Integrated sensing and communication (ISAC) plays a crucial role in the development of 6G networks. This study focuses on an ISAC scenario that utilizes a dedicated sensing reference signal (SRS). Similar to the position reference signal (PRS) in 5G, the SRS can be repurposed as other communication reference signals, leading to resource savings. However, it is important to note that sensing is more sensitive to power and is susceptible to severe multi-target interference. To address this issue, the paper proposes the incorporation of matched windows at both the transmitter and receiver ends. This approach aims to enhance energy efficiency by mitigating windowing mismatch loss. To achieve arbitrary window shapes in the frequency-domain while maintaining a constant amplitude waveform, the paper introduces discrete non-linear frequency modulation (DNLFM). DNLFM utilizes a limited number of Newton iterations and a geometrically-equivalent method to reduce waveform generation complexity. This method allows for timely adjustment of parameters based on changing sensing requirements. Additionally, the paper proposes the use of spatial-domain matched windows to minimize sidelobes. Simulation results demonstrate that the proposed methods outperform conventional schemes, highlighting their effectiveness in improving performance.

Recently, a two-dimension (2D) modulation waveform of orthogonal time-frequency-space (OTFS) has been a popular 6G candidate to replace existing orthogonal frequency division multiplexing (OFDM). The extensive OTFS researches help to make both the advantages and limitations of OTFS more and more clear. The limitations are not easy to overcome as they come from OTFS on-grid 2D convolution channel model. Instead of solving OTFS inborn challenges, this paper proposes a novel 2D modulation waveform named orthogonal time-frequency division multiplexing (OTFDM). OTFDM uses a 2D dot-product channel model to cope with doubly-selectivity. Compared with OTFS, OTFDM supports grid-free channel delay and Doppler and gains a simple and efficient 2D equalization. The concise dot-division equalization can be easily combined with MIMO. The simulation result shows that OTFDM is able to bear high mobility and greatly outperforms OFDM in doubly-selective channel.

Joint communication and sensing (JCAS) is a very promising 6G technology, which attracts more and more research attention. Compared with communication, radar has many unique features in terms of waveform design criteria, self-interference cancelation (SIC), aperture-dependent resolution, and virtual aperture. This article proposes a novel waveform design named max-aperture radar slicing (MaRS) to gain a large time-frequency aperture, which is generated by orthogonal frequency division multiplexing (OFDM) and occupies only a tiny fraction of OFDM resources. The proposed MaRS keeps the radar advantages of constant modulus, zero auto-correlation sequence, and simple SIC. As MaRS consumes much less resources, conventional processing methods fail, and novel angle-Doppler map-based methods are proposed to obtain the range-velocity-angle information from MaRS echos and strong clutters. To avoid complex full-duplex communication, this article proposes a hybrid-duplex JCAS scheme composed of half-duplex communication and full-duplex radar. The half-duplex communication antenna array is reused, and a small sensing-dedicated antenna array is added. Using these two arrays, a large space-domain sensing aperture is virtually formed to greatly improve the angle resolution. The numerical results show that the proposed MaRS and hybrid duplex can achieve a high sensing resolution with only 0.4% OFDM resources, which reduces the overheads of conventional methods to less than one tenth.

Cell-free massive multi-input multi-output (MIMO) provides ubiquitous connectivity for multiple users. Compared with co-located massive MIMO, the major cost includes fronthaul and access points (AP). This paper assumes an implementation using radio stripes. Maximum ratio combining (MRC) uses a low-loading fronthaul and low-cost APs, but the performance is bad. To solve these problems, this paper first proposes an SVD-based method named quasi-LMMSE (Q-LMMSE). Q-LMMSE is derived from standard linear minimum- mean-square-error (LMMSE) using only the MRC frounthaul signals. Employing the simple MRC fronthaul design, a novel processing method is derived from standard linear minimum- mean-square-error (LMMSE). Simulation results show that the proposed Q-LMMSE gains a higher SE with low fronthaul loading, AP complexity, and latency than existing distributed schemes and performs even better than centralized LMMSE in some cases.

Massive MIMO provides a high spatial degree of freedom (DoF) to support multiple users. To gain the spatial DoF, accurate channel information is crucial, and the pilot is important to obtain it. However, in grant-free transmissions, different users may select the same pilot, which leads to pilot collisions. To solve this problem, this paper proposes an irregular superimposed multi-pilot. The proposed superimposed structure provides a large multi-pilot pool than the conventional cascaded one. Using this structure, the number of single-pilots in multi-pilot can be different, and the pilot number distribution is optimized via a novel Monte-Carlo-based differential evolution. The simulation results verify the analysis and show that the proposed method outperforms existing works.

Due to the limited number of traditional orthogonal pilots, pilot collision will severely degrade the performance of contention-based grant-free transmission. To alleviate the pilot collision and exploit the spatial degree of freedom as much as possible, an extremely sparse orthogonal pilot scheme is proposed for uplink grant-free transmission. The proposed sparse pilot is used to perform active user detection and estimate the spatial channel. Then, inter-user interference suppression is performed by spatially combining the received data symbols using the estimated spatial channel. After that, the estimation and compensation of wireless channel and time/frequency offset are performed utilizing the geometric characteristics of combined data symbols. The task of pilot is much lightened, so that the extremely sparse orthogonal pilot can occupy minimized resources, and the number of orthogonal pilots can be increased significantly, which greatly reduces the probability of pilot collision. The numerical results show that the proposed extremely sparse orthogonal pilot scheme significantly improves the performance in high-overloading grant-free scenario.

Modern random access avoids scheduling overheads and greatly improves the transmission efficiency of small packets. The major challenge is the random collision, and slotted ALOHA (SA)-based methods were proposed to cancel collisions via the receiving time slot diversity. Based on power-domain multiple access (PDMA), some nonorthogonal multiple access (NOMA) SA methods increased the active user number. This article refines PDMA-based methods at the first step, including: 1) the existing NOMA irregular repetition SA is enhanced and 2) NOMA coded SA is proposed. However, PDMA-based methods require accurate sensing and power control to separate multiple users in the power domain, which is not friendly to low-cost devices. This article proposes a NOMA SA method named spreading SA (SSA), which does not rely on any sensing or power control. Both physical and medium access control layers are considered, and the outage model, instead of the collision model, is proposed to be used for NOMA SA. SSA uses random nonorthogonal code spreading to reduce collisions as a relatively large number of codes can be employed. Compared with the power domain, the code domain gains a much higher degree of freedom. It can be utilized without any coordination with the help of blind detection technologies. Moreover, collision resolution diversity SSA (CRDSSA) is proposed to further improve the user loading. The simulation results validate the analysis and show that the proposed SSA-based methods support a higher user loading and much higher flexibility than existing NOMA SA works in most cases.

In truly grant-free (TGF) transmissions, pilot is crucial to fully exploit the user separation capability of spatial domain. Based on pilots, joint active user detection and channel estimation can be done. The state-of-art work suggests to use the recovered data to improve the channel estimation accuracy. In this paper, a novel data-assisted algorithm is proposed. This algorithm jointly utilizes the recovered and unrecovered data to further improve the performance. The constant modulus (CM) feature is used as the optimization target. To obtain an efficient convergence, a fixed modulus version of CM is employed, and multiple relatively good spatial combining vectors are normalized and used as the initial values of the quasi-Newton iterations. Furthermore, a target function of post signal to interference plus noise ratio is proposed to gain a better performance and faster convergence. The simulation results show that the proposed method achieves a tremendous performance gain, especially when more receiving antennas are employed.

Autonomous grant-free data-only transmissions greatly simplify machine type communications, but present many challenges. One of them is the compressed sensing multiple measurement vector (MMV) problem of user detection. The sensing matrix is very underdetermined, and the amount of measurement vectors is large, which affect performance and complexity, respectively. In this paper, a fast power reconstruction (FPR) algorithm is proposed. FPR simplifies MMV to single measurement vector, and no iterations is required, which reduce the complexity. The row dimension of sensing matrix is expanded, and thus the performance is improved. The simulation results validate its good performance and ultra-low computational complexity.

Contention-based grant-free transmission is very promising for future massive machine-type communication (mMTC). In contention-based transmission, the random pilot collision becomes a challenge. To solve it, multi-pilot scheme is proposed. However, the existing work relies on the low correlation of spatial channels, and cannot be applied when the number of antennas is relatively small. This paper proposes a novel independent multi-pilot scheme, which utilizes the diversity of multiple pilots, instead of the spatial correlation. The interference cancellation of both data symbols and multiple pilots is utilized to improve the performance. The simulation results show that the proposed scheme significantly improves the performance in high-overloading mMTC and outperforms the existing work in a massive antenna array case.

Multi-user shared access (MUSA) is an autonomous grant- free and high overloading non-orthogonal transmission technology. However, the performance degrades when combining MUSA with discrete Fourier transform spreading OFDM (DFT-s-OFDM) directly. To solve this problem, the real Fourier-related transform spreading methods are researched which are able to reduce the peak-to-average power ratio (PAPR) and increase the stability against channel fading. Furthermore, it enables the receiver to blindly estimate time offset (TO) and frequency offset (FO). The simulation results show that the proposed system performs very well in a frequency selective channel model containing multipath, TO and FO.

In this paper, a novel blind multi-user detection( MUD) framework for autonomous grant-free(AGF) high-overloading non-orthogonal multiple access(NOMA) is introduced in detail aimed at fulfilling the requirements of 5G massive Machine-Type Communication(mMTC)and beyond. From the perspective of the transmitter side,characteristics of diverse types of emerging grant-free transmission, particularly autonomous grant-free(AGF), are elaborated and presented in a comparative manner. In the receiver end, codeword-level successive interference cancellation (CL-SIC) is revealed as the main framework to perform MUD. In addition, underpinning state-of-art blind MUD techniques such as blind activity detection taking advantage of the statistics of the aggregate signals, blind equalization based on the simple geometric characteristics of low order modulation constellation symbols, and blind channel estimation employing the successfully decoded codewords are explained.

In this paper, a blind multiple user detection for multi-user shared access systems (MUSA) is introduced for massive machine type communication (mMTC). Without relying on reference signal to estimate the channel state information, user traffic signal is detected and decoded via a unique blind detection algorithm. The successfully decoded signal is employed as ``pilot'' for channel estimation which would be refined as more signals are successfully decoded. High-overloading can be achieved for grant-free transmission of random signature selection, with relatively low complexity receiver, which are preferred by mMTC.

Internet of things (IoT) is widely expected to be an important scenario in the fifth generation (5G) wireless network. Major challenges of IoT include the low cost of devices, low energy consumption, low latency and the ability to support a large number of simultaneous connections. In this article, a new type of non-orthogonal multiple access scheme called multi-user shared access (MUSA) is proposed to support IoT. MUSA adopts a grant-free access strategy to simplify the access procedure significantly and utilizes advanced code domain non-orthogonal complex spreading to accommodate massive number of users in the same radio resources. A family of complex sequences with short length is chosen as spreading sequence for its ability to enable simple and robust successive interference cancellation at the base station side and cope with high user load. Simulation results show that MUSA can achieve significant gain in user overloading performance compared to orthogonal systems, while incurring much lower control overhead.