Yeni nesil haberleşme sistemleri için yeni bir zamanlama algoritmasının geliştirilmesi
Developing a radio resource scheduler for mobile systems
Yazar: FATİH BURAK KOYUN
Danışman: PROF. DR. MESUT KARTAL
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / Elektronik ve Haberleşme Mühendisliği Ana Bilim Dalı / Telekomünikasyon Mühendisliği Bilim Dalı
Derece: Yüksek Lisans, 2019
Konu: Elektrik ve Elektronik Mühendisliği = Electrical and Electronics Engineering
Dizin: Sayısal haberleşme =   ; Telefon haberleşmesi = Telephone communication

Özet:
İlk mobil haberleşme sistemi 1980'lerde hayatımıza girmiştir. Analog sistemler üzerine kurulu ilk nesilden sonra ikinci nesil sistemlerle birlikte mobil şebeke üzerinden ses trafiğine ek olarak veri trafiğinin taşınmasına da başlanmıştır. Üçüncü nesil sistemlerle birlikte artan bant genişliği ve veri hızları mobil cihazlardan multimedya servislere erişimi mümkün kılmıştır. Bu gelişmeler mobil kullanıcı ve cihaz sayısını büyük bir hızla arttırmıştır.
Dördüncü nesil sistemlerle birlikte sağlanan yüksek hızlı bağlantı imkanıyla birlikte bu artış hızı daha da yükselmiştir. Müşteri tarafındaki artan mobil cihaz ve kapasite ihtiyacı, mobil operatörler tarafında gün geçtikçe yönetimi zorlaşan, sistem kaynaklarını kullanıcılar arasında paylaştırma sorununu ortaya çıkarmıştır. Günümüzde internet trafiğinin büyük çoğunluğunu yüksek çözünürlüklü video, IPTV, çevrimiçi oyun, sosyal medya gibi uygulamalar oluşturmaktadır. Müşteriler artık sabit genişbant ağları kullanmayı azaltarak onun yerine mobil genişbant ağları kullanmaya yönelmektedir. Yakın gelecekte hayatımıza dahil olması beklenen beşinci nesil mobil haberleşme sistemleriyle birlikte nesnelerin interneti (Internet of Things - IoT) teknolojisi mobil şebekeden kaynak talebinde bulunacak mobil cihaz sayısını daha da arttırcaktır.
Kullanıcılara yüksek veri hızı sağlamanın yanı sıra, bu hızı adaletli bir şekilde sağlamak da bir o kadar önemlidir. Müşterilerden sadece küçük bir kesiminin yüksek veri hızlarına ulaşmaları sistem kaynaklarının verimli kullanılması açısından iyi olsa da, bu durum genel müşteri memnuniyeti açısından kabul edilebilir bir durum değildir. Bu noktada radyo kaynaklarının kullanıcılara en verimli şekilde paylaştırılmasının önemi ortaya çıkmaktadır.
Radyo kaynaklarının paylaştırılması için çeşitli zamanlama algoritmaları geliştirilmiştir. Ancak mobil cihaz sayısındaki artışın radyo kaynakları tarafındaki artış hızının çok üzerinde olması yeni algoritma ihtiyaçlarına sebep olmaktadır. Zamanlama algortimalarının tasarımındaki en büyük zorluklardan biri olarak kullanıcılar arasındaki adalet ve sağlanan veri hızınının birlikte maksimize edilmesi gösterilebilir.
Bahsedilen bu gereksinimler doğrultusunda bu çalışmada, algoritmalar arasında en yüksek veri hızını sağlayan Best CQI algoritmasının adalet ölçütünün arttırılması hedeflenmiştir. Bu amaca yönelik olarak; kaynak tahsis edilecek kullanıcının seçiminde, karar mekanizması geçmiş kaynak kullanımı bilgisinin de eklenmesiyle yeniden düzenlenmiştir. Elde edilen algoritma ile adalet ölçütünün önemli derecede arttırılmasıyla beraber veri hızındaki üstünlük de korunmuştur.

Abstract:
The first generation of mobile communication systems was developed during the seventies and launched 1980s. They all have in common that the user traffic, which is voice is transmitted with analog Frequency Division Multiple Access (FDMA). The new thing with second-generation systems was that they supported both voice and data traffic with digital Time Division Multiple Access (TDMA). With the increase in demand for multimedia and broadband services, the next step has been the third generation communication systems. The video was also conveyed over the mobile network with voice and data transmission. The third generation system for Release 99 (3G - Third Generation), High Speed Downlink Packet Access (3.5 G), High Speed Uplink Packet Access (3.5 G), High Speed Packet Access (HSPA) various versions such as High Speed Packet Access + (3.9 G) have been developed. The Third Generation Partnership Project (3GPP) has standardized Long Term Evolution (LTE) to make a structure for 3G evolution towards 4G. LTE is an all-IP packet based system which is aims supporting high data rates, low latency, improved system capacity. In order to achieve these targets, it employs some technologies such as Orthogonal Frequency-Division Multiple Access (OFDMA), Single-Carrier Frequency Division Multiple Access (SC-FDMA), Multiple-Input And Multiple-Output (MIMO), and Hybrid Automatic Repeat Request (HARQ).
OFDMA is a multiple-access modulation scheme based on resources in the time and frequency domains. The smallest resource in the frequency domain is subcarriers and the smallest unit in the time domain is slot. For scheduling, the smallest unit is resource block (RB), which occupies 12 subcarriers in frequency domain, and 1ms in time domain.
The uplink transmission technique, SC-FDMA. is realized in a similar manner as for the downlink (OFDM) and is also called Discrete Fourier Transform Spread OFDM (DFTS-OFDM). The time domain structure is also similar in uplink and downlink. SC-FDMA has much lower Peak to Average Power Ratio (PAPR) than OFDM. This is one the reasons for the choice of SC-FDMA for the uplink since the power amplifier in the user equipment (UE) can be manufactured lower cost then.
MIMO refers to the use of multiple antennas for transmission and reception in a cell. Multiple antenna configurations are expressed in the form mxn MIMO, where m represents the number of transmit antennas and n represents the number of receive antennas. For example, downlink 2x2 MIMO means that the eNodeB uses two antennas for transmission and the UE uses two antennas for reception;downlink 4x4 MIMO means that the Evolved NodeB (eNodeB) uses four antennas for transmission and the UE uses four antennas for reception.
A Medium Access Control (MAC) HARQ layer with fast feedback provides a means for quickly correcting most errors trom the radio channel. To achieve low delay and efficient use of radio resources the HARQ operates with a native error rate which is sufficient only for services with moderate error rate requirements such as, for instance, VolP. Lower error rates are achieved by letting an outer Automatic Repeat reQuest (ARQ) layer in the eNodeB handle the HARQ errors.
Schedulers are located at the Media Access Control (MAC) layer. The basic function of a scheduler is to allocate appropriate system resources to UEs in each subframe for uplink and downlink transmissions, without which the UEs would be unable to transmit and receive data.
In digital communications systems, modulation is the process of varying the amplitude, frequency, or phase of a carrier with a digital baseband signal to convey information using the carrier. A higher-order modulation scheme is one that modulates more bits of information into each modulation symbol, resulting in higher overall spectral efficiency of LTE networks. However, a higher modulation order also requires better channel quality for the receiver to be able to maintain a signal to interference plus noise ratio (SINR) that is high enough to allow for accurate demodulation of the signal. The UE measures its current channel situation to calculate Channel Quality Indicator (CQI) and then sends feedback to the eNodeB. Finally, the eNodeB relates this CQI index to prefer a specific level of MCS and designates RBs accordingly for this UE.
In the downlink, data is terminated in UEs instead of eNodeBs. Therefore, eNodeBs cannot measure the downlink SINR for evaluating downlink channel quality. UEs report channel quality indicators (CQIs) to eNodeBs to indicate the downlink channel quality of services from the eNodeBs. The eNodeBs then determine which modulation and coding scheme (MCS) to use based on these CQIs. CQI values include 0 to 15. The larger the CQI value, the better the channel quality.
Modulation and coding schemes (MCSs) are selected during scheduling. Each MCS represents a specific combination of a modulation scheme and a channel code rate. Scheduling is the process where the scheduler allocates RBs and selects MCSs for UEs.
Common modulation schemes include downlink and uplink quadrature phase shift keying (QPSK), downlink and uplink 16 quadrature amplitude modulation (16QAM), and downlink 64QAM. To meet the demand for the ever increasing data rates required for today's services, 3GPP has also introduced uplink 64QAM and downlink 256QAM. If channel quality is good enough, these modulation schemes help increase uplink and downlink transmission efficiency for UEs.
eNodeBs use different MCSs to ensure transmission efficiency and the quality of UE services. If the channel quality is good, an eNodeB selects an MCS with a high-order modulation scheme combined with a high code rate. If the channel quality is poor, the eNodeB selects one with a low-order modulation scheme and a low code rate (the code rate is higher if fewer redundant bits are inserted). A CQI table maps CQI indexes to modulation schemes.
The development of mobile communication systems has also triggered an increase in the number of users. With the high-speed connection, this rate of increase has risen. Decent use of resources is critical to achieving targeted data rates and improving service quality. The scheduling of resource allocation is a radio resource management problem. Various algorithms have been developed for scheduling of resources. The basic scheduling algorithms in the literature are Round Robin (RR), Best CQI and Proportional Fair (PF).
In this thesis, it is aimed to develop a scheduling algorithm which may be an alternative to the existing scheduling algorithms in the literature. A new scheduling algorithm that balances the performance between fairness and throughput is proposed. By the proposed scheduling algorithm, it is aimed to increase the fairness index which can be considered the most negative aspect of Best CQI algorithm.
The number of resource blocks that mobile devices have reached in the past has been used in the decision mechanism. Performance metrics compared with Best CQI, PF, and RR.
The proposed algorithm is better than the Best CQI algorithm in terms of fairness. At the same time, it has been achieved to allocate resources to users who have never reached the resources. According to the results of the simulation, the criteria of throughput fairness increased together with the distribution fairness criteria.