Abstract
We address the problem of superimposed trainings- (STs-) based linearly time-varying (LTV) channel estimation and symbol detection for orthogonal frequency-division multiplexing access (OFDMA) systems at the uplink receiver. The LTV channel coefficients are modeled by truncated discrete Fourier bases (DFBs). By judiciously designing the superimposed pilot symbols, we estimate the LTV channel transfer functions over the whole frequency band by using a weighted average procedure, thereby providing validity for adaptive resource allocation. We also present a performance analysis of the channel estimation approach to derive a closed-form expression for the channel estimation variances. In addition, an iterative symbol detector is presented to mitigate the superimposed training effects on information sequence recovery. By the iterative mitigation procedure, the demodulator achieves a considerable gain in signal-interference ratio and exhibits a nearly indistinguishable symbol error rate (SER) performance from that of frequency-division multiplexed trainings. Compared to existing frequency-division multiplexed training schemes, the proposed algorithm does not entail any additional bandwidth while with the advantage for system adaptive resource allocation.
Highlights
Orthogonal Frequency-Division Multiplexing Access (OFDMA) is a promising technique for future high-speed broadband wireless communication systems, and it has recently been proposed or adopted in many industry standards (e.g., IEEE 802.16e [1], 3 GPP Long Term Evolution (LTE) [2])
In conventional pilot-aided approaches wherein the pilot symbols are frequency-division multiplexed (FDM) with the data symbols [3,4,5,6,7,8, 10,11,12,13,14,15]; channel estimation can only be performed within each subband of individual user separately since each user is only assigned a subset of the whole frequency band
Unlike conventional FDM training strategy [12,13,14,15] where channel estimation can only be performed within each subband of individual user separately, the linearly time-varying (LTV) uplink channel transfer functions over the whole frequency band can be estimated directly by using designed superimposed training
Summary
Orthogonal Frequency-Division Multiplexing Access (OFDMA) is a promising technique for future high-speed broadband wireless communication systems, and it has recently been proposed or adopted in many industry standards (e.g., IEEE 802.16e [1], 3 GPP Long Term Evolution (LTE) [2]). In conventional pilot-aided approaches wherein the pilot symbols are frequency-division multiplexed (FDM) with the data symbols [3,4,5,6,7,8, 10,11,12,13,14,15]; channel estimation can only be performed within each subband of individual user separately since each user is only assigned a subset of the whole frequency band This may be a great disadvantage for OFDMA systems with adaptive resource allocation. Unlike conventional FDM training strategy [12,13,14,15] where channel estimation can only be performed within each subband of individual user separately, the LTV uplink channel transfer functions over the whole frequency band can be estimated directly by using designed superimposed training. IK denotes the identity matrix of size K, and []k,t denotes the (k, t) element of the specified matrix
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