GLRT Approach for Robust Burst Packet Acquisition in Wireless Communications

Abstract

Rapid detection of the arrival of a packet is challenging in burst wireless communications, where many parameters are unknown, such as signal power, noise power and carrier phase offset. Due to the unknown noise power, it is hard to set appropriate thresholds for the existing common detectors under the Neyman-Pearson criterion, which results in vulnerable acquisition and poor performance. In order to solve this problem, we propose the generalized likelihood-ratio test (GLRT) approach for sequence-aided packet acquisition in this paper. GLRT detection is formulated under multipath channel. Moreover, false alarm probability and detection probability of GLRT are derived and confirmed via simulations. Comparisons are conducted between GLRT and the common detectors, as well as GLRT under different channels. Results show that GLRT basically reveals more competitive and robust performance than the common detectors in practice, with only a little extra hardware cost by using the provided recursive computation structure. Additionally, it is shown that fading results in significant deterioration for GLRT; whereas GLRT has ability to exploit multipath diversity to reduce fading effect and improve acquisition performance.

Closed-Loop Sparse Channel Estimation for Wideband Millimeter-Wave Full-Dimensional MIMO Systems

“…F ≤ N RF BS to guarantee the constraint on the total transmit power [5]. Here at the CE stage, some elegant solutions [39], [42] can be used to acquire the robust synchronization of burst training signals without the knowledge of noise/interference power even at low SNR.…”

Sparse/dense channel estimation with non‐zero tap detection for 60‐GHz beam training

“…respectively, where the nuisance parameters are h i and σ 2 . Through some manipulations [21], we deriveĥ i (the maximum likelihood estimate (MLE) of…”

“…The detection variable of GLRT [21] in the ith position of the multipath channel can thus be written as…”

“…For a detector for non-zero taps, FAP and DP are crucial factors to evaluate its performance [21,22]. In order to derive the precise expressions of FAP and DP, we need to dispel the dependence between 1 Hh i andh H ihi , which is shown in (17).…”

“…For instance, the length of pilot before channel estimation field is 2176-symbol in IEEE 802.11ad [23]. For symbol synchronisation, the best sampling time can be found out by oversampling and interpolating [21,25]. Since the receiver has accomplished carrier and symbol synchronisation precisely before the channel estimation, these residual synchronisation errors are extremely small in a realistic situation [6].…”