论文标题
软干涉取消用于大规模高斯多访问中随机编码
Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access
论文作者
论文摘要
2017年，Polyanskiy [1]表明，大型高斯随机访问的功率和带宽效率之间的权衡受两个根本不同的政权支配：低功率和高功率。对于这两个制度，Zadik等人都发现了紧密的性能界限。 [2]，在2019年。这项工作利用了最新的结果，即加性白色高斯噪声中高斯随机代码的确切块误差概率，以基于迭代软解码为基于[2]中的界限的实用方法提出实用方法。在低功率制度中，这项工作发现可以直接应用正交随机代码。在高力量制度中，需要更加复杂的努力。这项工作表明，通过Caire等人开创的线性编程，通过线性编程进行了功能框架优化。 [3]在2001年，是一种有前途的适用策略。正交随机编码和迭代软解码的拟议组合甚至超过了Zadik等人的存在边界。 [2]在低功率制度中，对于100及以上的消息长度，非常接近不存在的范围。最后，发现针对高功率制度提出的线性编程的功率优化方法被发现受益于由于褪色而导致的功率失衡，这对典型的移动无线电频道更具吸引力。
In 2017, Polyanskiy [1] showed that the trade-off between power and bandwidth efficiency for massive Gaussian random access is governed by two fundamentally different regimes: low power and high power. For both regimes, tight performance bounds were found by Zadik et al. [2], in 2019. This work utilizes recent results on the exact block error probability of Gaussian random codes in additive white Gaussian noise to propose practical methods based on iterative soft decoding to closely approach the bounds in [2]. In the low power regime, this work finds that orthogonal random codes can be applied directly. In the high power regime, a more sophisticated effort is needed. This work shows that power-profile optimization by means of linear programming as pioneered by Caire et al. [3], in 2001, is a promising strategy to apply. The proposed combination of orthogonal random coding and iterative soft decoding even outperforms the existence bounds of Zadik et al. [2] in the low power regime and is very close to the non-existence bounds for message lengths around 100 and above. Finally, the approach of power optimization by linear programming proposed for the high power regime is found to benefit from power imbalances due to fading which makes is even more attractive for typical mobile radio channels.
