Perspectives of Jamming, Mitigation and Pattern Adaptation of OFDM Pilot Signals for the Evolution of Wireless Networks

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Date
2016-09-15
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Virginia Tech
Abstract

Wireless communication networks have evolved continuously over the last four decades in order to meet the traffic and security requirements due to the ever-increasing amount of traffic. However this increase is projected to be massive for the fifth generation of wireless networks (5G), with a targeted capacity enhancement of 1000× w.r.t. 4G networks. This enhanced capacity is possible by a combination of major approaches (a) overhaul of some parts and (b) elimination of overhead and redundancies of the current 4G. In this work we focus on OFDM reference signal or pilot tones, which are used for channel estimation, link adaptation and other crucial functions in Long-Term Evolution (LTE). We investigate two aspects of pilot signals pertaining to its evolution - (a) impact of targeted interference on pilots and its mitigation and (b) adaptation of pilot patterns to match the channel conditions of the user.

We develop theoretical models that accurately quantify the performance degradation at the user’s receiver in the presence of a multi-tone pilot jammer. We develop and evaluate mitigation algorithms to mitigate power constrained multi-tone pilot jammers in SISO- and full rank spatial multiplexing MIMO-OFDM systems. Our results show that the channel estimation performance can be restored even in the presence of a strong pilot jammer. We also show that full rank spatial multiplexing in the presence of a synchronized pilot jammer (transmitting on pilot locations only) is possible when the channel is flat between two pilot locations in either time or frequency.

We also present experimental results of multi-tone broadcast pilot jamming (Jamming of Cell Specific Reference Signal) in the LTE downlink. Our results show that full-band jamming of pilots needs 5 dB less power than jamming the entire downlink signal, in order to cause Denial of Service (DoS) to the users. In addition to this, we have identified and demonstrated a previously unreported issue with LTE termed ‘Channel Quality Indicator (CQI) Spoofing’. In this scenario, the attacker tricks the user terminal into thinking that the channel quality is good, by transmitting interference transmission only on the data locations, while deliberately avoiding the pilots. This jamming strategy leverages the dependence of the adaptive modulation and coding (AMC) schemes on the CQI estimate in LTE.

Lastly, we investigate the idea of pilot pattern adaptation for SISO- and spatial multiplexing MIMO-OFDM systems. We present a generic heuristic algorithm to predict the optimal pilot spacing and power in a nonstationary doubly selective channel (channel fading in both time and frequency). The algorithm fits estimated channel statistics to stored codebook channel profiles and uses it to maximize the upper bound on the constrained capacity. We demonstrate up to a 30% improvement in ergodic capacity using our algorithm and describe ways to minimize feedback requirements while adapting pilot patterns in multi-band carrier aggregation systems. We conclude this work by identifying scenarios where pilot adaptation can be implemented in current wireless networks and provide some guidelines to adapt pilots for 5G.

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Keywords
Pilot Pattern Adaptation, OFDM systems, Long-Term Evolution (LTE)/LTE Cell-Specific Refe, Multi-tone Pilot Jamming, Channel Quality Indicator (CQI) Spoofing, Mitigation
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