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Uplink IoT Networks: Time-Division Priority-Based Non-Orthogonal Multiple Access Approach

机译:上行链路IOT网络:基于时分优先级的非正交多访问方法

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Non-orthogonal multiple access (NOMA) has been investigated to support massive connectivity for Internet-of-things (IoT) networks. However, since most IoT devices suffer from limited power and decoding capabilities, it is not desirable to pair a large number of devices simultaneously, which encourages two-user NOMA grouping. Additionally, most existing techniques have not considered the diversity in the target QoS of IoT devices, which may lead to spectrum inefficiency. Few investigations have partially considered that issue by using an order-based power allocation (OPA) approach, where the power is allocated according to the order to the user’s target throughput within a priority-based NOMA (PNOMA) group. However, this does not fully capture the effects of diversity in the values of the users’ target throughputs. In this work, we handle both problems by considering a throughput-based power allocation (TPA) approach, that captures the QoS diversity, within a three-users PNOMA group as a compromise between spectral efficiency and complexity. Specifically, we investigate the performance of a time-division PNOMA (TD-PNOMA) scheme, where the transmission time is divided into two-time slots with two-users per PNOMA group. The performance of such TD-PNOMA is compared with a fully PNOMA (F-PNOMA) scheme, where the three users share the whole transmission time, in terms of the ergodic capacity under imperfect successive interference cancellation (SIC). The results reveal the superiority of TPA compared with OPA approach in both schemes, besides that the throughput of both schemes can outperform each other under imperfect SIC based on the transmit signal-to-noise ratio and the deployment scenarios.
机译:已经研究了非正交多次访问(NOMA)以支持对互联网(IOT)网络的大规模连接。然而,由于大多数IOT设备遭受有限的功率和解码能力,因此不希望同时配对大量设备,这鼓励两个用户NOMA分组。此外,大多数现有技术没有考虑IOT设备的目标QoS中的多样性,这可能导致频谱低效率。利用基于订单的功率分配(OPA)方法,很少考虑一些调查,其中根据基于优先级的NOMA(PNOMA)组中的用户目标吞吐量的顺序分配电力。但是,这并未完全捕获多样性在用户目标吞吐量的值中的影响。在这项工作中,我们通过考虑基于吞吐量的功率分配(TPA)方法来处理既有问题,它在三个用户的Pnoma组内捕获QoS多样性,作为光谱效率和复杂性之间的折衷。具体地,我们研究了时分PNOMA(TD-PNOMA)方案的性能,其中传输时间被分成双时隙,每个PNOMA组是两个用户。将这种TD-PNOMA的性能与完全庞大瘤(F-PNOMA)方案进行比较,其中三个用户在不完美的连续干扰消除(SIC)下的ergodic容量方面共享整个传输时间。结果揭示了与两种方案中的OPA方法相比的TPA的优越性,除了这两个方案的吞吐量基于发射信噪比和部署方案,这两种方案的吞吐量都可以在不完全SiC下彼此突出。

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