An Information Theoretic Charachterization of Channel Shortening Receivers

Optimal data detection of data transmitted over a linear channel can always be implemented through the Viterbi algorithm (VA). However, in many cases of interest the memory of the channel prohibits application of the VA. A popular and conceptually simple method in this case, studied since the early 70s, is to first filter the received signal in order to shorten the memory of the channel, and then to apply a VA that operates with the shorter memory. We shall refer to this as a channel shortening (CS) receiver. Although studied for almost four decades, an information theoretic understanding of what such a simple receiver solution is actually doing is not available. In this paper we will show that an optimized CS receiver is implementing the chain rule of mutual information, but only up to the shortened memory that the receiver is operating with. Further, we will show that the tools for analyzing the ensuing achievable rates from an optimized CS receiver are precisely the same as those used for analyzing the achievable rates of a minimum mean square error (MMSE) receiver

Beyond Massive-MIMO: The Potential of Positioning with Large Intelligent Surfaces

We consider the potential for positioning with a system where antenna arrays are deployed as a large intelligent surface (LIS), which is a newly proposed concept beyond massive-MIMO where future man-made structures are electronically active with integrated electronics and wireless communication making the entire environment \lq\lq{}intelligent\rq\rq{}. In a first step, we derive Fisher-information and Cram\'{e}r-Rao lower bounds (CRLBs) in closed-form for positioning a terminal located perpendicular to the center of the LIS, whose location we refer to as being on the central perpendicular line (CPL) of the LIS. For a terminal that is not on the CPL, closed-form expressions of the Fisher-information and CRLB seem out of reach, and we alternatively find approximations of them which are shown to be accurate. Under mild conditions, we show that the CRLB for all three Cartesian dimensions ($x$, $y$ and $z$) decreases quadratically in the surface-area of the LIS, except for a terminal exactly on the CPL where the CRLB for the $z$-dimension (distance from the LIS) decreases linearly in the same. In a second step, we analyze the CRLB for positioning when there is an unknown phase $\varphi$ presented in the analog circuits of the LIS. We then show that the CRLBs are dramatically increased for all three dimensions but decrease in the third-order of the surface-area. Moreover, with an infinitely large LIS the CRLB for the $z$-dimension with an unknown $\varphi$ is 6 dB higher than the case without phase uncertainty, and the CRLB for estimating $\varphi$ converges to a constant that is independent of the wavelength $\lambda$. At last, we extensively discuss the impact of centralized and distributed deployments of LIS, and show that a distributed deployment of LIS can enlarge the coverage for terminal-positioning and improve the overall positioning performance.Comment: Submitted to IEEE Trans. on Signal Processing on Apr. 2017; 30 pages; 13 figure

Beyond Massive-MIMO: The Potential of Data-Transmission with Large Intelligent Surfaces

In this paper, we consider the potential of data-transmission in a system with a massive number of radiating and sensing elements, thought of as a contiguous surface of electromagnetically active material. We refer to this as a large intelligent surface (LIS). The "LIS" is a newly proposed concept, which conceptually goes beyond contemporary massive MIMO technology, that arises from our vision of a future where man-made structures are electronically active with integrated electronics and wireless communication making the entire environment "intelligent". We consider capacities of single-antenna autonomous terminals communicating to the LIS where the entire surface is used as a receiving antenna array. Under the condition that the surface-area is sufficiently large, the received signal after a matched-filtering (MF) operation can be closely approximated by a sinc-function-like intersymbol interference (ISI) channel. We analyze the capacity per square meter (m^2) deployed surface, \hat{C}, that is achievable for a fixed transmit power per volume-unit, \hat{P}. Moreover, we also show that the number of independent signal dimensions per m deployed surface is 2/\lambda for one-dimensional terminal-deployment, and \pi/\lambda^2 per m^2 for two and three dimensional terminal-deployments. Lastly, we consider implementations of the LIS in the form of a grid of conventional antenna elements and show that, the sampling lattice that minimizes the surface-area of the LIS and simultaneously obtains one signal space dimension for every spent antenna is the hexagonal lattice. We extensively discuss the design of the state-of-the-art low-complexity channel shortening (CS) demodulator for data-transmission with the LIS.Comment: Submitted to IEEE Trans. on Signal Process., 30 pages, 12 figure

Massive MIMO performance evaluation based on measured propagation data

Massive MIMO, also known as very-large MIMO or large-scale antenna systems, is a new technique that potentially can offer large network capacities in multi-user scenarios. With a massive MIMO system, we consider the case where a base station equipped with a large number of antenna elements simultaneously serves multiple single-antenna users in the same time-frequency resource. So far, investigations are mostly based on theoretical channels with independent and identically distributed (i.i.d.) complex Gaussian coefficients, i.e., i.i.d. Rayleigh channels. Here, we investigate how massive MIMO performs in channels measured in real propagation environments. Channel measurements were performed at 2.6 GHz using a virtual uniform linear array (ULA) which has a physically large aperture, and a practical uniform cylindrical array (UCA) which is more compact in size, both having 128 antenna ports. Based on measurement data, we illustrate channel behavior of massive MIMO in three representative propagation conditions, and evaluate the corresponding performance. The investigation shows that the measured channels, for both array types, allow us to achieve performance close to that in i.i.d. Rayleigh channels. It is concluded that in real propagation environments we have characteristics that can allow for efficient use of massive MIMO, i.e., the theoretical advantages of this new technology can also be harvested in real channels.Comment: IEEE Transactions on Wireless Communications, 201

An Information Theoretic Charachterization of Channel Shortening Receivers

Optimal data detection of a linear channel can always be implemented through the Viterbi algorithm (VA). However, in many cases of interest the memory of the channel prohibits application of the VA. A popular and conceptually simple method in this case, studied since the early 70s, is to first filter the received signal in order to shorten the memory of the channel, and then to apply a VA that operates with the shorter memory. We shall refer to this as a channel shortening (CS) receiver. Although studied for almost four decades, an information theoretic understanding of what such simple receiver solution is actually doing is not available. In this paper we will show that an optimized CS receiver is implementing the chain rule of mutual information, but only up to the shortened memory that the receiver is operating with. Further, we will show that the tools for analyzing the ensuing achievable rates from an optimized CS receiver are precisely the same as the tools that are used for analyzing the achievable rates of an minimum mean square error (MMSE) receiver

Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation

To enable realistic studies of massive multiple-input multiple-output systems, the COST 2100 channel model is extended based on measurements. First, the concept of a base station-side visibility region (BS-VR) is proposed to model the appearance and disappearance of clusters when using a physically-large array. We find that BS-VR lifetimes are exponentially distributed, and that the number of BS-VRs is Poisson distributed with intensity proportional to the sum of the array length and the mean lifetime. Simulations suggest that under certain conditions longer lifetimes can help decorrelating closely-located users. Second, the concept of a multipath component visibility region (MPC-VR) is proposed to model birth-death processes of individual MPCs at the mobile station side. We find that both MPC lifetimes and MPC-VR radii are lognormally distributed. Simulations suggest that unless MPC-VRs are applied the channel condition number is overestimated. Key statistical properties of the proposed extensions, e.g., autocorrelation functions, maximum likelihood estimators, and Cramer-Rao bounds, are derived and analyzed.Comment: Submitted to IEEE Transactions of Wireless Communication

User Assignment with Distributed Large Intelligent Surface (LIS) Systems

In this paper, we consider a wireless communication system where a large intelligent surface (LIS) is deployed comprising a number of small and distributed LIS-Units. Each LIS-Unit has a separate signal process unit (SPU) and is connected to a central process unit (CPU) that coordinates the behaviors of all the LIS-Units. With such a LIS system, we consider the user assignments both for sum-rate and minimal user-rate maximizations. That is, assuming $M$ LIS-Units deployed in the LIS system, the objective is to select $K$ ($K\!\leq\!M$) best LIS-Units to serve $K$ autonomous users simultaneously. Based on the nice property of effective inter-user interference suppression of the LIS-Units, the optimal user assignments can be effectively found through classical linear assignment problems (LAPs) defined on a bipartite graph. To be specific, the optimal user assignment for sum-rate and user-rate maximizations can be solved by linear sum assignment problem (LSAP) and linear bottleneck assignment problem (LBAP), respectively. The elements of the cost matrix are constructed based on the received signal strength (RSS) measured at each of the $M$ LIS-Units for all the $K$ users. Numerical results show that, the proposed user assignments are close to optimal user assignments both under line-of-sight (LoS) and scattering environments.Comment: submitted to IEEE conference; 6 pages;10 figure

A comparison of DFT and SVD based channel estimation in MIMO OFDM systems

In this paper two simplified transform based estimators for MIMO OFDM systems using the DFT and an SVD based transform are compared over a tapped delay line channel model. In the resulting symbol error rate plots, it is seen that the DFT based estimator experiences an error floor caused by the mismatch between the discrete time model and a continuous time reality. This error floor becomes a problem at high SNR levels where high data-rate systems can be expected to operate. When using an SVD based estimator it is seen that this error floor is reduced at the cost of a somewhat increased estimator complexit

Comparing Analog Front-Ends for Duty-Cycled Wake-Up Receivers in Wireless Sensor Networks

Using ultralow-power wake-up receivers (WRxs) can reduce idle listening energy cost in wireless sensor networks with low traffic intensity. This has led to many WRx analog front-end (AFE) designs presented in literature, with a large variety of trade-offs between the sensitivity, the data rate, and the power consumption. Energy consumed during wake-up in a network depends on many parameters and without a unified energy analysis, we cannot compare performance of different AFEs. We present an analysis of duty-cycled WRx schemes which provides a simple tool for such a comparison based on the energy consumed in an entire single-hop network during a wake-up. The simplicity is largely due to the fact that all network and communication parameter settings can be condensed into a single scenario constant. This tool allows us to both compare AFEs for specific scenarios and draw more general conclusions about AFE performance across all scenarios