Polar Codes with Dynamic Frozen Symbols and Their Decoding by Directed Search

A novel construction of polar codes with dynamic frozen symbols is proposed. The proposed codes are subcodes of extended BCH codes, which ensure sufficiently high minimum distance. Furthermore, a decoding algorithm is proposed, which employs estimates of the not-yet-processed bit channel error probabilities to perform directed search in code tree, reducing thus the total number of iterations.Comment: Accepted to ITW201

Towards Optimal Decoding for Polar Codes

In the conventional successive cancellation (SC) decoder for polar codes, all the future bits to be estimated later are treated as random variables. However, polar codes inevitably involve frozen bits, and their concatenated coding schemes also include parity bits causally generated from the past bits estimated earlier. We refer to the frozen and parity bits located behind a target decoding bit as its future constraints (FCs). Although the values of FCs are deterministic given the past estimates, they have not been exploited in the conventional SC-based decoders, not leading to optimality. In this paper, we propose SC-check (SCC) and belief-propagation SCC (BP-SCC) decoding algorithms in order to leverage FCs in decoding.We further devise a tree search technique based on stack-based backjumping (SBJ) to solve dynamic constraint satisfaction problems (CSPs) formulated by FCs. Over the binary erasure channel (BEC), numerical results show that a combination of the BP-SCC algorithm and the SBJ tree search technique achieves the erasure recovery performance close to the dependence testing (DT) bound, a bound of achievable finite-length performance

A DETAILED ANALYSIS AND OPTIMIZATION OF THE MODIFIED POLAR DECODING RNTI RECOVERY METHOD TO TRACK USER ACTIVITY IN 5G NETWORKS

In this thesis, we analyze and optimize the modified polar decoding and syndrome matching radio network temporary identifier (RNTI) recovery method to de-anonymize the physical downlink control channel (PDCCH) in 5G networks. We present the impact on RNTI recovery of payload length, codeword length, signal-to-noise ratio (SNR) and the Hamming and longest common substring (LCS) recovery methods. Further, we consider the full set of RNTIs and downlink control information (DCI) fields that can be examined for user activity data and propose methods to track user activity within radio networks from the recovered data. Finally, we optimize the RNTI recovery method for different attacker scenarios to demonstrate how an attacker can recover RNTIs, track UEs, and aggregate data about the UE usage patterns and/or metadata about the user.DOD Space, Chantilly, VA 20151Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited