A Practical Cooperative Multicell MIMO-OFDMA Network Based on Rank Coordination

An important challenge of wireless networks is to boost the cell edge performance and enable multi-stream transmissions to cell edge users. Interference mitigation techniques relying on multiple antennas and coordination among cells are nowadays heavily studied in the literature. Typical strategies in OFDMA networks include coordinated scheduling, beamforming and power control. In this paper, we propose a novel and practical type of coordination for OFDMA downlink networks relying on multiple antennas at the transmitter and the receiver. The transmission ranks, i.e.\ the number of transmitted streams, and the user scheduling in all cells are jointly optimized in order to maximize a network utility function accounting for fairness among users. A distributed coordinated scheduler motivated by an interference pricing mechanism and relying on a master-slave architecture is introduced. The proposed scheme is operated based on the user report of a recommended rank for the interfering cells accounting for the receiver interference suppression capability. It incurs a very low feedback and backhaul overhead and enables efficient link adaptation. It is moreover robust to channel measurement errors and applicable to both open-loop and closed-loop MIMO operations. A 20% cell edge performance gain over uncoordinated LTE-A system is shown through system level simulations.Comment: IEEE Transactions or Wireless Communications, Accepted for Publicatio

LTE-Advanced radio access enhancements: A survey

Long Term Evolution Advanced (LTE-Advanced) is the next step in LTE evolution and allows operators to improve network performance and service capabilities through smooth deployment of new techniques and technologies. LTE-Advanced uses some new features on top of the existing LTE standards to provide better user experience and higher throughputs. Some of the most significant features introduced in LTE-Advanced are carrier aggregation, enhancements in heterogeneous networks, coordinated multipoint transmission and reception, enhanced multiple input multiple output usage and deployment of relay nodes in the radio network. Mentioned features are mainly aimed to enhance the radio access part of the cellular networks. This survey article presents an overview of the key radio access features and functionalities of the LTE-Advanced radio access network, supported by the simulation results. We also provide a detailed review of the literature together with a very rich list of the references for each of the features. An LTE-Advanced roadmap and the latest updates and trends in LTE markets are also presented

Evaluating the effectiveness of Cooperative/Coordinated Multipoint (CoMP) LTE feature in uplink and downlink transmissions

Shannon demonstrated that the channel capacity depends of the ratio of the received signal power to interference plus noise power (SINR). Inter-cell interference caused by neighbouring base stations (BSs) has been identified as one of the most severe problem towards the deployment of LTE technology as it can significantly deteriorate the performance of cellside User Equipment (UE). However, because of regulatory and radiation restrictions as well as operational costs, signal power may only be increased only up to a certain limit to reduce the interference. The other common radio propagation impairment is multipath. Multipath refers to a scenario where multiple copies of a signal propagate to a receiver using different paths. The paths can be created due to signal reflection, scattering and diffraction. As will be discussed later the effects of multipath contribute little to intercell interference because multipath characteristics such as delay spread are compensated for using cyclic prefixes. In this work, we will limit our scope to interference as it has been identified as the main cause of performance degradation for cell edge users due to the full frequency reuse technique used in LTE. To mitigate interference 3GPP devised options of increasing the capacity in LTEAdvanced Release 12 which include the use of spectral aggregation, employing Multiple Input and Multiple Output (MIMO) Antenna techniques, deploying more base stations and micro and femto cells, increasing the degree of sectorisation and Coordinated Multipoint (CoMP). We are primarily interested in evaluating performance improvements introduced when uplink (UL) and downlink (DL) coordinated/cooperative multipoint (CoMP) is enabled in LTE Advanced Release 12 as a way of reducing interference among sites. The CoMP option of reducing interference does not require deployment of new equipment compared to the other options mentioned above hence network deployment costs are minimal. CoMP in theory is known to reduce interference especially for cell edge users and therefore improves network fairness. With CoMP, multiple points coordinate with each other such that transmission of signals to and from other points do not incur serious interference or the interference can even be exploited as a meaningful signal. In September 2011 work on specifications for CoMP support was started in 3GPP LTEAdvanced as one of the core features in LTE-Advanced Release 11 to improve cell edge user throughput as well as the average network throughput. We set to do field measurements in the evaluation of the effectiveness of CoMP in LTE. 3GPP LTE Release 12 was used and cell edge users' performance was the focus. The network operates in 2330 - 2350 MHz band (Channel 40). From the field measurements, it was demonstrated that the CoMP (Scenario 2) feature indeed effective in improving service quality/user experience/fairness for cell edge users. CoMP inherently improves network capacity. A seven (7) percent throughput was noticed

Scheduler Algorithms for MU-MIMO

In multi-user multiple input multiple output (MU-MIMO), the complexity of the base-station scheduler has increased further compared to single-user multiple input multiple output (SU-MIMO). The scheduler must understand if several users can be spatially multiplexed in the same time-frequency resource. One way to spatially separate users is through beamforming with sufficiently many antennas. In this thesis work, two downlink beamforming algorithms for MU-MIMO are studied: The first algorithm implements precoding without considering inter-cell interference (ICI). The second one considers it and attempts to mitigate or null transmissions in the direction of user equipments (UEs) in other cells. The two algorithms are evaluated in SU-MIMO and MU-MIMO setups operating in time division duplex (TDD) mode and serving with single and dual-antenna terminals. Full-Buffer (FB) and file transfer protocol (FTP) data traffic profiles are studied. Additionally, various UE mobility patterns, UE transmit antenna topologies, sounding reference signal (SRS) periodicity configurations, and uniform linear array (ULA) topologies are considered. Simulations have been performed using a system level simulation framework developed by Ericsson AB. Another important part of this thesis work is the functional verification of this simulation framework, which at the time of writing is still undergoing development. Our simulation results show that in SU-MIMO, the second algorithm, which considers ICI, outperforms the first one for FB traffic profile and all UE speeds, but not for FTP traffic profile and medium (30 km/h) or high (60 km/h) UE speeds. In this case, the first algorithm, which does not consider ICI, can be used with advantage. In MU-MIMO, cell downlink throughput gains are observed for the second algorithm over the first one for low and medium system loads (number of users). For both algorithms, the cell throughput is observed to decrease with increasing UE speed and sounding periodicity.Scheduling in modern wireless standards, e.g., 3G, 4G and future 5G, can be defined as the task of allocating time and frequency resources by the base station (BS) to each user equipment (UE) that wants to engage in communication. Resources are allocated every transmission time interval (TTI), which is typically one millisecond. There exist both uplink (from the UEs to the BS) and downlink (from the BS to the UEs) resource schedulers implemented in the e-Node B, i.e., the base station (BS) in Long Term Evolution (LTE). The aim of this thesis work is to study how various communication techniques proposed for 5G can increase the overall system throughput of the downlink (DL) when a realistic resource scheduler is used. In particular, we consider: (i) Beamforming, (ii) Multi-user multiple input multiple output (MU-MIMO), and (iii) Inter-cell interference (ICI) mitigation. Beamforming can be achieved by deploying a large number of antenna elements at the BS with the aim of increasing the signal to interference noise ratio (SINR) towards the UE. Contrary to single-user multiple input multiple output (SU-MIMO), in MU-MIMO more than one UE are scheduled for transmissions in the same time-frequency resource; this is possible by judiciously pairing various UEs which are spatially sufficiently separated (according to some metric that we will define later). ICI mitigation can be achieved by means of proper precoding at BS where the precoder attempts to mitigate the interfering signal from BS towards UEs belonging to neighboring cells. In this thesis work, we investigate the performance of two scheduler algorithms for MU-MIMO, using SU-MIMO as baseline. The first algorithm does not consider ICI while the second one does. Dual layer beamforming (that is, two independent data streams are transmitted to each UE) and time division duplex (TDD) are assumed. In TDD mode the BS acquires the channel information from sounding reference signals (SRS) transmitted in the uplink (UL) and, by virtue of channel reciprocity, reuses the so-obtained channel information in the downlink. The performance evaluation of the two algorithms is based on the following parameters: UE Traffic profile, UE speed, SRS UL antenna configuration, SRS parameters, and BS antenna topology. - UE speed includes 3,30, and 60 km/h. - UE traffic profile includes full-buffer (FB) and file transfer protocol (FTP). With FB traffic profile, UEs send/receive data to/from the BS all the time, while this is not the case in the FTP traffic profile case. Some examples of FTP traffic profiles may include chatty, video, VoIP, web, etc. - SRS UL antenna configuration includes: (i) Two SRS, in which each UE sends two SRS to the BS from two antennas, (ii) one SRS with antenna selection, in which each UE alternately sends one SRS to the BS from each of two antennas, and (iii) one SRS without antenna selection, in which each UE sends one SRS to the BS from only one antenna. For two SRS UE case (note that in the downlink two layers, and hence two UE antennas, are always used). - SRS parameters include SRS bandwidth and SRS periodicity. In this thesis work, full-bandwidth SRS (20 MHz) with various SRS periodicities such as 5 ms, 10 ms, 20 ms are considered. - BS antenna topology includes 8 and 64 antenna elements at the BS. The main result of this thesis work is that in both SU-MIMO and MU-MIMO with FB traffic profile, it is better to use the second algorithm which considers ICI rather than the first one which does not. However, with FTP traffic profile, this is not always the case

Channel Estimation in Uplink of Long Term Evolution

Long Term Evolution is considered to be the fastest spreading communication standard in the world.To live up to the increasing demands of higher data rates day by day and higher multimedia services,the existing UMTS system was further upgraded to LTE.To meet their requirements novel technologies are employed in the downlink as well as uplink like Orthogonal Frequency Division Multiple Access (OFDMA) and Single Carrier- Frequency Division Multiple Access (SC-FDMA).For the receiver to perform properly it should be able to recover athe transmittedadata accurately and this is done through channel estimation.Channel Estimation in LTE engages Coherent Detection where a prior knowledge of the channel is required,often known as Channel State Information (CSI).This thesis aims at studying the channel estimation methods used in LTE and evaluate their performance in various multipath models specified by ITU like Pedestrian and Vehicular.The most commonly used channel estimation algorithms are Least Squarea(LS) and Minimum MeanaSquare error (MMSE) algorithms.The performance of these estimators are evaluated in both uplink as well as Downlink in terms of the Bit Error Rate (BER).It was evaluated for OFDMA and then for SC-FDMA,further the performance was assessed in SC-FDMA at first without subcarrier Mapping and after that with subcarrier mapping schemes like Interleaved SC-FDMA (IFDMA) and Localized SC-FDMA (lFDMA).It was found from the results that the MMSE estimator performs better than the LS estimator in both the environments.And the IFDMA has a lower PAPR than LFDMA but LFDMA has a better BER performance

Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise

Cell-free Massive MIMO (multiple-input multiple-output) refers to a distributed Massive MIMO system where all the access points (APs) cooperate to coherently serve all the user equipments (UEs), suppress inter-cell interference and mitigate the multiuser interference. Recent works demonstrated that, unlike co-located Massive MIMO, the \textit{channel hardening} is, in general, less pronounced in cell-free Massive MIMO, thus there is much to benefit from estimating the downlink channel. In this study, we investigate the gain introduced by the downlink beamforming training, extending the previously proposed analysis to non-orthogonal uplink and downlink pilots. Assuming single-antenna APs, conjugate beamforming and independent Rayleigh fading channel, we derive a closed-form expression for the per-user achievable downlink rate that addresses channel estimation errors and pilot contamination both at the AP and UE side. The performance evaluation includes max-min fairness power control, greedy pilot assignment methods, and a comparison between achievable rates obtained from different capacity-bounding techniques. Numerical results show that downlink beamforming training, although increases pilot overhead and introduces additional pilot contamination, improves significantly the achievable downlink rate. Even for large number of APs, it is not fully efficient for the UE relying on the statistical channel state information for data decoding.Comment: Published in IEEE Transactions on Wireless Communications on August 14, 2019. {\copyright} 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other use

Opportunistic channel estimation with LTE signals of limited bandwidth for positioning applications

The positioning problem is interesting in a variety of applications, especially in indoor environments or in urban canyons, where the position information obtainable with traditional Global Navigation Satellite Systems is limited. In this paper, we deal with the problem of estimating, for the purposes of positioning, the time of arrival (TOA) and the angle of arrival (AOA) by processing LTE 3GPP signals, with particular attention to the uplink signals. The main contribution of this paper is the definition of new opportunistic methods to estimate the TOA and the AOA using the upstream demodulation reference signal (DM-RS) instead of the Sounding Reference Signal. We will show that the use of DM-RS and of estimation algorithms such as the Space-Alternating Generalized Expectation-Maximization and the Iterative Adaptive Approach for Amplitude and Phase estimation (IAA-APES) allows an efficient estimate of the parameters, in spite of the small, occupied bandwidth

Digital signal processing waveform aggregation and its experimental demonstration for next generation mobile fronthaul

L'abstract è presente nell'allegato / the abstract is in the attachmen