timing and therefore ranging ambiguity in the sensing results, as well as causing difficulties in aggregating multiple measurements for joint processing. Second, the sensing receiver may not know the signal structure. As a result, passive sensing lacks the capability of interference suppression, and it cannot separate multiuser signals from different transmitters. Admittedly, the radio signals are usually not optimized for sensing in any way.

The most recent trend is that radar systems are evolving toward more general radio sensing. We prefer the term "radio sensing" to radar due to its generality and comprehensiveness. Radio sensing here refers to retrieving information from received radio signals; this is in contrast to extracting information from the communication data modulated to the signal at the transmitter. It can be achieved through the measurement of sensing parameters related to location and movement, such as time delay, angle-of-arrival (AoA), angle-of-departure (AoD), Doppler frequency, and magnitude of multipath signals, and physical feature parameters such as inherent "radio signature" of devices/objects/activities. The two corresponding processing activities are called sensing parameter estimation and pattern recognition in this book. In this sense, radio sensing refers more to general sensing techniques and applications using radio signals, just like video sensing using video signals. Radio sensing has a diverse range of applications such as object, activity, and event recognition in Internet of Things (IoT), Wi-Fi, and 5G networks. These radio signals are transmitted by an existing infrastructure and are not specifically designed for sensing purpose. The paper [9] presents numerous Wi-Fi sensing applications where, for instance, Wi-Fi signals have been used for people and behavior recognition in indoor environments. In [10], it is shown that other radio signals, such as radio-frequency identification (RFID) and ZigBee, can also be used for activity recognition. These publications demonstrate the strong potential of using low-bandwidth communication signals for radio-sensing applications.

Joint communications and radar/radio sensing (JCAS) [11, 12] is emerging as an attractive solution to integrating communications and sensing into one system. It has also been known under different terms, such as radar-communications (RadCom) [1], joint radar (and) communications (JRC) [3, 13, 14], joint communications (and) radar (JCR) [15], dual-function(al) radar communications (DFRC) [16, 17], and more recently, integrated sensing and communications (ISAC). In a JCAS system, a single transmitted signal for both communications and sensing is jointly designed and employed. The objective for JCAS is that the majority of transmitter modules can be shared by communications and sensing. In such a system, most of the receiver hardware can also be shared, but some receiver baseband signal processing would be different for communications and sensing. By virtue of joint design, JCAS can also potentially overcome the many limitations in passive sensing. These properties make JCAS significantly different from existing spectrum sharing concepts such as cognitive radio, the aforementioned coexisting communication-radar systems, and "integrated" systems using separated waveforms [18] where communications and sensing signals are separated in such resources as time, frequency, and code, despite the two functions may physically be combined in one system. In Table 1.1, we briefly compare the signal formats and key features, advantages, and disadvantages of five types of systems: communications and sensing with separated waveforms, coexisting communications and sensing, passive sensing, cognitive radio, and JCAS.

1.2 Three Categories of JCAS Systems

The initial concept of integrated communications and sensing may be traced back to the 1960s [3] and had been primarily investigated for developing multimode or multifunction military radars. In early days, most of such systems belonged to the type in which communications and sensing use separated waveforms, as detailed in Table 1.1. There has been very limited research on JCAS for civil systems before 2010. In the past 10 years, JCAS has been receiving rapidly growing interest and is being considered as a candidate for next generations of communications, radar, and sensing systems.

Based on the design priority and the underlying signal formats, the current JCAS systems may be classified into the following three categories:

• Communication-centric design: In this class, radio sensing is an add-on to a communication system, where the design priority is on communications. The aim of such a design is to exploit communication waveform to extract sensing information through target echoes. Enhancements to hardware and algorithms are required to support radio sensing. Possible enhancements to communication standards may be introduced to enable better reuse of the communication waveform for radio sensing. In this design, the communication performance can be largely unaffected; however, the sensing performance may be scenario-dependent and difficult-to-optimize.

  Table 1.1 Comparison of communications and sensing (C&S) with separated waveforms, coexisting communications and sensing, passive sensing, cognitive radio, and JCAS.

  Systems Signal formats and key features Advantages Disadvantages C&S with separated waveforms (e.g. [18])
  1. - C&S signals are separated in time, frequency, code and/or polarization
  2. - C&S hardware and software are partially shared
  1. - Low mutual interference
  2. - Almost independent design of C&S waveforms
  1. - Low-spectrum efficiency
  2. - Low order of...