Fundamental Limits of Many-User MAC With Finite Payloads and Fading
Fundamental Limits of Many-User MAC With Finite Payloads and Fading
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DOI：
10.1109/tit.2021.3091423
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发表时间：
2021-09-01
影响因子：
2.5
通讯作者：
Polyanskiy, Yury
中科院分区：
文献类型：
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作者：
Kowshik, Suhas S.;Polyanskiy, Yury
考虑一个（多址）无线通信系统，其中用户通过共享频谱无线电链路连接到唯一的基站。每个用户都有固定数量的 k 个比特发送到基站，并且他的信号会因随机信道增益而衰减（准静态衰落）。在本文中，我们考虑 Chen-Chen-Guo'2017 的多用户渐近，其中用户数量随块长度线性增长。但不同的是，我们采用每用户错误概率 (PUPE) 标准（与经典的联合错误概率标准相反）。在 PUPE 下，每比特有限能量通信是可能的，并且我们能够得出能量和频谱效率之间权衡的界限。我们再次确认了奇怪的行为（之前在非衰落 MAC 中观察到），即用户密度低于临界阈值时，可能会实现近乎完美的多用户干扰 (MUI) 消除。此外，我们还证明了标准解决方案的次优性，例如正交化（即 TDMA/FDMA）和将干扰视为噪声（即没有多用户检测的伪随机 CDMA）。值得注意的是，这里处理的问题可以看作是压缩感知中支持恢复的一种变体，用于稀疏性的不寻常定义，每个 2(k) 坐标的连续部分有一个非零条目。这确定了我们的问题与稀疏回归代码 (SPARC) 的问题，因此我们的结果可以在长度为 2(100) 的 SPARC 上下文中等效地理解。最后，我们讨论了近乎完美的 MUI 取消属性与复制方法预测的关系。
Consider a (multiple-access) wireless communication system where users are connected to a unique base station over a shared-spectrum radio links. Each user has a fixed number k of bits to send to the base station, and his signal gets attenuated by a random channel gain (quasi-static fading). In this paper we consider the many-user asymptotics of Chen-Chen-Guo'2017, where the number of users grows linearly with the blocklength. Differently, though, we adopt a per-user probability of error (PUPE) criterion (as opposed to classical joint-error probability criterion). Under PUPE the finite energy-per-bit communication is possible, and we are able to derive bounds on the tradeoff between energy and spectral efficiencies. We reconfirm the curious behaviour (previously observed for non-fading MAC) of the possibility of almost perfect multi-user interference (MUI) cancellation for user densities below a critical threshold. Further, we demonstrate the suboptimality of standard solutions such as orthogonalization (i.e. TDMA/FDMA) and treating interference as noise (i.e. pseudo-random CDMA without multi-user detection). Notably, the problem treated here can be seen as a variant of support recovery in compressed sensing for the unusual definition of sparsity with one non-zero entry per each contiguous section of 2(k) coordinates. This identifies our problem with that of the sparse regression codes (SPARCs) and hence our results can be equivalently understood in the context of SPARCs with sections of length 2(100). Finally, we discuss the relation of the almost perfect MUI cancellation property and the replica-method predictions.