Wireless relays extend coverage, improve spectral efficiency, and enhance reliability and rates of wireless cellular communication systems. In this work, we introduce the fundamental notion of asymmetric cooperation a...
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Wireless relays extend coverage, improve spectral efficiency, and enhance reliability and rates of wireless cellular communication systems. In this work, we introduce the fundamental notion of asymmetric cooperation among cooperating relays in cellular downlinks - different relays are party to different but overlapping knowledge about the messages transmitted from the base station. We argue that asymmetric cooperation arises naturally in most two-phase protocols In which the base station first transmits information to multiple relays that then cooperatively forward the information to the recipient mobile stations in the cell. For a system in which two relays are of the decode-and-forward type and cooperate using linear precoding to communicate with two mobile stations, we formulate the general, but complicated, throughput optimization problem and derive several results that considerably simplify the optimization. We show that under different channel configurations and fairness criteria, asymmetric cooperation is often the throughput-maximizing option. Under typical configurations, a 20-30% throughput enhancement is achieved compared to conventional full-cooperation systems.
Multi-antenna relaying has emerged as a promising technology to enhance the system performance in cellular networks. However, when precoding techniques are utilized to obtain multi-antenna gains, the system generally ...
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Multi-antenna relaying has emerged as a promising technology to enhance the system performance in cellular networks. However, when precoding techniques are utilized to obtain multi-antenna gains, the system generally requires channel state information (CSI) at the transmitters. We consider a linear precoding scheme in a MIMO relaying broadcast channel with quantized CSI feedback from both two-hop links. With this scheme, each remote user feeds back its quantized CSI to the relay, and the relay sends back the quantized precoding information to the base station (BS). An upper bound on the rate loss due to quantized channel knowledge is first characterized. Then, in order to maintain the rate loss within a predetermined gap for growing SNRs, a strategy of scaling quantization quality of both two-hop links is proposed. It is revealed that the numbers of feedback bits of both links should scale linearly with the transmit power at the relay, while only the bit number of feedback from the relay to the BS needs to grow with the increasing transmit power at the BS. Numerical results are provided to verify the proposed strategy for feedback quality control.
This paper investigates the performance of linear precoders in massive multiple-input multiple-output (MIMO) systems. Different from the existing research, in this paper, we consider a more realistic scenario, where t...
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This paper investigates the performance of linear precoders in massive multiple-input multiple-output (MIMO) systems. Different from the existing research, in this paper, we consider a more realistic scenario, where the input signals are taken from finite-alphabet constellation sets, such as phase shift keying (PSK) or quadrature amplitude modulation (QAM), instead of Gaussian signals. The expressions are derived for the achievable mutual information with two commonly known linear precoders, i.e., zero forcing (ZF) and matched filter (MF), in the scenarios were perfect and imperfect channel state information (CSI) is known at the base station (BS). Also, the performance upper bound of mutual information with precoding techniques is analyzed. Both the theoretical analysis and simulation results show that ZF and MF precoders are near optimal when the number of antennas equipped at the BS is much larger than the number of users, which is similar to the case of Gaussian inputs. However, different from the Gaussian inputs, for the case of finite-alphabet inputs, the increase in the number of antennas does not always mean the improvement of performance;specifically, after the number of antennas at the BS, reaches a certain value, more antennas actually almost have no help for the performance improvement of mutual information, which is true whether the CSI is perfect or imperfect.
We consider the use of linear constellation precoding and linear detection in a multicarrier OFDM system with multiple receive antennas to obtain improved performance over multipath fading channels at a low complexity...
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We consider the use of linear constellation precoding and linear detection in a multicarrier OFDM system with multiple receive antennas to obtain improved performance over multipath fading channels at a low complexity. We split the full set of subcarriers into smaller groups and spread the data symbols assigned to each group via precoding matrices. We adopt the diversity-multiplexing tradeoff (DMT) framework and derive the DMT-optimal split of the subcarriers (DMT-optimal grouping) and the DMT-optimal number of symbols assigned to each group (DMT-optimal symbol loading). We determine necessary and sufficient precoder design conditions to achieve DMT optimality and give specific constructions of such precoders. Next, we consider a multiuser OFDMA system and derive an algorithm which divides the available subcarriers among the active users in order to maximize the diversity order of the system (or joint) error probability. We also extend our analysis to OFDM systems equipped with multiple transmit antennas. Finally, we obtain important insights on the role of outer codes in an OFDM system employing linear precoding and linear equalization.
This work studies the robust design of linear precoding and linear/ non-linear equalization for multi-cell MIMO systems in the presence of imperfect channel state information (CSI). A worst-case design approach is ado...
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This work studies the robust design of linear precoding and linear/ non-linear equalization for multi-cell MIMO systems in the presence of imperfect channel state information (CSI). A worst-case design approach is adopted whereby the CSI error is assumed to lie within spherical sets of known radius. First, the optimal robust design of linear precoders is tackled for a MIMO interference broadcast channel (MIMO-IBC) with general unicast/multicast messages in each cell and operating over multiple time-frequency resources. This problem is formulated as the maximization of the worst-case sum-rate assuming optimal detection at the mobile stations (MSs). Then, symbol-by-symbol non-linear equalization at the MSs is considered. In this case, the problem of jointly optimizing linear precoding and decision-feedback (DF) equalization is investigated for a MIMO interference channel (MIMO-IC) with the goal of minimizing the worst-case sum-mean squared error (MSE). Both problems are addressed by proposing iterative algorithms with descent properties. The algorithms are also shown to be implementable in a distributed fashion on processors that have only local and partial CSI by means of the Alternating Direction Method of Multipliers (ADMM). From numerical results, it is shown that the proposed robust solutions significantly improve over conventional non-robust schemes in terms of sum-rate or symbol error rate. Moreover, it is seen that the proposed joint design of linear precoding and DF equalization outperforms existing separate solutions.
This paper extends the self-contained theory of linear precoding to the field of covariance based spatio-temporal downlink processing for direct-sequence code-division multiple-access (CDMA) systems and shows the appl...
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This paper extends the self-contained theory of linear precoding to the field of covariance based spatio-temporal downlink processing for direct-sequence code-division multiple-access (CDMA) systems and shows the applicability to the release 6 of high-speed downlink packet access (HSDPA). To this end, a unifying theory is developed to formulate the three known linear filters, namely, the transmit matched filter, the transmit zero-forcing filter, and the transmit Wiener filter, as optimization problems even in systems, where only covariance knowledge is available at the transmitter. Second, the solutions of these transmit filters are given for such systems with partial channel state information (CSI). Finally, it is shown how covariance-based linear precoding can be employed in the new generation CDMA system HSDPA, i.e., how channel estimation on the secondary common pilot channel allows for optimum full rank linear precoding employing only partial CSI.
In this paper, we study a simplified linear precoding scheme for far-end crosstalk (FEXT) cancellation in very high bit-rate digital subscriber line (VDSL) downstream transmission. We compare the proposed method to ze...
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In this paper, we study a simplified linear precoding scheme for far-end crosstalk (FEXT) cancellation in very high bit-rate digital subscriber line (VDSL) downstream transmission. We compare the proposed method to zero-forcing (ZF) FEXT cancellation and show that for multipair VDSL systems the method achieves rates that are close to the ZF precoding method. We also derive simple lower bounds on the performance that allows us to predict the performance of the proposed algorithm on each tone. We end up with testing the proposed method on theoretical and empirical channels. This is the first extensive study of VDSL precoding on measured channel data. The proposed method is less complex than ZF precoding and, therefore, *** computational load at the initialization and tracking of precoded VDSL or VDSL2 systems. Finally, we discuss implementation complexity in terms of total Silicon area and show that the method has favorable implementation complexity, since only channel coefficients need to be stored during steady-state transmission.
Multiple-input multiple-output (MIMO) orthogonal-frequency division multiplexing (OFDM) multicasting system is considered. For a real-time multicast MIMO-OFDM system, we propose a non-iterative and simple linear preco...
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Multiple-input multiple-output (MIMO) orthogonal-frequency division multiplexing (OFDM) multicasting system is considered. For a real-time multicast MIMO-OFDM system, we propose a non-iterative and simple linear precoding that consists of a linear sum (LS) of the corresponding channels. Through numerical results, we show that a minimum user rate of the proposed LS precoding is almost identical to its performance upper bound, which can be obtained through max-min rate maximization.
In order to account for spatial correlation in a multiple input multiple output (MIMO) channel using precoding over Space-Time Block Codes (STBC), an approach was proposed for the design of a linear precoder [1]. This...
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In order to account for spatial correlation in a multiple input multiple output (MIMO) channel using precoding over Space-Time Block Codes (STBC), an approach was proposed for the design of a linear precoder [1]. This approach works well for orthogonal STBC but fails in the case of non-orthogonal STBC. Based on a Min-Max problem formulation, a new design of the linear precoder is proposed in this paper. Simulation results in the case of quasi-orthogonal STBC (ABBA) are presented in order to show the gain over the conventional design approach and the non-precoded system.
According to research, the performance of the massive MIMO system is constrained by pilot contamination. Recent developments in massive MIMO provide a variety of methods for the reduction of pilot contamination with d...
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According to research, the performance of the massive MIMO system is constrained by pilot contamination. Recent developments in massive MIMO provide a variety of methods for the reduction of pilot contamination with diverse performances. There is a trade-off between the complexity of the system, the time-frequency resources needed to estimate the channel, and the effectiveness of pilot contamination mitigation. Limited research exists on the analysis of the combined effect of the three parameters, despite the impact of the parameters on the performance of massive MIMO multi-cell networks. Therefore, in this research, an algorithm consisting of a combined adaptive linear precoding and pilot assignment methods was designed for the reduction of pilot contamination in the massive MIMO multi-cellular network. The Maximum ratio Transmission (MRT) and Zero Forcing (ZF) precoding schemes were incorporated in the algorithm to diminish interfering signals from other cells while amplifying the intended signal, to improve the BER at low computational complexity. Pilot assignment methods of frequency reuse and the Zadoff-Chu sequence facilitated the optimal allocation of resources and reduced interference to improve spectral efficiency. The pilot assignment method ensures an optimal number of pilots are assigned to guarantee the efficient use of resources while precoding schemes eliminate interference. The effectiveness of the proposed algorithm was evaluated based on the ability to reduce BER, increase spectral efficiency, and reduce computational complexity. The results show improved performance of the proposed algorithm, compared to the conventional MRT and ZF precoders. Accordingly, this study contributes to the investigation of the impact of integrating adaptive linear precoding and pilot assignment methods for pilot contamination mitigation in massive MIMO systems.
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