Due to its simplicity and scalability, the Irregular Repetition Slotted ALOHA (IRSA) system that uses the successive interference cancellation (SIC) technique is a promising solution for uncoordinated multiple access of a massive number of Internet-of-Things (IoT) devices. In this paper, we propose two parallel decoding algorithms for IRSA in an additive white Gaussian noise channel. Our first algorithm is limited to SIC-decoupling matrices that correspond to the SIC decoding process in IRSA. For this, we propose a message-passing algorithm to find the optimal SIC-decoupling matrix that can minimize the accumulated noise power when the induced user-slot bipartite graph of an IRSA system is acyclic. This includes the Contention Resolution Diversity Slotted ALOHA (CRDSA) system that sends exactly two copies for each packet as a special case. Our second algorithm extends the first one by finding the optimal decoupling matrix for CRDSA through an optimal combination of two SIC-decoupling matrices. Using a random graph analysis, we derive the throughput for the two parallel decoding algorithms of CRDSA in a threshold-based decoding model. We then conduct various numerical experiments to illustrate the tradeoffs between sequential decoding with a limited number of iterations and parallel decoding with a predefined signal-to-noise ratio (SNR) threshold. Finally, we demonstrate how to extend our parallel decoding scheme to bipartite graphs with cycles.

Motivated by the need to provide differentiated quality-of-service (QoS) in grant-free uplink transmissions in 5G networks and beyond, we extend the probabilistic analysis of coded Poisson receivers (CPR) to the setting with multiple classes of users and receivers. For such a CPR system, we prove (under certain technical conditions) that there is a region, called the stability region in this paper. Each transmitted packet can be successfully received with probability 1 when the offered load to the system is within the stability region. On the other hand, if the offered load is outside the stability region, there is a nonzero probability that a packet will fail to be received. We then extend the stability region to the$\epsilon $-stability region for CPR systems with decoding errors. We also demonstrate the capability of providing differentiated QoS in such CPR systems by comparing the stability regions under various parameter settings.

Due to its simplicity and scalability, the Irregular Repetition Slotted ALOHA (IRSA) system that uses the successive interference cancellation (SIC) technique is a promising solution for uncoordinated multiple access of a massive number of Internet-of-Things (IoT) devices. However, the peeling (iterative) decoder for IRSA is sequential in nature, and it might lead to cascading errors due to imperfect SIC. In this paper, we propose a parallel decoding algorithm for IRSA in an Additive White Gaussian Noise (AWGN) channel. Inspired by a recent advance in collision resolution for random access, our approach is to find a SIC-decoupling matrix so that the receiver can perform interference cancellation based on the received signals only. We propose a message-passing algorithm to find the optimal SIC-decoupling matrix when the induced user-slot bipartite graph of an IRSA system is acyclic. This includes the Contention Resolution Diversity Slotted ALOHA (CRDSA) system that sends exactly two copies for each packet. Using a random graph analysis, we derive the throughput for parallel decoding of CRDSA in a threshold-based decoding model. We also conduct various numerical experiments to illustrate the tradeoffs between sequential decoding with a limited number of iterations and parallel decoding with a predefined signal-to-noise ratio (SNR) threshold. Our numerical results show that one can significantly reduce the decoding time and achieve comparable throughput by parallel decoding when the SNR is substantially larger than the decoding threshold.

Motivated by the need to hide the complexity of the physical layer from performance analysis in a layer 2 protocol, a class of abstract receivers, called Poisson receivers, was recently proposed by Yuet al.(2021) as a probabilistic framework for providing differentiated services in uplink transmissions in 5G networks. In this paper, we further propose a deterministic framework of ALOHA receivers that can be incorporated into the probabilistic framework of Poisson receivers for analyzing coded multiple access with successive interference cancellation. An ALOHA receiver is characterized by a success function of the number of packets that can be successfully received. Inspired by the theory of network calculus, we derive various algebraic properties for several operations on success functions and use them to prove various closure properties of ALOHA receivers, including (i) ALOHA receivers in tandem, (ii) cooperative ALOHA receivers, (iii) ALOHA receivers with traffic multiplexing, and (iv) ALOHA receivers with packet coding. By conducting extensive simulations, we show that our theoretical results match extremely well with the simulation results.

In the literature, there are several well-known periodic channel hopping (CH) sequences that can achieve maximum rendezvous diversity in a cognitive radio network (CRN). For a CRN with N channels, it is known that the period of such a CH sequence is at least N2. The asymptotic approximation ratio, defined as the ratio of the period of a CH sequence to the lower bound N2when N → ∞, is still 2.5 for the best known CH sequence in the literature. An open question in the multichannel rendezvous problem is whether it is possible to construct a periodic CH sequence that has the asymptotic approximation ratio of 1. In this paper, we tighten the theoretical gap by proposing CH sequences, called IDEAL-CH, that have the asymptotic approximation ratio of 2. For a weaker requirement that only needs the two users to rendezvous on one commonly available channel in a period, we propose channel hopping sequences, called ORTHO-CH, with period (2 p+1) p, where p is the smallest prime not less than N.