Month: December 2016

Jose F. Monserrat (Universitat Politècnica de València)

The specification of the 3GPP Release 14 began in September 2014 and marked the beginning of the New Radio (NR) specification, which will be the 3GPP candidate to 5G, as defined by the ITU-R for the IMT-2020 family of standards. The Release 14 is near its conclusion, as the definition of protocols (stage 3) is expected to be completed in June 2017, with the subsequent revisions to correct problems and bugs.

Definitely, the key input of Release 14 is the start of work on the specification of a new RAT non-backward compatible with LTE-A and with parallel evolution. This radio technology, which is known as New Radio, has started with a study item in Release 14 on scenarios and requirements, which began in December 2015. To date this study item has defined several important aspects of what shall be the proposal from 3GPP for 5G. In parallel, and from the second quarter of 2016, they are also studying the most appropriate technological solutions to meet the requirements marked. However, it is not going to be until the Release 15, when this NR is specified, expecting its realization in phase 1 in the second half of 2018.

However, Release 14 is much more than the beginning of the 5G, and there are more than 30 studies affecting aspects as diverse and as important as the following: V2X communications, improved location services, reducing latency in LTE, the separation of the user plane and control (so important for virtualization), improvements in the use of unlicensed spectrum, the extension relaying schemes for communication between machines, the carrier aggregation between bands, various improvements in broadcasting, or the extension in the number of antennas to more than 16. Because its special relevance, this post extends the description of three aspects, improved latency for LTE, the V2X communication aspects and Licensed-Assisted Access.

Improved latency for LTE

The item entitled “The study on techniques for LTE Latency reduction”, was finalized in June 2016 in the technical report 3GPP TR 36.881, giving terminate this study item from that point.

This improvement work mainly focused on improving semi-persistent scheduling (SPS), handover latency and reduction of the TTI length.

Regarding the former, it was interesting to enable SPS solution with 1 TTI period. This greatly reduced signalling for users with a high demand for resource availability. Regarding improving handover latency, the possibility to make a handover without a new RACH process was studied as well as maintaining connected the source cell throughout the handover period. Although both solutions were stressed as promising, it was not addressed the feasibility of these ideas. Finally, with regards to the reduction of TTI length, the simulation results were not promising for many services, and it was concluded not to reduce the TTI length below 1 slot, i.e. 0.5 ms.

V2X communications

Enabling direct communications between vehicles within the cellular system is a key to deal with the necessary security for the autonomous cars deployment. The standardization of V2X communications began in Release 13 with a study item on the requirements of ITS services. There are several specific aspects of this type of communication that make it particularly complex, including the relative lack of synchronism between the terminals and the high speed of transmitter and receiver, which requires a higher density of pilots to enable a proper coherent detection. In Release 14 these issues are addressed within the study item “Support for V2V services based on LTE sidelink”.

Although the study item has not yet been closed, the radio aspects are considered already completed being included in 3GPP technical report TR 36.785, while operational procedures are expected to be completed by March 2017.

The system is expected to operate with different bandwidths, including 10 MHz, using a dedicated carrier for V2X communications and the use of GNSS from satellites for time synchronization.

Two configurations have been defined. In configuration 1, the system is fully distributed, both for interference management and for scheduling, and it was defined a new way of scheduling, mode 4, which allows sensing and semi-persistent scheduling. Resource allocation also depends on the geographic information.

In configuration 2, mode 3 scheduling is used, which allows eNBs to assist in decision-making regarding interference management and scheduling, by using specific signalling over the Uu interface. In short, the eNB determines the set of resources that vehicles distribute dynamically.

Licensed-Assisted Access 

3GPP already included in Release 13 the possibility of transmitting in downlink in secondary cells operating in unlicensed spectrum, with control of a main cell operating in licensed spectrum. It is what is known as Licensed-Assisted Access.

LAA improvements are included in Release 14 within the study item known as “Enhanced LAA for LTE”. In late 2016, major contributions have focused on the necessary changes within the core of the wireless protocols to support this functionality, with modifications especially in the RRC and MAC protocol and physical capabilities of the user equipment and base stations. Other aspects are under development, and it is estimated that enough progress on the LAA issue won’t be expected until mid-2017.

The main complexity of LAA lies in the coexistence with other protocols in unlicensed bands, such as the IEEE 802.11 family. Therefore, LAA should include procedures for listen-before-talk (LBT) and discontinuous transmission schemes to allow lower occupancy of possible channel. Furthermore, Release 14 will include the transmission in LAA for the uplink also, so that signalling must be highly compressed compared to conventional operation.

Carsten Bockelmann (University of Bremen)

In the 5G book we focused on the overarching challenges to reduce the signaling overheads from protocol level to the physical layer design. Several ideas were discussed to resolve the problems of todays access reservation strategies to enable a truly massive access. However, todays systems mostly rely on coherent detection strategies that require knowledge about the channel state. Therefore, efficient channel estimation is a very important aspect to reduce the physical layer overhead in case of a massive number of users. In principle, the channel state information of every user communicating with the base station must be estimated which incurs a significant overhead in massive MTC with very small payloads (think temperature sensors, status messages, etc.). Furthermore, if large coverage areas are targeted high quality channel estimation requires significant resources for pilots to ensure good Signal-to-Noise ratios by noise averaging. Therefore, an alternative approach is called for.

Figure 1 – Multi-Carrier Compressed Sensing Multi-User Detection (MCSM) concept and components.

Taking the lessons learned and summarized in current research and the 5G book we proposed the so-called Multi-Carrier Compressed Sensing based Multi-User Detection (MCSM) as a physical layer concept for massive MTC [1, 2, 3]. MCSM is comprised of three main building blocks: (i) a multi-carrier waveform; (ii) Compressive Sensing Multi-User Detection (CS-MUD) and (iii) non-coherent communication.

The many advantages of multi-carrier waveforms are well discussed and need not to be repeated here. For MCSM two things are of importance: the realization of narrowband sub-channels in larger spectrum bands and flexible allocation of such narrow-band sub-channels. Specifically, narrowband sub-channels are required to enable easy differential modulation as explained below.

The second building block is Compressed Sensing based Multi-User Detection (CS-MUD) which serves as an activity detector in this concept and simultaneously separates the multi-user data streams that are superimposed through CDMA-like spreading [4]. Thus, CS-MUD reduces the protocol overhead as already discussed in the book, but in contrast to previous assumptions does not estimate the user data symbols. Instead it realizes the multi-user detection and provides estimates of the differentially encoded user symbols.

Finally, the third block “differential modulation” is introduced to solve the pilot overhead problem through non-coherent detection. Non-coherent communication is a very attractive solution for several reasons. A major advantage is the avoidance of channel estimation and the incurred pilot overhead. Instead of channel estimation and equalization the data is mapped onto the phase of transmit symbols which makes it robust against phase changes caused the by the transmit channel. If the channel is non-frequency selective and constant over the frame length only the starting phase of the data symbols must be known which reduces the overhead tremendously. As already indicated, the building block “multi-carrier waveforms” is required to implement this easily in a multi-service context. Massive MTC users are served by allocating sufficiently small sub-bands within the coherence bandwidth of the channel for a single MCSM system. Then, each MCSM system only experiences a non-frequency selective single-tap channel well suited for non-coherent modulation.

Of course, it is well known that non-coherent modulation suffers performance losses equivalent to a 3 dB SNR loss, but with advanced demodulation concepts this loss can be compensated in part [5]. So, fitting the theme of “simple transmitter” and “complex receiver” complexity is once again shifted to the base station for massive MTC uplink communication.

Figure 2 – Narrowband MCSM systems hopping in frequency.

A downside of narrowband MCSM channels is the dependence on channel quality as illustrated in Fig. 2. In the unlucky case that a user experiences a “bad” channel in the allocated frequency band decoding is nearly impossible. Therefore, the MCSM concept includes frequency hopping to allow for frequency diversity in one frame. Multiple MCSM systems can hop (pre-planned or randomly) in the allocated massive MTC resources as shown in Fig. 2 and thereby achieve a more stable performance. However, hopping incurs additional overhead. The starting phase of the differentially encoded user symbols must be known after each hop which is equivalent to another “pilot”. Hence, careful system design is required to balance overhead and diversity gains appropriately.

Finally, it is interesting to have a look at the performance of the MCSM concept depending on the allocated bandwidth. Fig. 3 shows the frame error rate after decoding of a half-rate convolutional code given different per user data rates [2]. Each rate corresponds to “narrowband” bandwidth that is allocated (fixed D-QPSK modulation and code rate). Thus, with increasing data rate the coherence bandwidth of the channel (approx. 300 kHz here) is increasingly violated leading to additional decoding errors. It is quite clear that such a system is highly dependent on the coherence bandwidth and chosen data rates (bandwidth) and must be carefully designed. Still, the general concept shows promising performance with low physical and medium access layer overheads. Also, we could show a first practical evaluation of MCSM in indoor contexts to demonstrate the practicality of the approach [6]. Surly, depending on the cell sizes, deployments, and so on the MCSM parametrization requires careful adaptation in a larger system context like 5G.

Figure 3 – Frame error rate over SNR for different data rates. Each data rate corresponds to an MCSM system bandwidth. Increasing data rates violate the coherence bandwidth (ca. 300 kHz) of the channel.

References

[1]       F. Monsees, M. Woltering, C. Bockelmann, and A. Dekorsy: „Compressive Sensing Multi-User Detection for Multi-Carrier Systems in Sporadic Machine Type Communication,” IEEE 81th Vehicular Technology Conference (VTC2015-Spring), Glasgow, GB, May 2015.

[2]       F. Monsees, M. Woltering, C. Bockelmann, and A. Dekorsy: „A Potential Solution for MTC: Multi-Carrier Compressive Sensing Multi-User Detection,” The Asilomar Conference on Signals, Systems, and Computers, Asilomar Hotel and Conference Grounds, USA, November 2015.

[3]       F. Monsees, M. Woltering, C. Bockelmann, and A. Dekorsy: “Multicarrier, Multi-User MTC System using Compressed Signal Sensing,” Paten application, PCT W02016177815 / DE102015208344A1.

[4]       C. Bockelmann, H. Schepker, and A. Dekorsy: „Compressive Sensing based Multi-User Detection for Machine-to-Machine Communication,” Transactions on Emerging Telecommunications Technologies: Special Issue on Machine-to-Machine: An emerging communication paradigm, Vol. 24, No. 4, pp. 389-400, June 2013.

[5]       L. Lampe, R. Schober, V. Pauli, and C. Windpassinger: “Multiple-Symbol Differential Sphere Decoding,” IEEE Transactions on Communications, Vol. 53, No. 12, December 2005.

[6]       M. Woltering, F. Monsees, C. Bockelmann, and A. Dekorsy: „Multi-Carrier Compressed Sensing Multi-User Detection System: A Practical Verification,” 19th International Conference on OFDM and Frequency Domain Techniques (ICOF 2016), Essen, Germany, August 2016.