Per-Chip Multi-User Detection for SFH/BPSK Systems

Ren, Yinpeng; Ni, Zuyao; Lu, Jianhua

doi:10.1109/vtcfall.2015.7391067

Cited by 1 publication

(3 citation statements)

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“…After de-hopping, the received pilots is expressed as (14), where hR ≤ l ≤ hR + P/2 and (h + 1)R − P/2 ≤ l ≤ (h + 1)R. By correlating the received pilots with the transmitted pilots, we can perform the maximum-likelihood (ML) estimation. The results of the correlation for each hop is given by…”

Section: Parameters Initializationmentioning

confidence: 99%

“…In recent years, there has been effective work on improving the performance of frequency hopping systems [12][13][14], it was assumed that the receiver has full knowledge of hopping patterns of all users. This assumption requires additional coordination among users and is usually appropriated for a base station (BS)-mobile station (MS) scenario.…”

Section: Introductionmentioning

confidence: 99%

“…Although the PH-MUD can work well for synchronous frequency hopping systems, it may revert to PH-SUD without the knowledge of the hopping patterns and pilot signals of the interfering users. Similarly, the PC-MUD proposed in [14] may not work in this scenario as the MAI model is unknown. For the SFH/BPSK systems, to the best of our knowledge, there is no feasible MUD algorithm exists in the scenario of ad hoc network.…”

Section: Introductionmentioning

confidence: 99%

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Joint interference estimation and cancellation for coherent frequency hopping multiple-access systems

Ren

et al. 2016

J Wireless Com Network

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In this paper, we propose an iterative detection algorithm that reconstructs and cancels the multiple-access interference jointly without the knowledge of hopping patterns of the interfering users for SFH/BPSK systems in an ad hoc scenario. Since users are asynchronous in this scenario, signal in one hop of the desired users is affected by partial signals in unaligned hops, called the interference fragments, of the interfering users. We address the interference model by defining a virtual user, which has the same hopping pattern as that of the desired user and contains the feature of the interfering fragments. Then, we derive the joint interference reconstruction and multiple-user detection (MUD) algorithm using the factor graph framework. Simulation results show that the performance of the proposed algorithm can be improved by up to 2 dB than that of the traditional single user detection (SUD) in AWGN at the packet error rate of 10 −2 for a total of 8 users over 20 hopping frequencies, and an outstanding performance may also be achieved in the channel with Doppler.

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Section: Parameters Initializationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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