We consider the unsourced random access problem with multiple receivers and propose a cell-free type solution. In our proposed scheme, active users transmit their signals to the access points (APs) distributed in a geographical area and connected to a central processing unit (CPU). The transmitted signals are composed of a pilot and a polar codeword, where the latter occupies only a small fraction of the data part of the transmission frame. The receiver operations of pilot detection and channel and symbol estimation take place at the APs, while the actual message bits are detected at the CPU by combining the symbol estimates from different APs. The effect of successfully decoded messages is then subtracted at the APs by successive interference cancellation, and the decoding iterations continue with the residual signal. Numerical examples illustrate that the proposed scheme can support up to 1400 users with high energy efficiency, and the distributed structure decreases the error probability by more than two orders of magnitude.

We investigate the unsourced random access scheme assuming that the base station is equipped with multiple antennas, and propose a high-performing solution utilizing on-off-division multiple access. We assume that each user spreads its pilot sequence and polar codeword to the pilot and data parts of the transmission frame, respectively, based on a transmission pattern. The iterative receiver operation consists of pilot and pattern detection followed by channel vector and symbol estimation, polar decoding, and successive interference cancellation. Numerical findings demonstrate that the proposed scheme has superior performance compared to the state-of-the-art in various antenna settings.

We consider unsourced random access over fading channels with a massive number of antennas at the base station, and propose a simple, yet energy-efficient solution by dividing the transmission frame into slots. We utilize non-orthogonal pilot sequences followed by a polar codeword for transmission in each slot. At the receiver side, we first detect the transmitted pilot sequences by employing a generalized orthogonal matching pursuit algorithm and utilize a linear minimum mean square error solution to estimate the channel vectors. We then perform an iterative decoding based on maximal ratio combining, single-user polar decoding, and successive interference cancellation with re-estimation of the channel vectors to recover the data bits. We also analyze the performance of the proposed scheme using normal approximations and provide a detailed complexity analysis. Numerical examples demonstrate that the proposed scheme either outperforms the existing schemes in the literature or has a competitive performance with a lower complexity. Furthermore, it is suitable for fast-fading scenarios due to its excellent performance in the short blocklength regime.

We consider unsourced random access for which the base station is equipped with a massive number of antennas and there are residual hardware impairments at both the base station and the user equipment. We divide the transmission frame into slots where each user sends a non-orthogonal pilot selected based on part of its message bits followed by its data bits encoded by a polar code. At the receiver side, we first identify the selected pilot sequences by a generalized orthogonal matching pursuit algorithm and estimate the user channels employing a newly developed hardware-impairment aware linear minimum mean-squared error solution. We then perform symbol estimation by maximal ratio combining and data decoding by a single-user polar decoder followed by successive interference cancellation in an iterative fashion. Numerical examples illustrate that hardware impairments degrade the system performance; however, the proposed solution alleviates this loss in terms of both energy efficiency and the number of supported active users.

We consider unsourced random access over fading channels with a massive number of antennas at the base station and propose a simple yet energy-efficient solution by dividing the transmission frame into slots where each slot is also divided into pilot and data parts. We utilize non-orthogonal pilot sequences selected based on part of the information bits, and encode the remaining message bits with a polar code for transmission. At the receiver side, we first detect the transmitted pilot sequences by employing the generalized orthogonal matching pursuit algorithm, and utilize a linear minimum mean square error solution to estimate the channel vectors. We perform symbol estimation by maximal ratio combining, and pass the symbol estimates to a single-user polar decoder to recover the data bits with succes-sive cancellation list decoding, along with successive interference cancellation at the end of each iteration. Numerical examples demonstrate that the proposed scheme either outperforms the existing schemes in the literature, or has a lower complexity while achieving a comparable performance.

We propose a serially concatenated coding scheme to communicate over binary energy harvesting communication channels with additive white Gaussian noise (AWGN), and design explicit and implementable codes for both long and short block lengths. Run length limited (RLL) codes are used to induce the required nonuniform input distributions for both cases. We employ low density parity check (LDPC) codes for long block lengths, while for short block lengths, we utilize convolutional codes as outer error correction codes. We consider different decoding approaches for the two cases, i.e., an iterative decoder is used for the former while Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm over the product trellis of the convolutional and run length limited codes is used for the latter. We also extend our work to joint energy and information transfer for both cases since similar coding solutions can be employed. Numerical examples demonstrate that the newly optimized codes with an inner RLL code are superior to the optimal codes over standard AWGN channels for long block lengths. Our results also show that, for the short block length case, concatenated convolutional and RLL codes with higher minimum distances offer excellent performance.