Analysis of Pure and Slotted ALOHA With Multi-Packet Reception and Variable Packet Size

Multi-Packet Reception (MPR) enables simultaneous receptions from different transmitters to a single receiver, which has been demonstrated to bring capacity improvement in wireless network. However, MPR does not improve the transmission capability of intermediate relay nodes in a multi-hop routing and thus these nodes may become the bottlenecks for increasing throughput despite of great reception capability. We investigate the scheduling for multi-hop routing with MPR to improve the network throughput under multiple data flows. We formulate the optimization problem under K-MPR model and analyze the performance upper bound with ideal scheduling. We propose a distributed scheduling scheme based on a k-Connected k-Dominating Set backbone to eliminate bottleneck effects on intermediate relay nodes as to enhance the network throughput. We show the effectiveness of our scheme by comparing its performance with the upper bound and node-disjoint routing.

We present an approach that takes advantage of multi-packet reception (MPR) to reduce the negative effects of multiple access interference and therefore increase the capacity of an ad hoc network. We analyze the performance upper bound of joint routing and scheduling for ad hoc networks that embrace interference by using MPR. We formulate the optimization problem under a deterministic model and seek to maximize the aggregate network throughput subject to minimum rate requirements. We then propose a polynomial-time heuristic algorithm aimed at approximating the optimal solution to the joint routing and channel access problem under MPR. We show the effectiveness of our heuristic algorithm by comparing its performance with the upper bound.

This paper presents a novel approach called VSP (Variable Size Packets) for satellite access lower layers. The VSP solution aims at optimizing the transport of packets issued from network layers with highly variable sizes. Therefore, VSP relies on the definition of multiple encapsulation sizes associated to a waveform, and an access adapted to the transport of variable size packets. We recall the VSP concept, insisting on its impact at the physical and access layers, and present an efficient coding and modulation scheme for the VSP solution, resources allocation constraints and packet sizes and slot sizes definition strategies.

ABSTRACTThe architectural design of the Indoor Internet of Things (IIoT) network targeting static end devices (EDs) and gateways (GWs) has been innovatively formulated in this paper, integrating LoRa technology to mitigate losses and ensure seamless information reception through meticulous ED allocation. The arrangement of simultaneously transmitted data within the network server (NS) employs a deep neural network (DNN) with distributed machine learning (DML) to adjust transmission parameters, ensuring frequent uninterrupted bidirectional communication. This augmentation is obtained by strategically deploying EDs within distinct clusters determined by K‐means and density‐based spatial clustering with noise (DBSCAN), thus optimizing spreading factor (SF) and data rate (DR) allocation to prevent data congestion and improve signal‐to‐interference noise ratio (SINR). The proposed hybrid model (DR|SF) for pure and slotted ALOHA amplifies the network's performance metrics for indoor scenarios. A unified framework utilizing a one‐slope model estimates path losses (PL) while exploring various bandwidths (BW), bidirectional interrogations, and duty cycles (DC) to lower the saturation and prolong the active lifespan of the EDs. The results manifest a packet rejection rate (PRR) of 0% for the DBSCAN, contrasting a 4.7% estimate for the K‐means. The network saturation is minimized to 9.5% and 10.1%, correspondingly, significantly increasing the efficiency of slotted ALOHA (91%) and pure ALOHA (90.6%), thereby prolonging the longevity of EDs.

In this paper, we propose an analytical approach for evaluating the performance of finite-user slotted Aloha in wireless networks with multiple packet reception and random traffic. We derive the exact values of the throughput, the average system size, the packet blocking probability, and the average system delay. Our analysis is based on probability theory. We show that our numerical results are identical to simulation results.

The effect of multipacket reception (MPR) on stability and delay of slotted ALOHA based random-access systems is considered. A general asymmetric MPR model is introduced and the medium-access control (MAC) capacity region is specified. An explicit characterization of the ALOHA stability region for the two-user system is given. It is shown that the stability region undergoes a phase transition from a concave region to a convex polyhedral region as the MPR capability improves. It is also shown that after this phase transition, slotted ALOHA is optimal i.e., the ALOHA stability region coincides with the MAC capacity region. Further, it is observed that there is no need for transmission control when ALOHA is optimal i.e., ALOHA with transmission probability one is optimal. Next, these results are extended to a symmetric N>2 user ALOHA system. Finally, a complete characterization of average delay in capture channels for the two-user system is given. It is shown that in certain capture scenarios, ALOHA with transmission probability one is delay optimal for all stable arrival rates. Further, it is also shown that ALOHA with transmission probability one is optimal for stability and delay simultaneously in the two-user capture channel.

This paper concerns the cross-layer design between physical layer and MAC (multiple access control) layer in asynchronous wireless random access network. The proposed cross-layer design consists of two parts: a MPR (Multiple Packet Reception) physical layer and a collision- aware MAC layer. In the physical layer design, different spreading codes are assigned to packets according to their frame types at the transmitter, and at the receiver, an enhanced synchronization method and MUD (Multi-user Detection) are utilized to synchronize the collided packets and recover packets. In order to reduce the computational complexity of the receiver, interference cancellation is performed at the receiver by utilizing the known preamble and the partially known frame header information. In the MAC layer design, collisions are divided into different types according to frame types and packet arrival time, and different operations are developed for different collision types to tactically access the channel. Simulation results show that the proposed cross-layer design can significantly improve the network throughput and reduce the transmission delay.

The conventional medium access control (MAC) protocols assume that only one packet (frame) can be received at a given time. However, with the advent of spread spectrum, antenna arrays, and sophisticated signal processing techniques, it is now possible to achieve multiple-packet reception (MPR) in wireless networks. With MPR, the network capacity can be remarkably increased, but so far, how to achieve fair bandwidth allocation for the stations with different quality of service (QoS) requirements in such networks is still a problem. To solve this problem, we propose a distributed method that can support multiple priority classes in the MPR-capable wireless networks with weighted fair share. In particular, this method assigns each class a frame transmission probability to reflect its relative weight among the different data traffic flows. A closed-form expression of system throughput is derived for each class in the environment, and it is numerically evaluated with different simulation scenarios. The results show that the method can achieve the weighted fairness under different numbers of priority classes and different numbers of stations in the networks.

In this paper we propose a decentralized medium access control (MAC) scheme to coordinate the access of multiple transmitters adopting a multi-packet reception (MPR) physical (PHY) layer. MPR receivers are able to decode multiple transmissions, and depending on the technique adopted at the PHY-layer, there is an optimal number of simultaneous transmissions that maximize the number of packets successfully decoded in a simultaneous way. The proposed MAC scheme admits an MPR PHY-layer and is divided in two stages. In the first one the nodes indicate their willingness to transmit, while in the second one they jointly transmit. Adopting a generic model for the PHY-layer, we characterize the throughput achieved by the proposed MAC when both MAC and PHY layers are considered. The formal characterization of the throughput is then used to optimize the duration of the first stage of the MAC scheme in order to optimize the throughput. In this way, the number of transmitters is regulated to optimize the cross-layer operation, taking into consideration the features of the MPR PHY-layer and the maximum performance achieved with the proposed MAC design. Several results obtained through simulation are presented, which validate the numerical results obtained with the proposed characterization. The proposed scheme is a first step to develop MAC protocols specifically designed to distributed MPR systems that operate in a cross-layer and improve the exploitation of current and future MPR techniques proposed for the PHY-layer.

Delay Tolerant Network (DTN) is a kind of networks that have no fixed path between nodes due to lack of continuous network connectivity. To achieve successful communication and to improve performance in DTN is always a challenge work. Most existing works are based on designing high efficient routing protocols and have not emphasized the MAC layer as well as new technologies available in the Physical layer which may influence the performance for whole networks. In this paper, we consider utilization of Multi-packet Reception (MPR) capability in DTN in order to provide better performance. We introduce our own MPR scheduling scheme, Group Based Scheme (GBS), and compare the performance of DTN with different MPR capabilities. Our works have been evaluated by the simulation using a real vehicular network trace composed of the GPS data of more than 4,000 taxis in Shanghai urban area. The results have demonstrated various impacts of using Multi-Packet Reception (MPR) on performance in DTN. By using MPR in DTN, it outperforms the network without MPR especially when the wireless transmission range increases.

Enhanced mobile broadband (eMBB) is a major scenario in the prospective fifth generation (5G) wireless communications. Achieving high user experienced data rate (UEDR) is one of vital goals of eMBB, which needs to consume massive bandwidth. Considering the limited radio frequency (RF) spectrum resource has got heavily congested, we explore the multi-packet reception (MPR) aided visible light communications (VLCs) system to support eMBB services in this paper. MPR can efficiently alleviate collisions for VLC system and enhance UEDR. However, the implementation of MPR in random access system is challenging because of dynamic and unpredictable transmissions of eMBB terminals. For fully utilizing MPR capability and promoting UEDR maximally, we design a two-period frame structure including the access request period (ARP) and the data transmission period (DTP). UEDR emphasizes not only the data rate measured in physical layer but also the network operation behaviour experienced by users which connects closely with quality of service (QoS). In this paper, effective capacity (EC) is employed to depict UEDRs for eMBB terminals for the first time, which provides an efficient link model to evaluate data rates with consideration of statistical delay QoS. Then, the aggregate UEDR is derived and defined as a system metric, which reflects the transmission features of both two periods. We formulate the hybrid access algorithm for eMBB terminals with heterogeneous QoS requirements as an aggregate UEDR maximization problem and find the optimum access probability (for ARP) and optimal resource allocation strategy (for DTP) via the particle swarm optimization-initialization intervention (PSO-II) algorithm.

Capacity estimation effective in an IP network path is a key enabling technology for proactive and reactive resource management as well as intelligent planning in next generation IP networks. We analyze capacity measurements at different Internet destinations. Particularly, we use the variable packet size (VPS) method to measure the per-hop capacity in some network paths. This method is based on round trip time (RTT) measurements as well as on the Internet control message protocol, ICMP. The RTT delay is approximated by a gamma distribution. We observe how the measurement accuracy of this active probing is affected by factors such as layer 2 device latencies, limited clock resolution at the probing host, or queuing delay. These factors cause non linearity on the RTT curves obtained and, consequently, inaccuracies on the estimation of path capacities. The use of robust regression to improve linear approximation in the VPS method is proposed. As a result, we obtain better qualitative and quantitative results.

In wireless multi-hop Ad hoc networks, contending existing at MAC layer could easily results in congestion, and the first-in-first-out queue within the nodes could make the head of the queue blocked, which affects the transmitting of the following packets. In this paper, we present a variable packet size supporting and congestion-based opportunistic packet scheduling (VS-CBOS) algorithm, in which the sender sends multicast RTS frame targeted to several next-hop receivers, the receiver will reply with priority-based CTS by the probability according to its queue congestion level, and reservation subheader is added to DATA frame to support variable packet size. The performance analysis and simulation results show that VS-CBOS can remarkably increase the signaling handshake success ratio, the network end-to-end saturation throughput and the fairness among traffic flows.

The Long Range (LoRa) networks are able to provide both long-range coverage and low power consumption for sensing devices. These features make it one of the most attractive solutions for Internet of Things (IoT) applications. The default channel access mechanism used by the protocol is pure ALOHA, which due to its simplicity and lack of synchronization creates scalability problems when the number of supported end devices increases. The slotted ALOHA channel access mechanism has been proposed as an alternative, which through the synchronization of transmissions achieves the improvement of the efficiency and scalability of LoRa networks. One of the most important operating parameters of slotted ALOHA is the backoff algorithm. In this paper we present a novel backoff algorithm assisted by reinforcement learning mechanism, which regulates the offered load on the network by adjusting the congestion window. Simulation results show that the proposed algorithm improves efficiency and energy consumption for the end devices compared to other backoff algorithms from the literature.

RFID technology has been widely utilized for supply chain management, objection location, vehicle control, and electronic toll collection (ETC). One of the most challenging RFID applications has to do with the improvement in reliability, scheduling and efficiency of large-scale RFID tags scenario. ALOHA algorithm is one of the key technologies which have been widely used in different RFID applications. ALOHA algorithm can be divided into the following subgroups: Pure ALOHA, Slotted ALOHA, Framed Slotted ALOHA and Dynamic Framed Slotted ALOHA. The performance of these ALOHA algorithms are analyzed in this paper. The simulation results show that the system achieves the optimal performance if the number of slots is equal to the RFID tags.