Sliding window-based Contention Resolution Diversity Slotted ALOHA

Abstract

Contention Resolution Diversity Slotted ALOHA (CRDSA) and its burst degree optimizations (CRDSA++, IRSA) make use of MAC burst repetitions and Interference Cancellation (IC) making possible to reach throughput values as high as T ≃ 0.8 in practical implementations, whereas for the traditional slotted ALOHA T ≃ 0.37. However, these new techniques introduce a frame-based access to the channel that limits the performance in terms of throughput and packet delivery delay. In this paper, a new technique named Sliding Window CRDSA (SW-CRDSA) and its counterpart for irregular repetitions (SW-IRSA) are introduced in order to exploit the advantages of MAC burst repetition and Interference Cancellation (IC) with an unframed access scheme. Numerical results are also provided in order to validate the statement of better performance

Average power limitations in Sliding Window Contention Resolution Diversity Slotted Aloha

“…Displayed results assume Poisson Arrivals for packets transmitted and G represents the mean of the corresponding Poisson distribution 3 . As claimed in the introduction and demonstrated in [8], the throughput for SW-CRDSA is generally higher than the one for FB-CRDSA if the same load for the two is considered. This can be explained with the fact that each packet's sliding window is different from the others unless more than one packet was ready for transmission within the same slot interval.…”

“…Therefore, after the decoding process for a given frame is finished and decoded packets have been passed to the upper layers, memorized slots are not anymore useful and can thus been removed if needed. 3 The assumption of Poisson Arrivals is necessary in order to obtain comparable results for FB-CRDSA and SW-CRDSA as thoroughly explained in [8]. In SW-CRDSA instead, also bursts received more than N sw slots before have the possibility to still be correctly decoded due to the fact that interaction among packet copies can not be a-priori bounded within a certain number of slots.…”

“…For this reason, the need to keep in memory a number of slots greater than N sw arises. While this fact would theoretically require an infinite memory, it has been demonstrated in [8] that keeping in memory at the receiver (5 · N sw ) slots it is sufficient to avoid almost any loss of potentially decodable packets.…”

“…Also the throughput performance is limited by frames since packets sent in the same frame share the same set of eligible slots to place their copies and this increases, from a probabilistic point of view, the occurrence of unsolvable collisions. For this reason, in [8] a new technique exploiting the advantages of CRDSA in an unframed manner has been introduced. This technique (named Sliding WindowContention Resolution Diversity Slotted Aloha) further boosts the throughput performance up to 13% with respect to CRDSA and at the same time reduces the average packet delay at destination.…”

Decentralized Reinforcement Learning Based MAC Optimization

“…Further improvements of IRSA can be found in the work of [7], which extends IRSA by introducing Coded Slotted ALOHA (CSA), where coding is performed between the packets available at the nodes. In [8], a frameless variant of CRDSA is introduced, which limits delays, as sensor nodes are not obliged to wait for the next frame to transmit their messages. Frame asynchronous Coded ALOHA [9] combines methods in [7] and [8] and shows an improvement both in achieved error floor and observed delay.…”