{'fraction_non_alphanumeric': 0.01634877384196185, 'fraction_numerical': 0.0, 'mean_word_length': 5.598802395209581, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Joint subcarrier and power allocation for OFDMA based mobile edge computing system

By offloading computationally intensive tasks to the edge cloud provided by the cellular base stations, the mobile edge computing (MEC) technique has the potential to realize the critical millisecond-scale latency requirement of next generation mobile services. In this paper, we investigate the joint subcarrier and power allocation problem in an orthogonal frequency division multiple access (OFDMA) based MEC system to minimize the maximal delay of each mobile device. The partial data offloading scenario is considered where mobile data can be computed at both local devices and the edge cloud. Since the problem is a combinatorial optimization one, we first propose a lower-bound algorithm by relaxing the channel allocation indicators into continuous variables. Then, to find a low-complexity feasible solution, we further develop a heuristic algorithm which separates subcarrier assignment and power allocation. The performances of our proposed algorithms are finally tested by extensive numerical simulations.