Performance evaluation of IB-DFE-based strategies for SC-FDMA systems
© Silva et al.; licensee Springer. 2013
Received: 15 July 2013
Accepted: 9 December 2013
Published: 30 December 2013
The aim of this paper is to propose and evaluate multi-user iterative block decision feedback equalization (IB-DFE) schemes for the uplink of single-carrier frequency-division multiple access (SC-FDMA)-based systems. It is assumed that a set of single antenna users share the same physical channel to transmit its own information to the base station, which is equipped with an antenna array. Two space-frequency multi-user IB-DFE-based processing are considered: iterative successive interference cancellation and parallel interference cancellation. In the first approach, the equalizer vectors are computed by minimizing the mean square error (MSE) of each individual user, at each subcarrier. In the second one, the equalizer matrices are obtained by minimizing the overall MSE of all users at each subcarrier. For both cases, we propose a simple yet accurate analytical approach for obtaining the performance of the discussed receivers. The proposed schemes allow an efficient user separation, with a performance close to the one given by the matched filter bound for severely time-dispersive channels, with only a few iterations.
Single-carrier frequency-division multiple access (SC-FDMA), a modified form of orthogonal frequency-division multiple access (OFDMA), is a promising solution technique for high data rate uplink communications in future cellular systems.
When compared with OFDMA, SC-FDMA has similar throughput and essentially the same overall complexity. A principal advantage of SC-FDMA is the peak-to-average power ratio (PAPR), which is lower than that of OFDMA[1, 2]. SC-FDMA was adopted for the uplink, as a multiple access scheme, of the current long-term evolution (LTE) cellular system.
Single-carrier frequency domain equalization (SC-FDE) is widely recognized as an excellent alternative to OFDM, especially for the uplink of broadband wireless systems[4, 5]. As other block transmission techniques, SC-FDE is suitable for high data rate transmission over severely time-dispersive channels due to the frequency domain implementation of the receivers. Conventional SC-FDE schemes employ a linear FDE optimized under the minimum mean square error (MMSE) criterion. However, the residual interference levels might still be too high, leading to performance that is still several decibels from the matched filter bound (MFB). Nonlinear time domain equalizers are known to outperform linear equalizers and DFE are known to have good performance-complexity tradeoffs. For this reason, there has been significant interest in the design of nonlinear FDE in general and decision feedback FDE in particular, with the IB-DFE being the most promising nonlinear FDE[7, 8]. IB-DFE was originally proposed in and was extended for a wide range of scenarios in the last 10 years, ranging from diversity scenarios[10, 11], MIMO systems, CDMA systems[13, 14], and multi-access scenarios[15, 16], among many other. Essentially, the IB-DFE can be regarded as a low complexity turbo equalizer[17–20] implemented in the frequency domain that do not require the channel decoder output in the feedback loop, although true turbo equalizers based on the IB-DFE concept can also be designed[21–23]. An IB-DFE-based scheme specially designed for offset constellations (e.g., OQPK and OQAM) was also proposed in. In the context of cooperative systems, an IB-DFE approach was derived to separate the quantized received signals from the different base stations (BSs).
Works related to IB-DFE specifically designed for SC-FDMA-based systems are scarce in the literature. In, the authors proposed an IB-DFE structure consisting of a frequency domain feedforward filter and a time domain feedback filter for single-user SC-FDMA systems. An iterative frequency domain multiuser detection for spectrally efficient relaying protocols was proposed in, and a frequency domain soft-decision feedback equalization scheme for single user SISO SC-FDMA systems with insufficient cyclic prefix was proposed in.
In this paper, we consider a broadband wireless transmission over severely time-dispersive channels, and we design and evaluate multi-user receiver structures for the uplink single-input multiple-output (SIMO) SC-FDMA systems that are based on the IB-DFE principle. It is assumed that a set of single antenna user equipment (UE) share the same physical channel to transmit its own information to the base station, which is equipped with an antenna array. Two multi-user IB-DFE-based processing schemes are considered, both with the feedforward and feedback filters designed in space frequency domain: iterative successive interference cancellation (SIC) and parallel interference cancellation (PIC). In the first approach, the equalizer vectors are computed by minimizing the mean square error (MSE) of each individual user at each subcarrier. In the second one, the equalizer matrices are obtained by minimizing the overall MSE of all users at each subcarrier. For both cases, we propose a quite accurate analytical approach for obtaining the performance of the proposed receivers.
The remainder of the paper is organized as follows: Section 2 presents the multi-user SIMO SC-FDMA system model. Section 3 presents in detail the considered multi-user IB-DFE-based receiver structures. The feedforward and feedback filters are derived for both cases and analytical approach for obtaining the performance is discussed. Section 4 presents the main performance results, both numerical and analytical. The conclusions will be drawn in Section 5.
Notation: Throughout this paper, we will use the following notations. Lowercase letters, uppercase letters, are used for scalars in time and frequency, respectively. Boldface uppercase letters are used for both vectors and matrices in frequency domain. The index (n) is used in time while the index (l) is for frequency. (.) H , (.) T , and (.) * represent the complex conjugate transpose, transpose, and complex conjugate operators, respectively, [.] represents the expectation operator, I N is the identity matrix of size N × N, CN(.,.) denotes a circular symmetric complex Gaussian vector, tr(A) is the trace of matrix A, and e k is an appropriate column vector with 0 in all positions except the k th position that is 1.
2. System model
assuming that the cyclic prefix is long enough to account for channel impulse responses between the UEs and the BS. In (1), represents the channel between user k and the m th antenna of the BS on subcarrier l, where denotes the normalized channel frequency response, i.e.,, while the coefficient α k is a weighting factor that accounts for the combined effects of power control and propagation losses. The average received power associated to the k th UE is therefore |α k |2 and is the noise.
The channel vector of the k th user is defined as.
3. Multi-user IB-DFE receiver strategies
In this section, we present in detail the multi-user iterative frequency domain receiver design strategies based on the IB-DFE concept. Two iterative approaches are considered: SIC and PIC.
3.1 IB-DFE SIC approach
with and, being the correlation matrices of data symbols and noise on each carrier.
The Lagrangian multiplier is selected, at each iteration i, to ensure the constraint. It should be emphasizes that for the first iteration (i = 1), and for the first UE to be detected, P(0) is a null matrix and is a null vector.
3.2 IB-DFE PIC approach
where is a matrix of size MxK with all UEs' feedforward vector coefficients, is a matrix of size KxK with all UEs' feedback vector coefficients, and.
Note that the correlation matrices,, and were already defined in (14).
In this approach, the Lagrangian multiplier is selected, at each iteration i, to ensure the constraint. Since all users are detected in parallel, for the first iteration (i = 1), P(0) is a null matrix and is a null vector.
The complexity of the SIC approach is slightly higher than the PIC one. For the SIC, we need to invert a matrix of size M xM for each user on each iteration, while for the PIC one, we need to invert a matrix of size M xM for all users on each iteration, i.e., the SIC approach requires K − 1 more matrix inversions per iteration. Since in the receiver SIC structure, each user is detected individually and sequentially, the delay is also higher.
4. Performance results
In this section, we present a set of performance results, analytical and numerical, for the proposed IB-DFE-based PIC and SIC receiver schemes. Two different scenarios are considered:
Scenario 1, we assume two UEs (K = 2) and a BS equipped with two antennas (M = 2).
Scenario 2, we assume four UEs (K = 4) and a BS equipped with four antennas (M = 4).
For both scenarios, the main parameters used in the simulations are N-FFT size of 1,024; L-DFT size set to 128 (this represents the data symbols block associated to each UE); sampling frequency set to 15.36 MHz; useful symbol duration is 66.6 μs, cyclic prefix duration is 5.21 μs; overall OFDM symbol duration is 71.86 μs; subcarrier separation is 15 kHz, and a QPSK constellation under Gray mapping rule, unless otherwise stated. Most of the parameters are based on LTE system.
The channel between each UE and the BS is uncorrelated and severely time dispersive, each one with rich multipath propagation and uncorrelated Rayleigh fading for different multipath components. Specifically, we assume a L p = 32-path frequency-selective block Rayleigh fading channel with uniform power delay profile (i.e., each path with average power of 1/L p ). The same conclusions could be drawn for other multipath fading channels, provided that the number of separable multipath components is high. Also, we assume perfect channel state information, synchronization and |α k |2 = 1, ∀ k. The results are presented in terms of the average bit error rate (BER) as a function of E b /N0, with E b denoting the average bit energy and N0 denoting the one-sided noise power spectral density. In all scenarios, we present the theoretical and simulation average BER performances for both proposed receiver structures: IB-DFE PIC and SIC. For the sake of comparisons, we also include the matched filter bound (MFB) performance.
From Figure 5, we can also see that the analytical approach proposed for the IB-DFE SIC structure is very accurate. The BER performance approaches, with a number of iterations as low as 4, very closely to the limit obtained with the MFB. This means mean that this receiver structure is also able to efficiently separate the UEs, while taking advantage of the space-frequency diversity inherent to the MIMO SC-FDMA-based systems. Comparing the SIC and the PIC approach, it is clear that for the first iteration the SIC approach outperforms the PIC one. It can be observed a penalty of approximately 1 dB of the PIC against the SIC, for a BER = 10−3. This is because the SIC-based structure to detect a given user takes into account the previous detected ones, with the exception for the first user. However, when the number of iteration increases, the performance of the PIC approach tends to the one given by the SIC approach. We can observe that the BER performance of both approaches is basically the same for four iterations.
The previous results indicate that IB-DFE receivers can have excellent performance, close to the MFB, for MIMO systems with QPSK constellations. One question that arises naturally is if this is still valid for larger constellations such as QAM constellations. In fact, the performance of a DFE for larger constellations can be seriously affected due to error propagation effects. As an example, we present in Figure 8 the performance results for 16-QAM constellations in the second scenario, considering IB-DFE SIC approach. Clearly, we are still able to approach the MFB, although we need more iterations, the convergence is less smooth and we only approach the MFB for lower BER (and, naturally, larger SNR). Although these good results might be somewhat surprising, we should have in mind that an IB-DFE is not a conventional DFE due to the non-causal nature of the feedback. Moreover, the error propagation effects are much lower in IB-DFE receivers due to the following issues:
Symbol errors (which are in the time domain) are spread over all frequencies. Due to the frequency-domain nature of the feedback loop input, a symbol error has only a minor effect on all frequencies.
The FDE is designed to take into account the reliability of estimates employed in the feedback loop. When we have a large number of symbol errors, the reliability decreases and the weight of the feedback part decreases.
When we have a decision error, we usually move to one of the closer constellation symbols, i.e., the magnitude of the error is usually the minimum Euclidean distance of the constellation, regardless of the constellation size. This is especially important for larger constellations.
As we pointed out, an IB-DFE can be regarded as a complexity turbo equalizer implemented in the frequency-domain which does not employ a channel decoder in the feedback loop. For this reason, it has a turbo-like behavior with good performance provided that the BER is low enough. That is why we can only approach the MFB for larger SNR.
In this paper, we designed and evaluated multi-user receiver structures based on the IB-DFE principle for the uplink SIMO SC-FDMA systems. Two multi-user IB-DFE PIC- and SIC-based processing schemes were considered. In the first approach, the equalizer vectors were computed by minimizing the mean square error (MSE) of each individual user at each subcarrier. In the second one, the equalizer matrices were obtained by minimizing the overall MSE of all users at each subcarrier. For both cases, we proposed a quite accurate analytical approach for obtaining the performance of the proposed receivers.
The results have shown that the proposed receiver structures are quite efficient to separate the users, while allowing a close-to-optimum space-diversity gain, with performance close to the MFB (severely time-dispersive channels) with only a few iterations. The performance of both PIC and SIC receiver structures is basically the same after three or four iterations. However, the main drawback of the SIC approach is the delay in the detection procedure, which is larger than for the PIC, since it detects one user at each time. Thus for practical systems, where the delay is a critical issue, the PIC approach can be the best choice.
To conclude, we can clearly state that these techniques are an excellent choice for the uplink SC-FDMA-based systems, already adopted by the LTE standard.
This study was supported by the Portuguese Fundação para a Ciência e Tecnologia (FCT) COPWIN (PTDC/EEI-TEL/1417/2012), CROWN (PTDC/EEA-TEL/115828/2009), and ADIN (PTDC/EEI-TEL/2990/2012) projects.
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