A Group-Based Massive Multiple Access Scheme in Cellular M2M Networks
Introduction
As a significant part in the Internet of Things (IoT), machine-to-machine (M2M) communications enable many devices spontaneously interactive with the network or each other, and inspire a wide range of emerging applications such as e-health, industrial automation, smart grids, intelligent transportation systems, smart home, etc [1]. It is expected that there will be 100-fold or more M2M connections in the emerging fifth generation (5G) [2], which may have serious effects on the traditional wireless networks with the limited radio resources [3], [4].
M2M communication is also known as machine-type communications (MTC) in the third generation partnership project (3GPP) [5]. In most application scenarios, massive MTC devices usually stay in idle state to save energy consumption until communicating with the network and transmitting data [6]. Random access (RA) procedure is the first step in initiating a network connection, where multiple devices access the evolved Node-B (eNB) by using given limited RA resources (i.e., preambles) in a contention-based method. A collision may occur if more than one devices select the same preamble. Due to a huge number of MTC devices, the preamble collisions become more frequently, which leads to severe RA overload, and radio resource wastage [7], [8]. Therefore, efficient RA and overload control schemes are required for M2M communications [9]. There have been some studies on the efficient RA schemes, and several kinds of overload control mechanisms have been proposed, e.g., dynamic allocation, slotted access, group-based, pull-based, and access class barring [10], [11], [12], [13], [14], [15], [16]. However, it is still challenging to further improve the RA performance to tackle a massive number of MTC devices accessing in 5G networks [17], [18].
Massive multiple-input multiple-output (MIMO), also known as large-scale antenna systems, is an emerging technology that has been identified as a key technology of 5G [19]. Compared to the conventional MIMO, massive MIMO scales up MIMO by possibly orders of magnitude and reaps all the benefits of conventional MIMO. In a massive MIMO system, the eNB equipped with a massive number of antennas simultaneously serves multiple terminals in the same time-frequency resource through spatial multiplexing, which bring huge improvements in throughput and spectral efficiency [20]. Moreover, massive MIMO also has many other advantages, such as extensive use of inexpensive low-power components, reduced latency, simplification of the MAC layer, and robustness against intentional jamming [21]. Although massive MIMO has been widely studied in recent years, the network access functionality has received very little attention in the system with massive MIMO. There is almost no study on how to leverage the excellent properties of massive MIMO to improve the efficiency of RA procedure for the massive number of MTC devices.
In this paper, we propose a group-based RA scheme that can improve the RA magnitude efficiently by exploiting the extra spatial degrees of freedom (DoF) of massive MIMO. The key idea of our proposed scheme is to use the beamforming technology to deal with the RA collisions caused by a massive number of MTC devices. In this scheme, the eNB equipped with a large-scale antenna array generates multiple beams to split the coverage area into multiple geometrical sectors. According to their locations, the MTC devices in whole area can be divided into multiple groups. Due to the spatial selectivity of beams, the MTC devices in different groups cause limited interference to each other during the RA procedure. It can efficiently reduce RA collisions and improve the access success probability of MTC devices. Numerical results is presented to demonstrate that the proposed scheme has a better performance than the legacy RA procedure under various experiment conditions.
The remainder of this paper is organized as follows. We first describe the proposed group-based RA scheme in Section 2.2. In Section 3, the system model is presented. Then, Section 4 provides numerical results as well as the performance analysis of our proposed scheme. Finally, concluding remarks are drawn in Section 5.
Section snippets
Proposed Group-based Random Access Scheme
In this section, we first present the RA procedure used in legacy cellular networks, and reveal its problem for M2M communications. Then, the proposed group-based RA scheme is described in detail.
System Model and Analysis
In this section, the performance of proposed group-based RA scheme is analysed by using a probability model. As illustrated in Fig. 2, we consider a single-cell cellular system that consists of an eNB and MTC devices. The eNB is equipped with a large-scale antenna array, and applies the beamforming technique to handling RA procedures initiated from MTC devices. It is assumed that Ng beams are formed at the eNB to split the coverage area into Ng sectors. That is, the MTC devices located in the
Numerical Results and Analysis
In this section, the performance of our proposed RA scheme is evaluated using Matlab. We first describe the system parameters and then analyze the numerical results.
We consider the scenario as illustrated in Fig. 2. The eNB equipped with a large-scale antenna array generates different numbers of beams Ng ∈ {32, 64, 128, 256} for the performance comparison. Fig. 4 illustrates the radiation patterns of beams under different numbers of beams. The gain of the receiving antenna at the eNB is
Conclusions
In this paper, we have presented a group-based RA scheme for M2M communications in cellular networks. Our proposed scheme employs the beamforming technology to divide the devices into multiple groups. Benefited from the spatial selectivity of beams, the limited interference are caused among different groups, which results in reducing RA collisions. The numerical results show that the access success probability of our proposed scheme increases with the increase of the number of beams. Moreover,
Acknowledgment
This work is supported by China Natural Science Funding under grant 61671089, BUPT Excellent Ph.D. Students Foundation under grant CX2016314, and China Unicom Network Technology Research Institute.
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