Seek and decode: Random access with physical‐layer network coding and multiuser detection

Abstract

We present a novel cross layer approach to random access (RA) that combines physical-layer network coding (PLNC) with multiuser detection (MUD). PLNC and MUD are applied jointly at the physical level in order to extract any linear combination of messages experiencing a collision. The set of combinations extracted from a whole frame is then processed by the receiver to recover the original packets. A simple pre-coding stage at the transmitting terminals allows the receiver to further increase system diversity. We derive an analytical bound on the system throughput and present simulation results for the decoding at the physical level as well as several performance measures at frame level in block fading channels, namely throughput, packet loss rate and energy efficiency. The results we present are promising and suggest that a cross layer approach leveraging on the joint use of PLNC and MUD can significantly improve the performance of RA systems.

On scalability of physical layer network coding with modulo‐sum mapping overN‐way relay channels

“…It is seen that the same NC is extracted for both methods. The proposed method in He and Liew 13 makes X R after 2 time slots using (1), while our proposed method extracts the same X R in 1 time slot based on PLNC-NWRC using (5). Considering Figure 2, the upper bound of probability of error for X R in He and Liew 13 can be calculated as follows:…”

“…The concept of physical layer network coding (PLNC) was introduced in Zhang et al, 1 which stimulated several research papers in this area, where, for example, some of them investigate code detection issues, [2][3][4][5] some issues related to synchronization analysis, 6 and some provide channel estimation methods in PLNC systems. [7][8][9][10] The basic idea of PLNC challenges the traditional treatment of interference in wireless networks as a destructive phenomenon, by utilizing the interference to increase the throughput.…”

PLNC Decoding: Enabler for Massive MTC in 5G Networks

“…More specifically, the considered scheme combines the principles of (a) contention based random access to allow for access protocol with small signaling overhead; (b) non-orthogonal transmissions, that is, allowing multiple users to transmit simultaneously over the same physical resources to efficiently use the spectrum, and (c) channel coding features to efficiently deal with collisions and exploit code redundancy at frame level. The main focus has been to advance on practical aspects of the PHY/MAC components [3] to improve access connectivity in the framework of mMTC services requiring short packet transmissions. Packet length is therefore a relevant aspect of the study.…”

“…We shall remark that even though in this work we consider that the same payload is repeated in all packets transmission attempts by each user per frame (x k,1 = x k,2 ) a pre-coding consisting in a multiplication over the extended binary field can be applied [3] in a straightforward manner. Such extension, does not modify the PHY-layer procedure.…”

Prioritized Random MAC Optimization Via Graph-Based Analysis

“…If different users select the same time slot for transmission, a packet collision is experienced. While collided packets were irremediably lost in early versions of SA, recent studies have shown that collisions can be resolved by network diversity, multiuser detection, network coding strategies [3]- [5], or by successive interference cancellation (SIC) techniques [6] which substantially improves the system throughput. The key concept behind SIC is that each user might send repetitions of the same message in different slots.…”