Reconfigurable Antenna Based Blind Interference Alignment over Heterogenous Block Fading Channels

In recent years, several experimental studies have come out to validate the theoretical findings of interference alignment (IA), but only a handful of studies have focused on blind interference alignment. Unlike IA and other interference mitigation techniques, blind IA does not require channel state information at the transmitter (CSIT). The key insight is that the transmitter uses the knowledge of channel coherence intervals and receivers utilize reconfigurable antennas to create channel fluctuations exploited by the transmitter. In this work, we present a novel experimental evaluation of a reconfigurable antenna system for achieving blind IA. We present a blind IA technique based on reconfigurable antennas for a 2-user multipleinput single-output (MISO) broadcast channel implemented on a software defined radio platform where each of the receivers is equipped with a reconfigurable antenna. We further compare this blind IA implementation with traditional TDMA scheme for benchmarking purposes. We show that the achievable rates for blind IA can be realized in practice using measured channels under practical channel conditions. Additionally, the average error vector magnitude and bit error rate (BER) performances are evaluated.

Blind interference alignment (BIA) can eliminate users’ interference without channel state information and greatly improve the channel capacity, which has been regarded as a promising technique in next generation wireless systems. However, current BIA mechanisms neglect noise accumulations, resulting in final signal-to-noise ratio (fSNR) deterioration and reduced transmission rates. Motivated by ameliorating such negative impact induced by noise accumulations, this study establishes an SNR aware semi-BIA (SNR SBIA) framework in the multi-input–single-output broadcast channel, where the users form different groups performing BIA for different SNR reductions. An SNR SBIA algorithm is further proposed based on tabu search for maximising the overall performance ensuring all users’ fSNRs higher than an SNR threshold. Extensive evaluations demonstrate that SNR SBIA can adapt to the users’ diverse received SNRs and the corresponding achievable sum rate is about 1.38 times and 1.92 times that in standard BIA and grouped hierarchical BIA, respectively.

The paper presents a new solution for interference management in downlink (DL) heterogenous networks where macrocell base station (MBS) and neighboring femtocell base stations cause interference on femtocell users. A novel scheme is proposed where the i-th macrocell user (MU-i, i = 1, ..., F) and the i-th femtocell (FC-i, i = 1, ..., F) form a pair ([MU-i FC-i] pair), and pairs are orthogonal ([MU-i FC-i] orthogonal to [MU-j FC-j], where i is not equal to j). Without loss of generality, it is assumed that i th macrocell user and femtocell are chosen. In each femtocell, blind interference alignment (BIA) using staggered antenna switching is utilized and the paired macrocell user's streams are aligned on the predetermined interference dimensions of the femtocell users set by BIA. For the baseline, it is assumed all femtocells, where BIA is applied in each, share their reserved resources thus causing significant interference on each other, and the macrocell users are orthogonal to all femtocells. It is shown that the degrees of freedom of the proposed and the baseline schemes in the case of 2 femtocells each with 2-user 2 × 1 multiple-input single-output (MISO) broadcast channels (BCs) is 7/3 and 1, respectively. Numerical results also show that the sum-rate of the proposed scheme is higher compared with the baseline where MBS applies zero-forcing precoder with water filling power allocation. The novel proposed scheme can be extended to a general network via judicious selection and orthogonalization approaches.

The explosive demand for high data rates and the need ubiquitous wireless connectivity has led to the phenomenon of network densification, the deployment of large number of base station within a geographic area. Since the radio spectrum is limited, wireless transmissions need to share a common resource which results in interference. Interference in turn creates a bottleneck on the communication rate. Recently three breakthroughs have been made to increase the capacity of wireless networks while mitigating interference : multiple input multiple output (MIMO) beamforming, interference alignment (IA) and pattern reconfigurable antennas (PRA). While a great deal of progress has been made on understanding each individually, relatively little is known about how to use these techniques in combination to increase system performance. In this dissertation, we analyze and experimentally evaluate how these new technologies can be leveraged to enhance the rate performance of communication networks. Specifically, we address three problems: i) enhancing multi-user MIMO performance with PRA, ii) improving IA performance with PRA-based antenna selection, and iii) enabling practical blind IA with PRA. To understand the impact PRAs on MU-MIMO and IA, it is necessary to evaluate their performance through measurements. Simulation-based studies often reiterate over set of simplistic channel models and unrealistic assumptions. This dissertation focuses on a measurement-based evaluation approach. For each of these problems, a hardware testbed implementation and measurement methodology is developed for evaluating the performance of the aforementioned technologies through efficient and repeatable experiments. The first two major contributions of this dissertation focus on multi-user MIMO (MU-MIMO) and IA. While the theoretical rate gains of MU-MIMO and IA are substantial, the performance gains in practical systems and measured channels have been limited. One of the key limiting factors are spatially correlated user channels. In this work, we propose MU-MIMO and IA transmission schemes that leverage the pattern diversity provided by PRAs to mitigate the effects of spatial correlation in wireless channels. PRAs are capable of dynamically adjusting their radiation pattern, providing an additional degree of freedom that can be exploited to improve MU-MIMO and IA performance by treating the array configuration and radiation characteristics as additional components in the joint optimization of adaptive system parameters. We quantify the benefits of pattern diversity on the rate performance of MU-MIMO and IA systems through extensive measurements. Furthermore, we develop efficient antenna mode selection algorithms to realize those benefits without increasing the system complexity or overhead, making these techniques suitable for practical implementation. The third contribution of this dissertation focuses on a transmission technique known as blind IA. In contrast to MU-MIMO and conventional IA, blind IA is signaling scheme that suppresses interference in multi-user systems, without the knowledge of channel state information at the transmitter (CSIT). The key to performing IA without CSIT is the use of PRAs that are capable of dynamically switching among a fixed number of radiation patterns to introduce artificial fluctuations in the channel. In this dissertation, we develop a novel implementation of a blind IA system on a software defined radio platform where each of the receivers is equipped with a PRA. Our work provides the first experimental evaluation of PRA-based blind IA schemes and demonstrates significant gains in rate and reliability over traditional orthogonal transmission schemes such as TDMA.

In order to explore the compatibility of blind interference alignment schemes with channel knowledge based beamforming and zero-forcing schemes, in this work we initiate the study of the degrees of freedom (DoF) of the two-user MIMO interference channel (IC) where Transmitter 1 is equipped with reconfigurable antennas and has no channel knowledge while Transmitter 2 has partial channel knowledge but no reconfigurable antennas. In particular we focus on two challenging examples to show how blind interference alignment, rate-splitting and partial zero-forcing schemes may be combined in non-trivial ways. Limited generalizations of these examples to broader parameter regimes are also presented.

We derive the degrees of freedom (DoF) for K-user single-input single-output interference channels with a reconfigurable antenna at receivers, assuming linear coding strategies without channel state information at transmitters. Our DoF converse builds upon the inherent feature that channel state's changing patterns of the links towards the same receiver are always identical. We prove the linear sum DoF is upper-bounded by n* K/K+n*(n*-1), n* where n* is the optimal number of preset modes among N. Moreover, we propose a linear scheme that achieves the upper-bound if K/n* is an integer. For the other cases, we give a guideline for the achievable scheme.

We consider the K-user MISO interference channel where each transmitter has multiple antennas and each receiver has a reconfigurable antenna capable of switching among several pre-set modes. The channels in different modes are assumed to be independent. We propose an interference alignment scheme without channel information at transmitters. We show that the achievable degree of freedom of the proposed scheme outperforms that in the traditional K-user MISO interference channel without the reconfigurable antenna.

In this paper, we look at the simplest instance of heterogeneous broadcast channel (BC) where a multi-antenna transmitter base station (BS) is trying to communicate data to two user equipments (UEs), having the perfect CSIT about UE-1 and no CSIT about UE-2. We focus on UE-2 which is severely limited by the interference of UE-1. We consider the question whether additional spatial diversity or advanced receiver design at UE-2 is feasible for mitigating this interference. We investigate both the options and show that the rate of UE-2 gets significantly improved in both cases however hardware and RF design constraints may make the advanced receiver design solution preferable over spatial diversity solution.

We consider two-user MIMO broadcast and interference channels in which confidential messages intended for each receiver are kept secret from the other receiver. The confidential secrecy rates are nonconvex functions of transmit covariance matrices, which makes it intractable to find optimal transmit covariance matrices analytically. In the MIMO broadcast channels, we prove the weighted secrecy sum rate maximization has zero duality gap and KKT conditions are necessary conditions for the optimal solution. We apply the block successive lower-bound maximization technique to nonconvex weighted secrecy sum rate maximization problems. We also derive numerical algorithms for MIMO interference channels and Gaussian wiretap channels with a cooperative jammer. Every limit point achieved by the proposed algorithms is a local optimal solution that satisfies the KKT conditions. Numerical results show that the proposed algorithms outperform existing suboptimal algorithms in terms of secrecy rates.

Consider M independent users, each user having his own transmit antenna, that transmit simultaneously to a receiver equipped with N antennas through a Rayleigh block-fading channel having a coherence interval of T symbols, with no channel state information (CSI) available to either the transmitters or to the receiver. The total transmitted power is independent of the number of users. For a given coherence time T, we wish to identify the best multiaccess strategy that maximizes the total throughput. If perfect CSI were available to the receiver, it is known that the total capacity would increase monotonically with the number of users. If the CSI is available to both the receiver and to all transmitters, the throughput maximizing strategy implies for N=1 that only the single user who enjoys the best channel condition transmits. In the absence of CSI one is forced to a radically different conclusion. In particular, we show that if the propagation coefficients take on new independent values for every symbol (e.g., T=1) then the total capacity for any M > 1 users is equal to the capacity for M=1 user, in which case time division multiple access (TDMA) is an optimal scheme for handling multiple users. This result follows directly from a recent treatment of the single-user multiple antenna block-fading channel. Again, motivated by the single-user results, one is lead to the following conjecture for the multiple-user case: for any T > 1, the maximum total capacity can be achieved by no more than M = T users. The conjecture is supported by establishing the asymptotic result that, for a fixed N and a constant M/T for large T, the total capacity is maximized when M/T/spl rarr/0, which yields a total capacity per symbol of N log(1 + /spl rho/), where /spl rho/ is the expected signal-to-noise ratio (SNR) at the receiver. We further support the conjecture by examining the asymptotic behavior with large to for fixed M, T, and N /spl les/ T.

Analog transmission of correlated information over Gaussian broadcast channels (BCs) using analog joint source–channel coding (JSCC) is addressed. This communication strategy has attractive advantages, such as low complexity, minimal delay, graceful degradation, and adaptation to time-varying environments. In this paper, we focus on the optimization of parametric continuous mappings that satisfy individual quality of service requirements over Gaussian BCs. This optimization is based on the balancing of the user distortions to ensure the feasibility of the resulting optimization problems. An analysis of the overall distortion corresponding to the considered mappings is carried out to design algorithms that determine the optimal values for the mappings parameters. Results show that the proposed analog JSCC scheme provides near optimal performance and an adequate balancing of the individual distortions.

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This paper reports on polarimetric radiation properties based on the switching modes of normal PSR B2020+28 by analysing the data acquired from the Nanshan 25-m radio telescope at 1556 MHz. With nearly 8 hours quasi-continuous observation, the data presented some striking and updated phenomena. The change of relative intensity between the leading and trailing components is the predominant feature of mode switching. The intensity ratio between the leading and trailing components are measured for the individual profiles averaged over 30 seconds. It is found that there is an excess of high ratios over the normal distribution, which indicates that two modes exist in the pulsar. The distribution of abnormal mode has a narrower width indicating that the abnormal mode is more stable than the normal mode. A total of 76 mode switching events are detected in our data. It spends 89\% in the normal mode and 11\% in the abnormal mode. The intrinsic distributions of mode timescales are constrained with power-law distributions. The significant difference in the index of the duration distribution between normal and abnormal modes possibly indicates that the timescale for the abnormal mode to get stable is shorter than that for the normal mode. The frequent switching between both modes may indicate that the oscillations between different magnetospheric states are rapid.

Dynamic Spectrum Sharing (DSS) enables spectrum sharing between Long-Term Evolution (LTE) and New Radio (NR) systems, addressing spectrum scarcity in NR. To avoid interference when supporting NR traffic within LTE spectrum, key factors must be compatible. Effective DSS techniques are essential for coexistence. This paper discusses these issues in two parts. Part I covers LTE and NR coexistence using DSS, introducing resource grids, control signals, and channels, and explores DSS approaches for NR data traffic, including NR Synchronization Signal/Physical Broadcast Channels (SSB) transmission via LTE Multicast-Broadcast Single-Frequency Network (MBSFN) and non-MBSFN subframes with associated challenges and standardization efforts for DSS improvement. Part II presents a DSS technique using MBSFN subframes in a heterogeneous network with a macrocell and picocells running on LTE, and in-building small cells running on NR, sharing LTE spectrum via DSS. An optimization problem is formulated to manage traffic through MBSFN allocation, determining the optimal number of MBSFN subframes per LTE frame. System simulations indicate DSS improves Spectral and Energy Efficiency in small cells. The paper concludes with key lessons for LTE and NR coexistence.

In this paper, the problem of joint mode switching and power adaptation is studied for simultaneous wireless information and power transfer (SWIPT) over a fading channel. The receiver dynamically switches between information decoding (ID) and energy harvesting (EH) modes while the transmitter dynamically adapts the transmit power. Considering the nonlinearity of practical EH circuits, a realistic nonlinear EH model is adopted rather than the idealistic linear EH model. To characterize the ultimate performance tradeoff between ID and EH, an optimization problem is formulated to maximize the average harvested energy under the constraints on the average achievable rate and the average transmit power, which is a nonconvex and combinatorial problem. To solve this problem, first, the optimal power adaptation scheme for the nonlinear EH receiver that operates only in the EH mode is proposed. Using this scheme, the jointly optimal solution for the mode switching and power adaptation is then derived. By comparing the obtained results to the existing results, various useful and interesting insights into the optimized SWIPT system with nonlinear EH are presented. An important insight into the impact of nonlinear EH is that, to exploit the high energy conversion efficiency of the nonlinear circuit, the EH mode has to be selected only in the moderate range of channel gains. Also, in the EH mode, the power has to be adapted to the short-term power threshold only for the moderate channel gains.