Internet of Things (IoT) is one of the main research directions in the future 5G wireless network applications such as industrial assets monitoring, smart city, logistics and environmental data sensing (Stefano et al., 2018). Nowadays, the information transmission between IoT terminals and the gateway station mainly depends on terrestrial wireless network, Wi-Fi and other local area networks, which need to construct numerous ground base stations to support massive IoT terminals. However, there will exist a conflict between service capability and network QoS requirement when IoT is applied in mountainous area, ocean and desert, because ground base stations are not suitable to construct and maintain in these remote areas (Wei-Che et al., 2019). Due to the nature of wide coverage, satellite communication systems have become an important supplement network to meet the requirement of the global coverage for 5G IoT applications (Mauro et al., 2015; Zhicheng et al., 2017; Tingting et al., 2019). Therefore, low Earth orbit (LEO) satellite based IoT networks has become a hot research topic in IoT area.

Compared with traditional wireless broadband access, the IoT service has the characteristics of massive connections, strong burstiness, and short packets. Therefore, RA is an effective access scheme from point view of channel utilization compared with fixed allocation and on-demand allocation multiple access methods. The RA scheme is to share channel resources in a competitive way. Multi-terminals occupying the same time-frequency resource will cause packets collision, which results in increasing the system packet loss ratio (PLR) and decreasing throughput of system. The channel utilization rate of the pure ALOHA (P-ALOHA) protocol is only 18.4% (Abramson, 1970). On this basis, the time slot ALOHA (S-ALOHA) protocol is proposed to improve the throughput for satellite networks by dividing the transmission time into several time slots (Roberts, 1975). The terminal can only send packets at the beginning of each time slot. In this way, the channel utilization rate improves to 36.7% by reducing the collision window of packets. However, S-ALOHA protocol requires network synchronization, which increases the complexity of the system. In (Enrico et al., 2007), E. Casini proposed a contention resolution diversity slotted ALOHA (CRDSA) to resolve contention of the packet collision, which combines multiple copies in the time or frequency domain with SIC technology. The collision packets have a chance to be recovered by this scheme. To improve the performance of CRDSA, R. De Gaudenzi presented a CRDSA++ scheme by transmitting more than two replicas of packet in (Riccardo and Oscar, 2007). This proposed RA scheme reveals that the increased replicas allow better resolve collision performance by SIC processing, although the more replicas can increase the probability of collision. G. Liva optimized the CRDSA scheme in (Gianluigi, 2010), called as irregular repetition slotted ALOHA (IRSA). In IRSA, the terminal generates a different number of copies according to the optimized allocation rules, which makes the throughput higher than the CRDSA protocol. However, terminals need to transmit signal copies in the time or frequency domain for these CRDSA based schemes, which not only consume the more power of terminals but also trigger ‘avalanche effect’ in high load condition of IoT networks. These time-frequency diversity improved RA schemes at the terminals fall far short of the initial design goal of low power consumption and massive access.

Inspired by transmitting signal copies in the time or frequency domain, massive multiple input multiple output (MIMO) is an effective spatial diversity measure to improve the system capacity in terrestrial wireless networks (Mingjin et al., 2019). However, compared with rich-scattering channel environment in terrestrial wireless network, light-of-sight (LOS) channel plays an important role with characteristic of non-rich-scattering channel in satellite communication channel. Therefore, the technique of massive MIMO applied in satellite communication system is difficult to achieve ideal diversity performance. To improve the system capacity in LOS channel, X.Q. Gao’s research team proposed a beam division multiple access (BDMA) transmission technology to reuse time-frequency resources in orthogonal beam domain for massive MIMO communications (Chen et al., 2015; Xin et al., 2017). On this basis, R.D. Jia combine BDMA with power domain non-orthogonal multiple access (NOMA) to increase the number of concurrent access terminals in the same time-frequency resource for the terrestrial IoT networks in (Rundong et al., 2019). However, the spatial resolving ability of antenna array in LEO satellite is much less than the same aperture of antenna array in terrestrial wireless networks because of the long distance between LEO satellite and IoT terminals, such as 150 km covering radius for antenna array with meter aperture in L band. J Ding proposed a novel machine learning based framework solution to address the preamble collision problem by joint processing distributed massive MIMO signal in terrestrial wireless networks in (Jie et al., 2021). This joint processing algorithm clustered the neighboring access points (APs) of collided RA terminals and organize each AP cluster to decode the received data individually. Motivated by this distributed cooperative scheme in terrestrial wireless networks, based on the precondition of synchronous mode, B. Zhao proposed a novel multi-satellite cooperative random access (MSC-RA) scheme combine with CRDSA, CRDSA++, and IRSA, respectively, to improve the RA performances in (Bo et al., 2019), which utilized multi-satellite overlapping coverage condition for the IoT terminals, such as OneWeb, Starlink and Telesat LEO satellite constellation development plan (Nils et al., 2021; Tong and Venkata, 2021). P. Li proposed an Asynchronous Cooperative ALOHA (ACA) scheme to form a spatial replica of the packet by multiple receiving satellites in (Pengxu et al., 2017). For this distributed spatial diversity scheme, the non-collision packet in a certain satellite is used to resolve contention in other satellites by SIC technology, which improves the system channel utilization rate. The techniques in ACA schemes that utilize multiple distributed nodes to receive signal separately and then process signal centrally can be categorized as coordinated multipoint (CoMP) transmission techniques for uplink. For example, Chen Zhang in the (Chen et al., 2021) used 3-dimensionally placed unmanned aerial vehicles as receiving nodes to process uplink data information under complex geographical conditions. Liang Liu used UAVs as CoMP nodes for interference cancellation in (Liang et al., 2019) to enhance the sum-rate capacity of the cellular uplink network. Compared with the time-frequency replicas schemes, the terminals do not need to send packet replicas, which not only saves the power of terminals but also alleviates network load at the expense of LEO multi-satellite spatial domain resources. However, the author considers that at least one of the receive packets by multiple satellites must not collide with other packets in a certain satellite. In this way, the SIC technology can be used to iteratively recover more collision packets. For this SIC cooperative scheme among multi-satellite, a ‘deadlock’ phenomenon will occur when the receive packet collide in all satellites, which will degrade the advantages of multi-satellite spatial diversity.

To solve this ‘deadlock’ phenomenon of multi-satellite spatial diversity scheme, we propose a cooperative beamforming ALOHA (CBA) scheme based on linearly constrained minimum variance (LCMV) criterion for LEO satellite IoT networks. This scheme combines multi-satellite receive diversity of RA packets with cooperative beamforming technique to resolve contention of the packet collision at the gateway station. The power of the collision packet will be suppressed in the spatial domain by cooperative beamforming technique compared with SIC cooperative scheme for ACA scheme in (Pengxu et al., 2017), cluster cooperative scheme in (Jie et al., 2021) and MSC MIMO detection in (Bo et al., 2019). The proposed CBA technique combined with SIC scheme is also designed to efficiently resolve packet collision for multi-satellite receive signal by iteration way. In this way, the multiple access interference (MAI) in multi-satellite overlapping coverage areas is changed into the available spatial resource for LEO satellite IoT networks. Furthermore, we derived the theoretical performance of proposed CBA scheme. Simulation results show that the proposed CBA scheme can effectively solve the problem of ‘deadlock’ and improve the performances of RA compared with benchmark problems.

The rest of this paper is organized as follows:

• In System Model, a RA system scenario with multi-satellite coverage is established.

Figure 1 shows a typical multi-satellite coverage scenario in LEO satellite IoT networks with terminals, LEO multi-satellite and gateway station. The area bounded by the black line denotes the multi-satellite overlapping coverage areas. Thus, the packets received by multi-satellite are forwarded to the gateway station transparently with independent backhaul channels which are assumed to be error free. Packets are performed at the gateway station. Without loss of generality, we supposed that the IoT network load follows Poisson distribution with parameter λ in one packet transmission duration and each transmitted packet length is fixed with the same duration T 0 . Thus, the normalized load G = ( λ lo g 2 b ) / M rev (bit/symbol) denotes the amount of data received by the gateway station per unit time, where b is the signal modulation order and M r e v is the total number of cooperative satellites. The normalized throughput T = G ( 1 − PLR ( G ) ) represents the amount of data can be correctly demodulated by the gateway station per unit time, where PLR ( G ) is the PLR under a specific network load. Due to the difference distance between each terminal and multi-satellite, a specific packet is transmitted once without any copy and it can be received by multi-satellite with different propagation delays in the receiving window [ t , t + Δ t ] , where t denotes the minimum propagation delay and Δ t is the maximum difference of propagation delays. For the typical LEO satellite constellation, such as OneWeb, Starlink and Telesat, Δ t is about 10–100 ms, while the typical packet length of IoT networks T 0 is approximately equals to 1 ms. Therefore, we consider Δ t > T 0 in the following sections.

To describe proposed CBA scheme in detail, the packet and receiving window status is represented in Packet and receiving window structure, the processing flow of proposed Multi-satellite CBA scheme is introduced in Packet processing flow of proposed CBA scheme, and the throughput and PLR performance of proposed CBA scheme is analyzed in Performance Analysis.

In this section, we analyze the throughput and PLR performance of proposed CBA scheme compared with traditional CRDSA scheme in (Enrico et al., 2007) and ACA algorithm in (Pengxu et al., 2017). The physical and MAC layer is jointly performed in the MATLAB simulation platform and the Monte Carlo method is adopted to verify the theoretical performance. These simulation conditions are similar to the benchmark problems. The simulation conditions are similar to the benchmark problems and the simulation parameters are given in Table 1.

Figure 7 shows the normalized throughput versus normalized load for the proposed CBA scheme compared with the CRDSA scheme and ACA scheme. As a baseline, we consider that the number of receiving satellites for the proposed CBA scheme and ACA scheme is the same as the number of replicas for the CRDSA scheme to generate the packet copies in spatial and time domain, respectively. From Figure 7A, we can find that throughput curves of different schemes linearly increase to a peak value in the low load area and then steeply degrade in the high load area. For proposed CBA scheme and ACA scheme, the throughput performances increase with the number of receiving satellite. The maximum normalized throughput reaches to 0 . 5 (bit/symbol) and 0 . 9 (bit/symbol) using two and three receiving satellites, respectively, for ACA scheme. Meanwhile, the maximum normalized throughput approximately reaches to 0 . 6 (bit/symbol) and 1 . 1 (bit/symbol) using two and three receiving satellites, respectively, for the proposed CBA scheme. However, for CRDSA scheme, the throughput performance seriously degrades with the packet copies increase in the high load area, because packet copies generated in the time/frequency domain increase the network load, which will result in ‘avalanche effect’ in high load area. The maximum normalized throughput approximately reaches to 0 . 55 (bit/symbol) and 0 . 7 (bit/symbol) using two and three packet copies, respectively, for the CRDSA scheme. For a fixed normalized load G = 1 , the throughput performance of proposed CBA scheme increases 10 % and 80 % performance compared with ACA scheme and CRDSA scheme, respectively, when the number of packet copies equals to 3 . From Figure 7B, the simulation results show that the theoretical Throughput curves are well matched with those simulated by Monte Carlo method of both two and three receiving satellites.

Figure 8 shows the PLR performance versus normalized load for the proposed CBA scheme compared with the CRDSA scheme and ACA scheme. From Figure 8A, we can find that the PLR of CRDSA scheme is lower than proposed CBA scheme in low load area, because CRDSA scheme adopts time slot synchronization. However, the PLR of proposed CBA scheme is lower than CRDSA scheme in the medium and high load area. For a fixed normalized load G = 1 , PLR value for the proposed CBA scheme reaches to 1 0 − 2 when the number of copies equals to 3 , while PLR value for CRDSA and ACA scheme approximately degrades to 1 and 1 0 − 1 , respectively. From Figure 8B, the simulation results show that the theoretical PLR curves are well matched with those simulated by Monte Carlo method of both two and three receiving satellites.

To increase the throughput performance of RA system, we presented a CBA scheme to solve the problem of ‘deadlock’ in ACA scheme under the multi-satellite common-view scenario. The cooperative beamforming collision resolution technique combined with SIC scheme was designed to efficiently resolve packet collision by iteration way at the gateway. Simulation results show that the proposed CBA scheme can effectively increase the RA performance compared with traditional ACA scheme. Further works on cooperative beamforming algorithm for packet collision resolution need to be discussed such as the robust design and collaboration receiver selection strategy of beamforming algorithm.