摘要 :
Interference alignment (IA) is a precoding technique that aligns interfering signals at receivers. It is known that IA achieves the maximum degrees of freedom over an interference channel under ideal assumptions. The real-world pe...
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Interference alignment (IA) is a precoding technique that aligns interfering signals at receivers. It is known that IA achieves the maximum degrees of freedom over an interference channel under ideal assumptions. The real-world performance of IA depends on a range of practical issues, such as imperfect synchronization, channel estimation, and feedback. Practical issues have been studied in simulations and prototypes, but fully distributed operation of IA network nodes has not been considered. In this paper, we present the first investigation of real-time IA performance on a fully distributed 2 2 multiple-input–multiple-output (MIMO) prototype system with three physically independent user pairs. Over-the-air algorithms for time and frequency synchronization, as well as analog feedback, are studied and implemented. Sum rates are illustrated as a function of complexity and accuracy of different alignment, synchronization, and feedback algorithms. Corresponding tradeoffs are evaluated using an iterative IA method, the injection of residual frequency offset into synchronization, and analog versus quantization-based limited feedback approaches. We demonstrate that, while considering all possible error sources in estimation, synchronization, and feedback, the theoretical multiplexing gain of IA can be reached in practical systems with a constant sum rate loss that remains within 5 bits/Hz/s compared with an ideal simulation.
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The $K$-user single-input single-output (SISO) additive white Gaussian noise (AWGN) interference channel and $2times K$ SISO AWGN X channel are considered, where the transmitters have delayed channel state information (CSI) throug...
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The $K$-user single-input single-output (SISO) additive white Gaussian noise (AWGN) interference channel and $2times K$ SISO AWGN X channel are considered, where the transmitters have delayed channel state information (CSI) through noiseless feedback links. Multiphase transmission schemes are proposed for both channels which possess novel ingredients, namely, multiphase partial interference nulling, distributed interference management via user scheduling, and distributed higher order symbol generation. The achieved degree-of-freedom (DoF) values are greater than the best previously known DoFs for both channels with delayed CSI at the transmitters.
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With the rapid growth of network users, how to increase the system capacity has become an urgent problem for the current communication system in the case of limited spectrum resources. The introduction of multi-user systems has in...
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With the rapid growth of network users, how to increase the system capacity has become an urgent problem for the current communication system in the case of limited spectrum resources. The introduction of multi-user systems has increased system capacity, but it has also led to inter-user interference, which has further affected system capacity. To solve the multi-user interference problem, interference alignment is introduced. Interference Alignment (IA) is an interference cancellation technique that effectively eliminates the effects of interfering signals by compressing the interfering signal into a space independent of the desired signal and then forcing the interfering signal to zero at the receiving end. However, in practical applications, interference-aligned transceivers require a joint design, which is often difficult to achieve. The traditional approach is to mathematically expect it, but it also leads to some degree of irrationality in the transceiver design. In this paper, based on the traditional least square interference alignment (LS-IA) algorithm, a symbol-detection-assisted least square interference alignment (SDA-LS-IA) algorithm is proposed for its shortcomings in transceiver algorithm design. Firstly, based on the precoding matrix and the zero-forcing matrix of the transceiver designed by the traditional LS-IA, the symbol detection is performed, and then the transceiver is designed again according to the detection symbol, and then the symbol detection is performed. The computer simulation proves that the proposed algorithm has better anti-interference performance than the traditional LS-IA.
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Interference alignment (IA) is a technique shown to be able to achieve a significant overall throughput in a if-user multiple-input multiple-output (MIMO) interference channel (IC). In this paper, we try to modify the conventional...
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Interference alignment (IA) is a technique shown to be able to achieve a significant overall throughput in a if-user multiple-input multiple-output (MIMO) interference channel (IC). In this paper, we try to modify the conventional IA designs to achieve enhanced sum-rate performance. We jointly design transmit and receive IA filters (precoding and suppression filters) at a central unit (CU) to reduce the channel state information (CSI) feedback/sharing overhead. At the CU, in a one-way iterative strategy (left 'L' to right 'R', see Fig. 1), the precoding filters are optimized (on side 'L') in the direction of the gradient of the sum-rate, and the suppression filters are chosen (on side 'R') to minimize the leakage interferences. Then, in a two-way iterative strategy, the proposed scheme alternates between 'L' and 'R' sides to design the IA filters through the joint sum-rate maximization and interference leakage minimization on each side. Finally, a modified version of the two-way iterative strategy is proposed to design the IA filters on the basis of signal-to-interference-plus-noise ratio (SINR) (instead of the interference minimization) and the sum-rate maximization techniques. Comparing to other conventional IA designs, the proposed designs with provable convergence show a significant sum-rate performance improvement and often outperform other widely used algorithms, as shown in the simulation examples.
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摘要 :
Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. Most of the existing IA designs require full channel state information (CSI) at the transmi...
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Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. Most of the existing IA designs require full channel state information (CSI) at the transmitters, which induces a huge CSI signaling cost. Hence it is desirable to improve the feedback efficiency for IA and in this paper, we propose a novel IA scheme with a significantly reduced CSI feedback. To quantify the CSI feedback cost, we introduce a novel metric, namely the feedback dimension. This metric serves as a first-order measurement of CSI feedback overhead. Due to the partial CSI feedback constraint, conventional IA schemes can not be applied and hence, we develop a novel IA precoder/decorrelator design and establish new IA feasibility conditions. Via dynamic feedback profile design, the proposed IA scheme can also achieve a flexible tradeoff between the degree of freedom (DoF) requirements for data streams, the antenna resources and the CSI feedback cost. We show by analysis and simulations that the proposed scheme achieves substantial reductions of CSI feedback overhead under the same DoF requirement in MIMO interference networks.
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In this paper, we investigate iterative interference alignment (IA) approaches for multi-input multi-output (MIMO) multicell communication systems. We proposed an iterative reweighted least square (IRLS) approach for MIMO interfer...
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In this paper, we investigate iterative interference alignment (IA) approaches for multi-input multi-output (MIMO) multicell communication systems. We proposed an iterative reweighted least square (IRLS) approach for MIMO interference channel in single-cell scenario. The basic contribution of this paper is to extend the proposed IRLS algorithm to the more practical case of aligning co-channel interference signals in orthogonal frequency division multiple access (OFDMA) based cellular systems. The simulation results show that the proposed approach achieves a superior total system sum-rate than both the conventional Orthogonal-Minimum Leakage (OR-ML) and the Orthogonal-Maximum Signal to Interference Noise Ratio (OR-MSINR) approaches.
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This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under a Gaussian Interference compounded broadcast channel scenario. The basic idea is to s...
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This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under a Gaussian Interference compounded broadcast channel scenario. The basic idea is to split up the role of the transmit beamforming matrix according to the type of interference caused by each base station. It will be shown that, for a network of base stations, the proposed method would result in achieving degrees of freedom per user and convert the multi-cell multi-user MIMO channel into a set of single-cell single-user MIMO channels. Finally, we derive the relationship between all the relevant network elements as , where and are the numbers of transmit and receive antennas, respectively, and denote the number of cells and the number of data streams transmitted from each base station, and is the number of users per cell defined under the proposed system model. Hence, we show that the proposed scheme makes it possible to implement interference alignment using less antenna resources.
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An interference alignment (IA) scheme is presented that allows multiple opportunistic transmitters (secondary users) to use the same frequency band of a pre-existing primary link without generating any interference. The primary an...
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An interference alignment (IA) scheme is presented that allows multiple opportunistic transmitters (secondary users) to use the same frequency band of a pre-existing primary link without generating any interference. The primary and secondary transmit-receive pairs are equipped with multiple antennas. Under power constraints on the primary transmitter, the rate of the primary user is maximized by water-filling on the singular values of its channel matrix leaving some eigen modes unused, and hence, the secondary users can align their transmitted signals to produce a number of interference-free dimensions at each secondary receiver without causing any interference to the primary user. An outer bound is developed on the degrees of freedom (DoF) of the secondary users. In the case of a symmetric secondary network with time-varying channel coefficients having $M$ antennas at each node and operating in the presence of a primary link with $d_0$ active eigen modes, a precoding scheme is presented for the secondary transmitters that can asymptotically achieve the available $(M-d_0)^+/2$ DoF per secondary user. An iterative algorithm is also presented that utilizes channel reciprocity to achieve the proposed cognitive IA scheme. For a cognitive 3-user secondary network with constant channel coefficients, a novel closed-form solution is derived for the precoding matrices of the secondary users.
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Interference alignment (IA) is a promising technique to effectively manage the interference. The realization of IA requires a proliferation of feedback bits. In a general centralized feedback model, the feedback rate of the precod...
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Interference alignment (IA) is a promising technique to effectively manage the interference. The realization of IA requires a proliferation of feedback bits. In a general centralized feedback model, the feedback rate of the precoder and the decoder affects the performance of the IA directly. In this paper, to improve the feedback efficiency of the precoder and the decoder, a strategy that can adaptively allocate the feedback bits of the precoder and the decoder is proposed. We consider the effect of link loss on the throughput loss caused by the quantization error of the precoder and decoder. An upper bound of leaked interference as a function of the link loss and the feedback bits of the precoders and the decoders is derived. The feasibility conditions for dynamically allocating the feedback bits of the precoder and the decoder are analyzed. It is proven that the properties of general asymmetric interference network can satisfy the feasibility conditions for dynamic feedback scheme. According to the simulation results, our proposed scheme achieves higher throughput compared with the conventional schemes in the asymmetric interference network.
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To deal with ever-growing wireless services and to increase network throughput, it has been proposed to deploy femtocells with frequency reuse based on orthogonal frequency-division multiple access (OFDMA). However, the interferen...
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To deal with ever-growing wireless services and to increase network throughput, it has been proposed to deploy femtocells with frequency reuse based on orthogonal frequency-division multiple access (OFDMA). However, the interference poses big challenges, particularly for dense deployment scenarios. The resource allocation with joint consideration of subchannel assignment and interference alignment (IA) is different from the traditional problems. First, we need to select the users to perform IA since the number of participant users is limited by the feasibility constraint, and the interference power levels are different due to the path loss. Second, IA increases the degrees of freedom (DoFs) while occupying the additional signal dimension of the participant user; hence, the entirety of the participants in IA require more subchannels compared with the nonparticipants when each of the users transmits the same number of streams. In this paper, we propose a transformed conflict graph-based resource-allocation scheme, where the users are selected according to the effect of IA on the requirement under the feasibility constraint. Then, the subchannel assignment can be modeled as a classical color problem. Extensive simulations show that our scheme can approximate the optimal scheme in a small network and effectively improve the satisfactory ratio of users compared with the scheme without IA in dense femtocell networks.
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