The large number of antennas at the base stations (BSs), the reference signal transmission over a wide bandwidth, and dense network deployment can be used to achieve unprecedented position accuracy in 5G and beyond networks. This work proposes a position estimation method using a full dimension massive multiple-input multiple-output (MaMIMO) system in cellular networks. The user equipment (UE) estimates the time of flight/arrival (ToA) from multiple BSs using estimation of signal parameters via rotational invariant technique (ESPRIT). A novel method that selects a subset of the accurate ToA measurements and uses it to estimate the position of the target UE based on multilateration is proposed. The simulation results demonstrate that there is a significant improvement in positioning accuracy over the conventional methods, and the proposed method closely matches the genie-aided algorithm for small subsets, and outperforms it for large subsets. The proposed method achieves 20 cm positioning accuracy for 90% of the UEs in indoor factory (InF) scenarios using practical 3GPP channel models. It also satisfies the ITU requirement for Industry 4.0 and requires a low transmission and measurement overhead.

Transceiver designs for multiple-input multiple-output (MIMO) two-way relaying are being actively explored. Most of the state-of-the-art studies optimize a system-wide objective function subject to the transmit power constraints on the two source nodes and the relay. Transceiver designs with quality-of-service (QoS) constraints have lacked attention in two-way relaying literature. In this paper, we study a MIMO transceiver design, based on the generalized singular value decomposition, that allocates power at the source and relay nodes to optimize the following per-stream rate-constrained objectives: 1) network transmit power, and 2) sum-rate. In addition, we also maximize the rate of the transmit stream with the worst signal-to-noise ratio. Through extensive numerical evaluations, we demonstrate the superior performance of proposed design over the existing ones, not only with QoS constraints but also without them.

We investigate a joint design of linear precoders and receivers for multiple-input multiple-output non-simultaneous two-way relaying (NS-TWR). Unlike conventional two-way relaying, the base station in NS-TWR performs two-way relaying with two different users-a transmit-only user and a receive-only user (RUE). The RUE experiences back-propagating interference (BI). The proposed design cancels this BI and provides beamforming gain over existing designs. For NS-TWR, we maximize the weighted sum-rate (WSR) through joint power allocation, by solving a sequence of geometric programs. The precoder and the receiver designs as well as the power allocation program are then extended for a multi-user system with multiple transmit-only and receive-only users. With exhaustive simulations, we show that the proposed design provides significantly better WSR than the existing ones. The proposed design is also evaluated in a cellular framework using realistic path loss models, to assess the system-level performance gain achievable.

In conventional two-way relaying (TWR), it is assumed that a user has data to send and receive simultaneously from the base station (BS) via a relay. In cellular systems, data flow between the BS and a user is usually not simultaneous, e.g., a transmit-only user (say, TUE) may have uplink data to send in the multiple access (MAC) phase, but may not have downlink data to receive in the broadcast (BC) phase. Such one-way data flow will reduce TWR to spectrally inefficient one-way relaying. The multiple-input-multiple-output (MIMO) asymmetric TWR (ATWR) protocol considered here restores the two-way data flow via a relay. In ATWR, the BC phase following the MAC phase of a TUE is used to send downlink data to a receive-only user (say, RUE). However, the RUE will not be able to cancel the back-propagating interference. We design a structured precoder at the relay to cancel this interference. The proposed precoder also triangularizes the end-to-end MIMO channels. The channel triangularization reduces the weighted sum-rate maximization and relay power minimization problems to power allocation problems, which are then cast as geometric programs. Simulation results illustrate the effectiveness of the proposed precoder when compared with conventional solutions.

Two-way relaying reduces the loss in spectral efficiency caused in a conventional half-duplex relay due to two channel uses per data unit transmitted to the destination. Two-way relaying is possible when two nodes exchange data simultaneously through a relay. In the case of cellular systems, data exchange between base station (BS) and users (UE) is usually not symmetric, e.g., a user (UE1) might have uplink data to transmit during multiple access (MAC) phase, but might not have downlink data to receive during broadcast (BC) phase. This asymmetry in data exchange will reduce the gains of two-way relaying. In the case of infrastructure relays, where there are multiple users communicating through a relay, we propose that the BC phase following the MAC phase of UE1be used by the relay to transmit downlink data to a second user (UE2). Conventional two-way relaying with symmetric MAC and BC phases must now be modified to asymmetric MAC (BS → RS ← UE1) and BC phases (BS ← RS → UE2), respectively. This will result in UE2not being able to cancel the back-propagating interference in the usual way. We design precoders using conventional zero-forcing and linear minimum-mean-square-error criteria to mitigate the back-propagating interference at UE2for an amplify-and-forward (AF) relay. We also propose a novel precoder appropriate for the asymmetric two-way relaying. The sum-rate performance of the proposed precoder is shown to be better than the conventional precoders.

In this paper, we propose two-hop user-deployable indoor relays for CDMA systems with signal bandwidth 5 MHz or less. We assume concurrent relaying wherein macro base stations (BS) are allowed to transmit when a relay is forwarding. The two-hop indoor relay is studied using a generalized model for outdoor-to-indoor communication in a frequency-selective channel in the presence of co-channel interference. We propose an equalize-and-forward relay that employs multiple-antenna interference-aware equalization before forwarding. We present a unified solution to minimize interference (due to concurrent transmissions) at the relay-served destination and the BS-served destination, using power control and exploiting spatial reuse. A systematic method to enable indoor relays with the proposed interference management solutions is presented that is applicable to existing CDMA systems, without additional requirements in Access Terminal (AT)/User Equipment. Simulation results in the context of High Rate Packet Data (HRPD) CDMA network shows that the ATs served through the indoor relays experience throughput improvement by at least a factor of two, whereas the ATs served by the BS experienced a gain of around 6% in spite of concurrent relaying. The results also show an overall system throughput gain upto 30% when compared to the existing network with only single hops.

In this work, we propose a cognitive interference management scheme for heterogeneous cellular wireless networks (LTE-A and WiMAX) with macrocells and femtocells (that operate in a closed-access mode). The scheme presented allocates resources (in time and frequency) and transmission opportunities to the macro/femtocells in the network by considering their potential to cause interference at each others' associated user equipments (UEs). We study the efficacy of the proposed scheme using a LTE-A system level simulator and compare with frequency reuse techniques and no interference management scenarios. We observe that our scheme significantly enhances average cell-edge UE throughput (5\%-tile throughput) with some degradation in overall sum throughput. Also we observe that the scheme decreases the probability of cell-edge users in the system experiencing degraded SINR.

We consider the problem of cooperative precoding for controlling interference in the downlink of a multiple-input and multiple-output (MIMO) interference channel. A model for the multicell, multiuser, MIMO system is analyzed, and a criterion to simultaneously maximize the SINRs of users sharing a common spectral resource is provided. An asymptotically optimal solution is then proposed as the number of users per sector (U) and the number of resources (B) in the system become large, within a specific framework for scheduling co-channel users in interfering cells. Based on this, a heuristic algorithm for distributed cooperative precoder selection (CPS) is proposed for application in practical systems with finite B and U values. System performance gains measured in terms of mean cell throughput and cell-edge spectral efficiency values are estimated using numerical simulations. The proposed technique takes into account practical constraints such as limiting the information exchanged from the user equipments to the serving base stations, and amongst the cooperating base stations, to a modest level.

Today, it is well understood that interference poses the main capacity limitation and thus challenge for future cellular networks. A promising concept that addresses interference is multi-cell cooperative signal processing, often referred to as Network MIMO. While in recent publications, it is often assumed that the required exchange of information among the base stations can be done with unlimited capacity, current network infrastructures do not necessarily support very high data rates and backhaul has been identified as a major cost driver. For the case of unlimited backhaul availability, it has been shown that large gains can be achieved through intelligent resource assignment (scheduling). In this paper, we introduce a low-complexity algorithm for uplink scheduling in cooperative cellular networks under the assumption of a capacity constrained backhaul with the target of maximizing the tradeoff between backhaul and sum rate.

In the emerging broadband wireless networks such as IEEE 802.16m and LTE-A networks which employ universal frequency reuse-1, the cell coverage is predominantly limited by the co-channel interference. Bit level data repetition, and conventional multi-antenna maximal-ratio-combining (MRC) techniques are typically used to improve the signal-to-interference-plus- noise ratio (SINR) at the receiver. Simple data repetition does not guarantee efficient interference suppression and it reduces spectrum efficiency. In this paper, we propose a symbol level data repetition technique called conjugate data repetition (CDR), which transmits the modulation alphabet of the desired signal and its complex-conjugate in distinct sub carriers. The CDR operation is performed across all base stations in a synchronous manner. We show that minimum mean-square error (MMSE) filtering of the complex-valued signal and its conjugated copy, provides a high interference cancellation (IC) gain. For repetition factor greater than 2, we propose a combination of conjugate repetition and random phase rotation of the repeated symbols. Simulation results show that CDR with a repetition factor 2 or 3 can provide a significant advantage in coverage/reliability for cell edge users.

In this paper, we consider the use of variable bitrate (VBR) speech coding to reduce co-channel interference and thus increase the capacity of cellular systems. We propose the so-called VBR-FEC scheme in which a variable-rate forward error-correcting code (FEC) is used in conjunction with a VBR speech coder. We then present an analysis of the enhancement in capacity that can be expected in the case of a CDMA system employing the proposed VBR-FEC scheme. Next, we present a design example using a specific VBR coder and a family of BCH codes for the FEC. Finally, we present a real-time statistical simulation platform that can be used to evaluate the impact on capacity of interference-reduction techniques, by studying their effect on received speech quality using listening tests. We use this platform to simulate the design example and present results of its performance.

Simulation work is reported indicating that packet reservation multiple access (PRMA) allows a variety of information sources to share the same wireless access channel. Some of the sources, such as speech terminals, are classified as periodic and others, such as signaling, are classified as random. Packets from all sources contend for access to channel time slots. When a periodic information terminal succeeds in gaining access, it reserves subsequent time slots for uncontested transmission. Both computer simulations and a listening test reveal that PRMA achieves a promising combination of voice quality and bandwidth efficiency.>

We consider a set of uncoordinated users employing an ALOHA protocol to transmit packets to a central base station in a local radio environment, e.g., in an urban area or within a building. Because of the different distances between the various users and the base station, the signals received from different users have substantially different power levels. This near/far phenomenon gives rise to a capture effect at the receiver such that when several packets are transmitted simultaneously, the receiver has a good chance of accurately detecting the packet arriving with the highest energy. Moreover, capture can be made near perfect in this environment through the use of properly design spread-spectrum signaling technique that enables the receiver to differentiate among the arriving packets based on both power differences and differing arrival times. We investigate variations to the conventional ALOHA protocols that take advantage of perfect capture to reduce the delays and increase the throughputs of all users, including the furthest one. Three protocols are introduced and compared, which we call "persistent ALOHA with capture" (PAC), "gated ALOHA with capture" (GAC), and "gated ALOHA with capture/exhausted" (GAC/E). Two goals are considered in the comparison: an equatable delay profile among the users, and a small expected number of simultaneously transmitted packets. The latter is quite relevant for the practical implementation of a perfect-capture receiver. We conclude that the GAC/E protocol is most desirable from the twin points of view of delay profile and receiver implementation.

Direct-sequence spread spectrum with differential phase shift-keying (DPSK) modulation and code-division multiple-access is a promising approach for wireless communications in an indoor environment, which is characterized in this paper by a Rayleigh-fading multipath channel. In this study, we consider two specific channel models having different path-delay distributions and average path power profiles. A star configuration, in which each user exercises average power control in transmitting to a central station, is the basic communication unit, which could be one cell in a cellular hierarchy. We obtain the performance of a single link between a user and its receiver in the central station, and consider two types of diversity, selection diversity and predetection combining to exploit the multipath. A similar system with coherent PSK (CPSK) modulation has been studied previously for one of the channel models considered here. For the same channel model, we show that the irreducible error probability with selection diversity is about half an order of magnitude higher when DPSK is used instead of CPSK. With predetection combining, the performance improves significantly in comparison with selection diversity as the diversity order increases. DPSK modulation with predetection combining is akin to coherent PSK with optimal maximal-ratio combining, but is simpler to implement. The performance with selection diversity for a second channel model, which is based on measurements in an office building, is not significantly different. This indicates that the spreadspectrum approach is rather robust to the path-delay distribution and average path-power profile.

Vector quantization (VQ) provides many attractive features for image coding with high compression ratios. However, initial studies of image coding with VQ have revealed several difficulties, most notably edge degradation and high computational complexity. We address these two problems and propose a new coding method, classified vector quantization (CVQ), which is based on a composite source model. Blocks with distinct perceptual features, such as edges, are generated from different subsources, i.e., belong to different classes. In CVQ, a classifier determines the class for each block, and the block is then coded with a vector quantizer designed specifically for that class. We obtain better perceptual quality with significantly lower complexity with CVQ when compared to ordinary VQ. We demonstrate with CVQ visual quality which is comparable to that produced by existing coders of similar complexity, for rates in the range 0.6-1.0 bits/pixel.

A fundamental computational task that arises in several areas of signal processing is pattern matching, where a given test pattern is compared with a large set of stored templates, to find the best match that minimizes a given measure of dissimilarity. Three different geometrically-oriented methods are proposed for substantially reducing the computational complexity of the search process by reducing the number of multiplies in exchange for additional low complexity operations and, in two of the methods, additional memory for storing precomputed tables.

Vector quantization (VQ) has made it possible to utilize perceptually meaningful techniques for direct space-domain image coding. A simple 2 or 3 way classified codebook approach [2,3] allocates the perceptually important edges with more resolution than the easily encoded monotone regions of an image. In this paper, we introduce a major extension of the classification approach to include edge orientation and location, thereby exploiting an important feature of the human visual mechanism. In particular, each 4 × 4 block of pixels is classified into one of 31 classes for the case of 16 dimensional VQ. The encoding and codebook design complexity is significantly reduced, allowing us to use large codebooks designed from a large database of training images. We present images encoded at 0.7 and 0.8 bits per pixel using this scheme with 16- dimensional vectors. Only a small fraction of one bit per pixel is needed to code the monotone regions of an image; the rest of the bitrate is used to achieve a high level of edge integrity.

An important application of spatial filtering techniques is in the post-processing-of images degraded by coding. Linear post-processing methods are inadequate to reduce the degradations in block-coded images. In this paper, a new nonlinear, space-variant filtering algorithm is proposed, which sharpens jagged edges without blurring them, and smoothes out small abrupt changes in the grey-level in monotone areas. It is not much more complex to implement than simple linear filtering. We show that this kind of post-processing significantly reduces the subjective effects of quantization noise in decoded images with almost no degradation of the signal.

An image is partitioned into cells of pxp pixels. Each cell is regarded as a vector of dimension p2and is encoded by searching through a codebook for a nearest matching representative vector. A binary word identifying the selected representative vector is assigned as the codeword to describe the original cell. The decoder uses this codeword to address a codebook. Each entry of the codebook contains a full precision digital representation of one of the N representative vectors. The codebook design is based on a clustering technique for vector quantizer design preceded by a classification of training cells into edge or shade cells. Results for coding rates from 0.5 to 1.5 bits/pixel are discussed. Vector quantization appears to be a powerful and promising technique for image coding.