Slotted Aloha has been widely adopted in various communication networks. Yet if the transmission probabilities and traffic input rates of transmitters are not properly regulated, their data queues may easily become unstable. For stability analysis of Aloha networks with multiple transmitter-receiver (T-R) pairs, the focus of previous studies has been placed on the maximum input rate of each transmitter, below which the network is guaranteed to be stabilized under any given topology. By assuming a fixed and identical transmission probability across the network, however, network stability is found to be unachievable when the input rate exceeds zero. As we will demonstrate in this paper, the key to stabilizing the network lies in proper selection of transmission probabilities according to the traffic input rates and locations of all transmitters and receivers. Specifically, for an Aloha network with multiple capture receivers, by establishing and solving the fixed-point equations of the steady-state probabilities of successful transmissions of Head-of-Line packets, the exact service rates of all transmitters’ queues are obtained, based on which the operating region of transmission probabilities for achieving stability and the stability region of input rates are further characterized. The results are illustrated in various scenarios of multi-cell and ad-hoc networks. Simulation results validate the analysis and corroborate that the network can be stabilized as long as the traffic input rates are within the stability region, and the transmission probabilities are properly adjusted according to the traffic input rates and network topology.

Slotted Aloha has been widely adopted in various communication systems, while its stability performance has long been observed as being sensitive to the setting of transmission probabilities. For stability analysis of Aloha networks with multiple transmitter-receiver (T-R) pairs, the focus of previous studies has been placed on characterization of the maximum input rate of T-R pairs, below which the network can be stabilized under any given topology. With a fixed and identical transmission probability for all T-R pairs, nevertheless, network stability is often found to be unachievable, as part of transmitters would become unstable regardless of how small the traffic input rate is. As we will demonstrate in this paper, to stabilize the whole network, transmission probabilities of T-R pairs should be properly adjusted according to their traffic input rates and locations. Specifically, by establishing the fixed-point equations of the steady-state probabilities of successful transmissions of Head-of-Line (HOL) packets, the service rates of transmitters' queues can be obtained, based on which the operating region of transmission probabilities for achieving stability can further be characterized. Simulation results corroborate that all the T-R pairs can be stabilized by choosing transmission probabilities from the region, which highlights the importance of proper transmission control based on the traffic input rates and network topology for Aloha networks.

As one of the most representative random-access schemes, slotted Aloha has been adopted in various wireless communication networks. A multi-cell Aloha network may easily become unstable as the inter-cell interference grows if the traffic input rates and transmission probabilities of nodes are not properly regulated. Yet how to stabilize a multi-cell Aloha network has remained largely unknown. To address the above open issue, an analytical framework is proposed in this paper for multi-cell Aloha networks to characterize the stability region of traffic input rates and operating region of transmission probabilities of nodes for achieving network stability. Specifically, the inter-cell interference level is captured by the overlapping ratio of each cell, and shown to be a key factor that determines the stability performance. For a two-cell Aloha network, the stability region of input rates and complete operating regions of transmission probabilities are obtained as functions of the overlapping ratios of cells. For the general$M$-cell case, a transmission control algorithm is further proposed to stabilize the network only based on the local information exchange between neighboring cells, with effectiveness demonstrated through simulations.

This paper focuses on the outage probability of access delay of Machine-to-Machine (M2M) communications in cellular networks, which is an important performance indicator for Ultra-Reliable and Low-Latency Communication (URLLC). Specifically, by deriving the outage probability for given maximum allowable access delay as a function of system parameters, the outage probability is minimized by optimally tuning the Access Class Barring (ACB) factor. For given outage probability bound, the admission control and resource allocation for the random access channel are further discussed, where the maximum number of Machine-Type Devices (MTDs) that can be admitted with given number of preambles and the minimum number of preambles that should be allocated with given network size are obtained. Compared to the standard setting where the ACB factor is fixed, significant gains in outage probability are demonstrated by optimally tuning the ACB factor according to the number of MTDs and the traffic input rate of each MTD. It is also shown that for given required outage probability bound, the optimal tuning of ACB factor enables much more MTDs to be admitted for given preamble resource, and requires much fewer preambles for given network size.