On Discrete Memoryless Relay Channels with Designable Transmitter Side Information

The achievable degree of freedom (DoF) boosting has been demonstrated on a single-input single-output (SISO) X channel by using outdated and instantaneous channel state information at transmitter (CSIT) synergistically, in contrast to that of using completely outdated CSIT. However, the means by which the DoF gain can be obtained in a multiple-input multiple-output (MIMO) system remains unclear. This paper proposes an interference alignment scheme with synergistic CSIT for MIMO X channel. We show that the achievable DoF is greater than the optimal DoF obtained with outdated CSIT, and that achievable DoF equals to the optimal value with outdated CSIT and transmitter cooperation.

Multiple-input multiple-output (MIMO) wireless communication systems in combination with orthogonal frequency division multiple access and space division multiple access are flexible, spectrally efficient and of high capacity. These systems can allocate frequency, time, and space resources adaptively among mobile stations. Optimal resource allocation (RA) for maximizing the sum rate is usually too complex for practical applications, hence suboptimal algorithms are required. The performance of RA algorithms are degraded due to imperfections in channel state information at transmitter (CSIT). Thus, techniques that make the RA algorithm, robust against CSIT errors are favorable. In this paper, two novel suboptimal grouping algorithms are introduced that are shown to achieve better sum rate-complexity and fairness-complexity performances. A novel index is proposed to measure the efficiency of RA algorithms, which takes into account sum rate and complexity simultaneously. Moreover, the effect of erroneous CSIT on sum rate is investigated and it is shown that performance of the proposed RA algorithms with erroneous CSIT are superior to the existing schemes. Finally, fairness performance of the proposed RA algorithms are evaluated, which are shown to be the same if not superior to other existing algorithms.

The performance of adaptively grouped multilevel space---time trellis codes (AGMLSTTCs) is limited due to predefined component space---time trellis codes (STTCs) used in multilevel coding and lack of beamforming. In this paper, we present improvement in performance of AGMLSTTCs by combining beamforming and dynamic selection of component STTCs with AGMLSTTCs to design new codes henceforth referred to as weighted adaptively grouped multilevel dynamic space---time trellis codes. The channel state information at transmitter (CSI) is used to select a code set having different sets of generator sequences. The selected code set is used for generating dynamic STTCs (DSTTCs). The DSTTCs are used as component codes in multilevel coding. We use a single full-diversity DSTTC at some initial levels and multiple DSTTCs at some later levels. The single full diversity DSTTC at each initial level spans all transmit antennas and the DSTTC at each later level spans a group of transmit antennas. The CSI is further used to provide a beam forming scheme by properly weighting transmitted signals. Weights are selected that based on CSI at transmitter. The simulation results show that AGMLSTTCs combined with beamforming and DSTTCs provide significant improved error performance over grouped multilevel space---time trellis codes and AGMLSTTCs.

In this paper, we investigate the topological interference management (TIM) for MIMO interference broadcast channels (IBC) under the fixed topology, where only topology information is needed to cancel the inter-cell interference (ICI). For the single user case, where the MIMO IBC network is reduced to the MIMO interference channel (IC) networks, we propose one novel TIM scheme by exploiting the solution to the corresponding SISO IC TIM based on topology information. And also, we present one theorem to characterize the achievable degrees of freedom (DoFs). For the multiple user case, assuming that each BS not only knows topology information but also knows the channel state information at transmitters (CSIT) within its own cell, we propose two novel TIM schemes, i.e., the virtual user compression-based scheme and the virtual base station extension-based scheme. For each scheme, we design transceivers to cancel both the ICI only based on the topology information by exploiting the solution to the corresponding SISO IC TIM and the multiple user interference (MUI) within its own cell based on the CSIT. Furthermore, we present one theorem to characterize the achievable DoF, respectively. Moreover, we prove that the DoF achieved by the virtual base station extension-based scheme is higher than or equal to that achieved by the virtual user compression-based scheme. Hence, the achievable DoF of MIMO IBC TIM is lower bounded by the optimal DoF attainable for the base station extension scheme. Furthermore, the numerical results show that our schemes can achieve significant performance gain against the traditional interference avoidance scheme.

In this paper we investigate the codebook design for a time division duplex (TDD) non-antenna switching system, where the user device is equipped with two receive radio frequency (RF) chains but only one transmit RF chain. To acquire the channel state information at transmitter (CSIT), we resort to a mixture of channel sounding and limited feedback, where the former is employed to obtain the CSIT of the antenna connected to the transmit RF chain and the latter is employed for the other antenna. We propose a deep learning method to design the codebook for limited feedback. The learned codebook is distinguished from the traditional ones in two ways. First, the learned codebook is so-called personalized, which is not fixed but adapt to the partially known CSIT. Second, the codebook exhibits different beam patterns from the traditional codebook that is designed for quantization error minimization. Simulation results demonstrate that the learned codebook can achieve higher data rate with lower complexity than traditional codebook.

In many modern wireless systems that operate based on availability of channel state information at transmitter (CSIT), one of the main bottlenecks is updating CSIT of the time varying channel. In multiple-input multiple-output (MIMO) broadcast channels, CSIT is required for user scheduling and precoding. Most existing CSI feedback reduction techniques reduce the number of feedback terms by allowing only a limited number of users to feedback CSI, or allowing only partial/limited information of user channels to be send back to the transmitter. In this work, CSI is reduced over several time-slots of transmission, and not in a single snapshot at the beginning of each time-slot. A time-varying MIMO broadcast channel with limited-capacity feedback links is considered. An efficient threshold-based feedback technique that maximises net-throughput is proposed. The proposed scheme assigns different CSI feedback rates over several time-slots to different groups of users proportional to their channel strength. Analysis and simulation results for zero-forcing beamforming precoding show net-throughput superiority of the proposed scheme over the case of perfect CSI.

Adapting user selection, power allocation and rate allocation, cross layer centralized scheduling can achieve a tremendous gain due to multiuser selection diversity in wireless networks. Yet, conventional cross layer designs all require channel state information at transmitters (CSIT), which is difficult to obtain in practice. In this paper, a closed loop cross layer design with no CSIT in a block fading frequency selective environment is proposed as an extension of flat fading case in (Ka Ming Ho, 2006). The solution to optimal power, rate allocation and user selection involves stochastic programming and thus has high complexity, especially when the channel is highly frequency selective. Instead, we would like to focus on two suboptimal algorithms, namely CP-TX and OP-TX, which are based on ACK/NAK feedbacks from selected mobiles. In practical situations, OP-TX can achieve more than 67 % of the goodput of the optimal algorithm.

In this paper, the downlink rate quantization and cross-layer scheduling design are investigated in multiuser multiple-input single-output (MISO) systems with imperfect channel state information at transmitter (CSIT). We shall propose a systematic analytical design framework based on information theoretical approach. To capture the effect of the potential packet outage, we introduce the average system goodput, which measures the average b/s/Hz delivered to the mobiles successfully, as the system performance objective. Numerical results demonstrate that, by considering the statistics of CSIT errors into the design, the proposed scheduling scheme provides significant performance enhancement.

Obtaining accurate global channel state information (CSI) at multiple transmitter devices is critical to the performance of many coordinated transmission schemes. Practical CSI local feedback often leads to noisy and partial CSI estimates at each transmitter. With rate-limited bi-directional backhaul, transmitters have the opportunity to exchange few CSI-related bits to establish global channel state information at transmitter (CSIT). This paper investigates possible strategies toward this goal. We propose a novel decentralized algorithm that produces minimum mean square error-optimal global channel estimates at each device from combining local feedback and information exchanged through backhauls. The method adapts to arbitrary initial information topologies and feedback noise statistics and can do that with a combination of closed-form and convex approaches. Simulations for coordinated multi-point transmission systems with two or three transmitters exhibit the advantage of the proposed algorithm over conventional CSI exchange mechanisms when the coordination backhauls are limited.

In this letter, we explore interference alignment for the $K$ -user single input single output interference channel with more efficient precoder sizes and lower sensitivity to channel state information at transmitters (CSIT). The main idea in this letter is to divide transmission time into some distinct blocks and select a subset of transmitters and receivers for signaling in each block. We show that our method can achieve more sum degrees-of-freedom compared with other schemes in the limited number of channel extensions. Furthermore, our method needs no full CSIT to be applicable which can be considered as another advantage of this letter.

The Compute-and-Forward protocol in quasi-static channels normally employs lattice codes based on the rational integers $\mathbb{Z}$, Gaussian integers $\mathbb{Z}\left[i\right]$ or Eisenstein integers $\mathbb{Z}\left[\omega\right]$, while its extension to more general channels often assumes channel state information at transmitters (CSIT). In this paper, we propose a novel scheme for Compute-and-Forward in block-fading channels without CSIT, which is referred to as Ring Compute-and-Forward because the fading coefficients are quantized to the canonical embedding of a ring of algebraic integers. Thanks to the multiplicative closure of the algebraic lattices employed, a relay is able to decode an algebraic-integer linear combination of lattice codewords. We analyze its achievable computation rates and show it outperforms conventional Compute-and-Forward based on $\mathbb{Z}$-lattices. By investigating the effect of Diophantine approximation by algebraic conjugates, we prove that the degrees-of-freedom (DoF) of the optimized computation rate is ${n}/{L}$, where $n$ is the number of blocks and $L$ is the number of users.

Multi-user multiple-input and multiple-output (MU-MIMO) wireless systems have the potential to increase system capacity significantly by separating multiple users in the space domain through appropriate signal processing. These techniques require accurate channel state information at transmitter (CSIT) for their proper operations. With inevitable channel imperfections in practice, robustness has become an important issue in the development of beamforming techniques. In this work, we propose a robust leakage-based transmit beamforming design for multi-user MIMO systems by introducing a probabilistic constraint. In a multi-user system, the main challenge for transmit beamforming is to suppress the co-channel interference (CCI) from other users. Our approach optimizes the average signal-to-interference-plus-noise ratio (SINR) performance implicitly by maximizing the average signal power subject to probabilistic leakage and noise power constraint. Moreover, both the single-stream-per-user and multiple-stream-per-user cases are considered.In the latter case, a hybrid scheme is suggested by incorporating Alamouti code into the proposed design. Simulation results show that under proper control of the probabilistic constraint, both beamformers achieve good bit-error-rate (BER) performances, reliability of SINR levels as well as robustness against channel uncertainties.

We investigate remote estimation over a Gilbert-Elliot channel with feedback. The channel is modelled as an ON/OFF channel, where the state of the channel evolves as a Markov chain. The channel state is observed by the receiver and fed back to the transmitter with one unit delay. In addition, the transmitter gets ACK/NACK feedback for successful/unsuccessful transmission. Using ideas from team theory, we establish the structure of optimal transmission and estimation strategies and identify a dynamic program to determine optimal strategies with that structure. We then consider first-order autoregressive sources where the noise process has unimodal and symmetric distribution. Using ideas from majorization theory, we show that the optimal transmission strategy has a threshold structure and the optimal estimation strategy is Kalman-filter like.

In recent results, a theoretical framework has been developed that shows that wavefront predistortion with transmitter channel state information can effectively mitigate turbulence induced fading for free space communication systems. The theoretical framework, however, relies on the assumption of perfect channel state information available at the transmitter, which is not physically realizable since it would require an infinite rate feedback link. This paper extends the theoretical framework to physically realizable systems with finite rate feedback. Specifically, we provide the performance and optimal feedback strategy given a finite rate feedback link.

Rate-splitting multiple access (RSMA) is acknowledged as a promising solution for improving the capacity of dense downlink networks designed to meet the severe criteria of networks beyond 5G, in which a large number of users may be simultaneously supplied by a single bandwidth spectrum. Numerous studies have focused on establishing acceptable RSMA solutions for energy optimization measures like energy efficiency (EE) and weighted power consumption of all users under the acceptance of perfect or imperfect channel state information at transmitter (CSIT). This evaluation focuses on the technical features of newly published papers and their relevance in a variety of situations. We also cover the difficulties and unresolved concerns of RSMA applications in future heterogeneous downlink networks.