An Extremely Flexible, Energy, and Spectral Effective Green PHY-MAC for Profitable Ubiquitous Rural and Remote 5G/B5G IoT/M2M Communications

An Extremely Flexible, Energy, and Spectral Ef fective Green PHY-MAC for Pro fi table Ubiquitous Rural and Remote 5G/B5G IoT/M2M Communications Alexander Markhasin ( & ) Siberian State University of Telecommunications, Novosibirsk, Russia almar@risp.ru Abstract. In this paper, the fundamental PHY-MAC throughput limits and extremum of the energy, power, spectral ef fi ciency invariant criteria are proved. The invariant criteria are constructed relying on Shannon ’ s m -ary digital channel capacity which a rich palette of the technically interpreted PHY-MACs parameters consider. Therefore, the invariant criteria as very suitable for research and design of an 5G extremely performance problems are found. The PHY-MACs smart distributed control techniques which able implements “ on-the- fl y ” the limits close and invariant criterion optimization or trade-of f is proposed. Such PHY-MAC ’ s smart control techniques represent a key disrup- tive technologies meet the 5G/B5G network challenges. Keywords: 5G/B5G  Rural  PHY-MAC  Green  Pro fi table 1 Introduction Unacceptably high investments are required into deployment of the optic core infras- tructure for ubiquitous wide covering of spars ely populated rural, remote, and dif fi cult for access (RRD) areas using the recent (4G) and also forthcoming (5G) broadband radio access (RAN) centralized techni ques, characterized by short cells ranges, because their pro fi tability boundary exceeds a several hundred resi dents per square kilometer. Furthermore, the unprecedented requirements and new features of the forthcoming Internet of Things (IoT), machine-to-machine (M2M), smart city, and also many other machine type IT-systems lead to a breakthrough in desig ning extremel y intensive technologies for future 5G/B5G wireless systems which will be able to reach in real time the performance extremums, trade-of f opti mums and fundamental limits [ 1 – 3 ]. Recently, a numbe r of 5G extremely intensive solutions were proposed which are suitable mainly for well-urbanized areas: ultra-dense networks [ 4 ], massive MIMO [ 5 ] and M2M for smar t city [ 6 ], disruptive 5G PHY technology [ 2 ]. For weakly urbanized areas, we offer extremely effective green [ 7 ] techniques as an approach for ubiquitous pro fi table covering by 5G/B5G IoT/M2M/H2H multifunc- tional communications of the RRD terr itories [ 8 , 9 ]. Practically, the necessary and suf fi cient conditions for RRD areas pro fi tability border overcom ing envisages three extremal RRDs networking perfor mances ’ : (i) the hyper long range hypercells ’ radically Author Proof distributed cost-ef fecti ve Multifunctional Hyperbus Architecture (MFHB A) [ 8 , 9 ] and MFHBA mission-critical convergent techniques – (ii) the extremely energy-effective green PHY [ 1 0 ], and (iii) the supreme throughput capacity multifunctional MAC [ 11 ]. Convergent PHY-MACs shall close the Shannon ’ s fundamental limits or extre mums using the multifunctional opti mal “ on-the- fl y ” control techni ques [ 8 , 12 ]. Recently [ 3 , 7 ], the spectral (SE) and energy (E E) ef fi ciency criteria are expressed usually throu gh the Shannon ’ s capacity of the continuou s channels with additive white Gaussian n oise (AWGN) [ 13 ] whi ch, in principle, allow to study only the PHY potential ef fi ciency values depending directly on three spect ral-power basic parameters, i.e., bandwidth Δ F s , signal power P s and AWGN noise power P n .I n[ 10 , 14 ] so called invariant criteria of spectral (ICSE), power (ICPE) and energy ICEE) ef fi ciency were fi rst introduced for ortho gonal spread spectrum m-ar y signals. The invariant criteria are constructed relying on Sh annon ’ s m-ary digital channel capac ity which considers a rich palette of the technicall y interpreted PHY-MAC parameters. Therefore, the invariant criteria wer e found very suitable for research and design of an 5G extremely perfor- mance problems. In this paper, we generalize and develop the results of our abov e cited researches of the RRD radically distributed multifunctional device-centric MFHBA architecture, fundamental RRD PHY an d information-theoretic RRD MAC limit s and extre mums focused on the 5G/B5G extremel y performance issues and also PHY-MAC multi- functional optimal control techniques whi ch meet green p ro fi table ubiquitou s rural and remote 5G/B5G IoT/M2M/H2H communi cations. The conceptual vision of the green pro fi table ubiquitous RRD 5G/B5G IoT/M2M/H2H architecture is also presented. 2 Extremely Green and Cost-Ef fective Ubiquitous RRD 5G PHY 2.1 Vision of Extremely Green and Ef fecti ve 5G PHY for RRD Areas As stated above, the widespr ead cell range of the recent (4G) and forthcoming (5G) generations of radio access techno logies (RAN) does not exceed few kilometers. The sparsely populated RRD areas dif fer by low density up to a few tens residents. Hence, the reall y indi spensable approach for overcoming the 5G RRDs economical barrier lead to extre mely incre asing of the numbe r of the ef fectual subscribers, i.e., to increasing of the air interface range of broadband hyperce lls by several ten times through approaching the fundamental Shannon limits of spectral (SE) and power (PE) ef fi - ciency. Usually [ 3 , 7 ], the SE and PE ef fi ciency criteria are expres sed through the Shannon ’ s capacity of the continuous channel s with a dditive AWGN noise [ 13 ] C ¼ D F s log 2 ð 1 þ P s = P n Þ ; ð 1 Þ where D F s is bandwidth, P s – signal p ower, P n – noise power, P n ¼ D F s N 0 , N 0 – signal-sided spectral power noise density, in Watt-per-Hertz. In the chann el output, or receiver input, power characteristic P s = P n is called the signa l-to-noise-ratio (SNR). 2 A. Markhasin Author Proof However, the continuous channel throughput capacity ( 1 ) allow to study only the potential ef fi ciency PHY values dependi ng directly on three spectral-energy basic parameters. So called invariant criteria of spectral, power and energy ef fi ciency [ 10 ] allow to solve an optimization or trade-of f problem depending on the set of real conditions and parameters of the radio channel, methods of signa l coding, formation, modulation, transmitting, receiving, processing, decoding, etc. Two invariant ef fi ciency criteria were fi rst introduced for the wireless physical layer with orthogonal spread spectrum m -ary signals in [ 14 ] basing on Shannon ’ s m -ary digital channel capaci ty. As in [ 10 ], let us introduce an invariant ef fi ciency criterion for modern 5G PHY relying on SINR [ 15 ] approac hes. The invariant criterion for spectral ef fi ciency (ICSE) was introduced as the digital channel Shannon capacity per Hertz ((bit/sec)/Hz): c F ð m ; g ; B s Þ¼ C m ð g ; B s Þ = ð B s = 2 Þð 2 Þ where g is channel-si de, or receiver input, mean square signal power invariant variable expressed via signal-to-interference plus noise ratio (SINR) [ 15 ], g 2 ¼ P s = ð P i þ P n Þð 3 Þ P s , P i , P n are, respectively, signal, interfere nce, and noise powers, B s is frequency-time invariant variable named as signal ’ s base, B s ¼ 2 D F s T s , T s is m -ary signal duration. Further, C m ð g ; B s Þ is m -ary digital channel Shannon capacity in bit-per-symbol [ 10 ], C m ð g ; B s Þ¼ log 2 m þ½ 1  p m ð g ; B s Þ log 2 ½ 1  p m ð g ; B s Þ þ p m ð g ; B s Þ log 2 ½ p m ð g ; B s Þ = ð m  1 Þ ; ð 4 Þ where p m ð g ; B s Þ is m -ary symb ol ’ s error probability (SER) [ 15 ]d e fi ned throu gh invariant variable h ð g ; B s Þ¼ g ffiffiffiffiffiffiffiffiffi ffi B s = 2 p expressed, in turn, through receiver ’ s output ratio signal energy per symbol to signa l-sided spect ral power additional Gaussian interference plus noise density N 0 in ¼ N 0 i þ N 0 n , i.e., energi es SINR, or ESI NR [ 10 ]: h 2 ¼ E s = N 0 in ¼ P s B s = ½ 2 ð P i þ P n Þ ¼ g 2 B s = 2 : ð 5 Þ An invariant criterion for power ef fi ciency (ICPE) was introduced as the signal-to-interference plus noise ratio (SINR ) per m -ary digital channel Shannon capacity per Hertz: SINR/[(bit/sec)/Hz] [ 10 ]: w ð m ; g ; B s Þ¼ g 2 = c F ð m ; g ; B s Þ : ð 6 Þ One can express a power ef fi ciency criterion ( 6 ) through various measure units: dBm per (bit/sec)/Hz, Watt per (bit/sec)/Hz, a nd also convert it to energy ef fi ciency invariant criterion (ICEE) in Joule per (bit/sec)/Hz. Moreover, through invariant cri- terion for power ef fi ciency ( 6 ) one can express the invariant criteria for cover ef fi ciency (ICCE) in Watt/(bit/sec)/ Hz/squar e km, i.e., IC PE per area coveri ng by cell radius R c ð m ; g ; B s Þ and also invariant crite rion for investment (cost) ef fi ciency (ICIE) through CAPEX calculated as some invariant function F I ½ w ð m ; g ; B s Þ divided into area cov- ering p R 2 c ð m ; g ; B s Þ . Extremely Flexible, Energy, and Spectral Ef fective Green PHY-MAC 3 Author Proof Based on the introduced invariant criteria, we can formulate the foll owing RRD-aimed breakthrough qualities and techniques capable to implement the perfect green 5G PHY for hyperrange space/ wireless mediums corres ponding to rural ubiq- uitous IoT/M2M/H2H 5G communications: • design an advanced set of the orthogonal broadband m -ary OFDM-CDMA like waveforms correspondin g to a perfect green 5G PHY for h yperrange space/wireless mediums which are wel l adapted to cognitive interference-robust “ on-the- fl y ” control and approaching the trade -of f extremum s or fundamental limits of the spectral/power/energy/ economics ef fi ciency criteria [ 10 ]; • re fi ne the green 5G PHY disruptive approaches for the potent ially reachabl e energy-saving techniques of hyperrange rural area cost-ef fective covering; • increase the channel-side ratio SINR ( 3 ) in pure ecological way of imp rovement both the denominator (reduce an interference [ 16 ]), and the numerator (smarter increase a beamforming and antenna gain, as Frii s models), close to the funda- mental limits without the rise of transmitter po wer; • reaching conti nuously the fundamental minimum [ 10 ] power consumpti on criterio n ICPE representing an imperative law for smart green PHY optimi zation and trade-of f problems; • as in [ 3 ], developing the pro fi tability-pow er-ef fi ciency-aim ed fundamental trade- of fs for rural green 5G networks in practical invariant variables notions. 2.2 Fundamental Limits and Extremums of 5G PHY The fact that the value of invariant function F(x 1 ,x 2 … ) does not change by substitution instead of every x i argument ’ s his x  i ð x 1 ; x 2 ; ... Þ invar iant maps may be suitable for universal appropr iateness resear ch all measures: the information, the powe r, the cov- ering, and the investment (i.e., pro fi tability) meas ures. Let us denote by U the set of possible values of the invariant parameters ð m ; g ; B s Þ . In a speci fi c optimiza tion problem some invariant variables are free and other parameters are fi xed. We denote the set of possible values of the free variables by V ; V 2 U . Next we can form ulate a set of general optimi zation problems [ 10 ]. Power Ef fi ciency Optimization Problem. For ICPE ( 6 ), we can formulat e the general optimization problem w ð m ; g ; B s Þ! min, ð 7 Þ where a free variable belongs to V . It is necessary to bind the problem ( 7 ) with the constraint on the least permissible value ½ c F  min of ICSE c F ð m ; g ; B s Þ½ c F  min ð 8 Þ and, possibly, the constraints on the permissible values of cover ef fi ciency ICCE and investment ef fi ciency ICIE, i.e. pro fi tability. The example of the numerical analysis [ 10 ] of ICPE opti mization problem is show n in Fig. 1 . 4 A. Markhasin Author Proof Studying the Fig. 1 a and [ 14 ], we can formulate a fundamental power-consumption Statement 1: The minimal speci fi c power consumption ( 6 ) w min ð m ; g ; B s Þ per (bit/sec)/ Hz for fi xed alphabet size m , and free g and B s for both Gaus sian noise and interference is a univer sal power const ant which depends neither on the signa l base B s nor on SINR ( 3 ). Let w  min ð m ; g  ; B  s Þ be some minimum point on graph of Fig. 1 a which was expressed in SINR-per-(bit/H z)/sec. We can express this minim um value in Joule-per- (bit/Hz)/sec using the invariant relationship w  Jc ð m ; g  ; B  s Þ¼ w  min ð m ; g  ; B  s Þ N  0 in B  s = 2, where N 0 in is the value realized in minimum point of both Gaussian inter- ference an d signal-sided noise spectral power density as in ( 5 ), N 0 in ¼ N 0 i þ N 0 n ,i n Watt-per-Hertz. Moreover, we can expres s this minimum value in Joule-per-bit w  Jb ð m ; g  ; B  s Þ¼ w  Jc ð m ; g  ; B  s Þ B  s = 2. Spectral Ef fi ciency Optimiz ation Problem. For ICSE ( 2 ), we can formulate the general optimization problem [ 10 ]: c F ð m ; g ; B s Þ! max ð 9 Þ with respect to free variables belonging to the subset V ; V 2 U . The problem ( 9 ) expediently be bound wi th constraints on the in fi mum value of ICPE criterion w ð m ; g ; B s Þ¼ const( m Þ w inf ð m ; g  ; B  s Þþ o ð w Þ ; ð 10 Þ where o(w) is Landau Small Symbol. The Eqs. ( 9 ) and ( 10 ) determine the fundamental extremum of the invar iant power ef fi ciency ICPE ( 6 )a si n Statement 2: The fundamental local maximum, or conditional suprem um, of the invariant spectral ef fi ciency ( 2 ) under the condition of minimal powe r consumption, or conditional in fi mum ( 10 ), equals the solut ion of the problem ( 9 ). Fig. 1. The graphs of general optimization problems of green invariant ef fi ciency criterion: (a) close fundamental minimum limit (in fi mum) of power ef fi ciency ICPE [ 10 ]; (b) close upper limits of spectral ef fi ciency ICSE (calculation: T. Pereverzina, D. Shatsky). Extremely Flexible, Energy, and Spectral Ef fective Green PHY-MAC 5 Author Proof Figure 1 b shows three subsets of ICS E spectral ef fi ciency optimization graphs accordingly to three fi xed values of SINR invariant variable (g = 0,5/1,0 /2,0) and dif ferent signal alphabet sizes m with dependency from signal base B s variations. In fact, the given series of SINR express the changes of channel quality from very poor up to average. Observing the numerical optimi zation graphs according to the given SINR series and correlating the signal complexity with signal base B s values presented on Fig. 1 b graphs and [ 1 4 ], we can state the following fundamental ICSE. Statement 3: Opt imal signa ls according to the spect ral ef fi ciency criterion ( 2 ) should be more complicated as the quality of SINR of the channel is worse, and, on the contrary, these signals should be easier when the quality of the SINR is better. The above formulated stat ements lead to extremely green strategies of minimal power consumption and energy savin g for both the ultra-dense urban and also the ultra-covering or extremely cost-ef fective rural optimization problems. 2.3 Fundamental Limits of m -ary Orthogonal Signal Interfe rence As shown in [ 16 ], the errors of inaccurate ful fi llment of conditions of mutual signals orthogonality inevitably generate the intra-cell and inter-cell interference that deter- mines the avail able value of the SINR ratio. The SINR value, in turn, limits the capacity o f cellular cell. In [ 16 ], an advanced calculation method of the CDMA net- work capacity is of fered, which allows to consider the dependences “ SINR versus not strict ortho gonality errors ” directly through the orthogonal signals autocorrelation and mutual correlation funct ions. It is shown, that it is p ossible to raise many times the SINR or network capaci ty by reduction of the signal orthogonality errors. The state- ments concerning fundamental limits for interference power are proved [ 16 ]: Statement 4: If the errors E caused of the not-strictly orthogonality of the intra-cell m - ary orthogonal signals ensembles can be reduced as wished, then the power P(E) of intracell interference can be asymptotically decreased up to as much as small values : lim E ! 0 P intra  cell ð E) ¼ lim E ! 0 X n  1 j ¼ 0 ; j 6¼ i 1 T ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi M ½ K 2 ji ð t ; E j Þ q ¼ 0 ; ð 11 Þ where K 2 ji ð t ; E j Þ is the intra-cel l mutual correlation function. Figure 2 explains the impac t of the reduct ion of the signal orthogonality errors on the raise many times of the SINR or the network capacity. Statement 5: If the errors E caused by the not-stri ct orthogonality of the inter-cell m - ary orthogonal signals ensembles can be reduced as wished, then the power P(E) of inter-cell inte rference can be asymptotically decreased to smal l values of an order of Landau Big Symbol 0 ð M ½ a  ; 1 = ffiffi ffi n p Þ : 6 A. Markhasin Author Proof lim E ! 0 P inter  cell ¼ lim E ! 0 X J 2 G n I X J 2 G n I X n  1 j J M ½ a j J  = T  ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi M ½ K 2 j J i ð t ; E j J Þj j J 2 J ; i 2 I  q ¼ 0 ð M[ a  ; 1 ffiffi ffi n p Þ ; ð 12 Þ where K 2 j J i ð t ; E j J Þ is the inter-cell mutual correlati on function, M[ a  is the weighte d average of the space path loss indexes a j J , n – the degree of the generat ing M-sequence polynomial. 3 Extremely Flexible and QoS-Guaranteed Distributed Multifunctional RRD 5G MAC 3.1 Vision of the Distrib uted Multifunctional Perfect 5G MAC Assume that at some time t some quantity N t of machine type network ’ s i th devices ’ / users ’ which de fi ned by k th data service classes, G ikt input traf fi cs intensities, S ikt output traf fi c intensities, total traf fi c G t ¼ P i ; k G ikt  C MAC , where C MAC ¼ max f G t ; t g P i ; k S ikt ð G t Þ is MAC useful throughput, is active. Let we denote further by X ikt the really values of service parameters by ½ X ikt  – their required values, and by Y it – i th device ’ s bandwidth resource. In our vision, the perfect machine type (MTC ) rural 5G MAC protocol represents a MTC-enhanc ed fl exible multifuncti onal distributed long- delay medium access control technology (MFM AC [ 8 ]), incl uding also the functions of guaranteed dynamical control up to real time ( “ on the fl y ” ) of the bandwidth resources f Y it g allocation, guaranteed dynamical contr ol accordingly to k th data service classes of the traf fi c p arameters f S ikt g and soft/dif ferent QoS param eters f X ikt g , i.e., personally guaranteed Quality of Experience (QoE) for any user/device. Fig. 2. 3D graphs SINR versus standard deviations of the synchronization e t and phase error e / by thermal noise − 113.101 dB [1 6 ]. Extremely Flexible, Energy, and Spectral Ef fective Green PHY-MAC 7 Author Proof The required qualiti es of a perfect rural 5G MAC protocol may be implemented as MTC-aimed enhancem ents of the multifunctional distributed long-delay medium access control techniques [ 8 , 12 ] exactly: • high ef fi ciency, tolerance, and lower latency [ 12 ], higher throughput and minimal overheads both come nearing fundamental limits [ 11 ] for a distributed multiple access control to long-delay wireless/space mediums; • high controllability, reliability, stability, fl exibility, and guarantee of distributed dynamical ( “ on the fl y ” ) con trol of broadband RAN technologies [ 8 , 9 , 12 ]; • multifunctional and universality abilities that rely on the dynamical ly contr olled and adaptive ATM-like smart uni fi ed protocol MAC, i.e., MFMAC [ 8 , 12 ], through the entire wireless networking hierarchy – core, backbone , and acc ess networks; • fully mesh all-device-centric radio access architecture all_device-to-all_device (D m D, m >>2) relies on the mul tipoint-to-multipoint (MPMP ) [ 9 ] Virtual Space/ Wireless ATM Hyperbus topology with fully distributed QoS-guaranteed multi- functional long-delay MAC [ 8 ]; • cost-ef fective completely distributed (grid-like) all-IP/M PLS over ATM-MFMAC Hyperbus (MFHBA) that implements the data packet selecting technique rather than packet switching technique [ 8 , 9 ]. 3.2 Fundamental Limits of the Di stributed MAC As showed [ 11 ], the real reachabl e throughput for various MAC protocols depends on ensuring the “ MAC collective intellect ” that contains a plenitude of information about the real-time state of the mul tiple access processes in geographical ly distributed queues, and also on the normalized overhead for provisioning QoS. What is the minimum reachable, or in fi mum, MAC overhead? And what is the potent ial reachable maxi mum throughput, or fundam ental limit of potential capacity, of the ideal MAC proto col? It is reasonable to fi nd the MAC overhea d in fi mum as the Shannon entro py of the dist ributed multiple access processes based on the Marko v model s of distrib uted queues, and to fi nd the potential capacity of MAC protocols as a function of the overhead in fi mum. Let we de fi ne the real throughput capacity for real MAC protocol speci fi ed by real structural speci fi cations and system parameters Γ , and by real medium conditions Ψ including presence of errors as C C ; W ¼ max f G 2 F G g S C ; W ð G Þ ; ð 13 Þ where F G is the fi eld of the possible values of input traf fi c intensity G. As in [ 11 ], we de fi ne the MAC throughput fundamental lim it as supremum of the real throughput ( 13 ) on the set F C of MAC proto col ’ s po ssible structural speci fi cations and system parameters by given medium conditions Ψ , i.e., as potential capacity, C sup W ¼ sup f G 2 F G ; C 2 F C g S C ; W ð G Þ¼ M ½ s  = ð M ½ s þ d inf W Þ¼ 1 = ð 1 þ v inf W Þ ; ð 14 Þ 8 A. Markhasin Author Proof where d inf W is the potential reachabl e minimum, or in fi mum, of the time resource overhead for medium access contr ol per data unit/packe t by durat ion M ½ s  , d inf W ¼ inf f C 2 F C g d C ; W ; ð 15 Þ m inf W is the normalized value of the in fi mum of overhead ( 15 ) according M ½ s  . The MACs o verhead and throughput fundamental limits for widespread queueing models of distributed multiple access systems TDMA determine the stat ements [ 11 ]: Theorem 1: If the TDMA system is described by an in fi nite model of equiva lent centralized M/M/1 queue C 0 by W 0 zero errors channel conditions, then the value of minimum reachable overhead on distributed MAC contr ol is equ al to inf f C 2 F C g v C ; W 0 ¼ v inf C 0 ; W 0 ¼½ 2 þ H ð s Þ = BM ½ s  ; ð 16 Þ and the potential throu ghput capacity of the ideal MAC is equal to sup f C 2 F C ; G 2 F G g S W 0 ; C ð G Þ¼ C sup W 0 ¼ 1 = ð 1 þð 2 þ H ð s ÞÞ = BM ½ s Þ ; ð 17 Þ where B is the bit rate, M ½ s  is the mean duration of traf fi c packet s, H ð s Þ is the entro py of the packets durat ion distribution given by the geometric law [ 11 ]. Theorem 2: If the TDMA system is described by the in fi nite model of equiva lent centralized M/D/1 queue Γ 0 under conditions described in Theorem 1, then the value of minimum reachable expenses on distributed MAC contr ol is equal to inf f C 2 F C g v C ; W 0 ¼ v inf C 0 ; W 0 ¼ 1 ; 854 = BM ½ s ð 18 Þ and the potential throu ghput capacity of the ideal MAC protocol is equal to sup f C 2 F C ; G 2 F G g S W 0 ; C ð G Þ¼ C sup W 0 ¼ð 1 = ð 1 þ 1 ; 854 = BM ½ s Þ : ð 19 Þ We observe in Fig. 3 , that the MAC ’ s total entropy, i.e., overhead in fi mums ( 16 ) and ( 1 8 ), depends mainly from the data slots duration law indeterminacy. The M/M/1/* systems family must be characterize d by greatest entropy in accordan ce with its exponential law ’ s greatest indeterm inacy. Opposite them, the M/D/1/* systems which are described by deterministic duration law ensure the least entropy, therefore – the greatest MAC potential throughput capacity ( 17 ) and ( 19 ). As proved in [ 11 ], the adaptive controlled multiple access MAC protocols with deterministic packet size and, hence – the least overheads, allow to reach to a fundamental limit of a MACs throughput capacity which, in turn, as much close to 1,0 as it ’ s wished. The fully distributed ATM- like multifunctional MAC technology (MFMAC) [ 8 , 12 ] meets the above breakthrough quali fi cations. Extremely Flexible, Energy, and Spectral Ef fective Green PHY-MAC 9 Author Proof The disr uptive MFMA C technology uses the recurrent M-sequences (RS) MA C addressing opportunities [ 8 , 14 ] in order to organize a RS-token tools “ all-in-one ” for high e f fecti ve multiple access to long-delay space medium, soft QoS provision and distributed dynamical control of traf fi c parameters and bandwidth resources [ 8 , 12 , 14 ] approaching the subli mit of throughput capacity. The M -subs equences A j ¼ a j ð n  1 Þ ; a j ð n  2 Þ ; ... ; a j serve as RS-identi fi ers of the unique MAC addresses and other protocol subjects. Some subset of i th “ personal ” identi fi ers f A i jkt k ¼ 1 ; 2 j ; ... ; m it g¼ B it are dynamically assigned to each i th station on a decent ralized basis by Shannon-Fano method for passing of the user ’ s request in proportion to the required bandwidth resource ½ Y it  . 4 Concept of Ubiquitous IoT/M2/H2H Green RRD 5G System The RRDs extremely green device-centric Hypercelle is explained in Fig. 4 . A con- ceptual look of the IP over DVB-2S multifunctional satellite-based fully distributed hybrid 5G networking techno logy RCS-MFMAC for RRD areas is explained in Fig. 5 . The hybrid archi tecture relies on implem entation of the QoS-guaranteed multi- functional 5G machine type MAC perfect rural PHY-MAC techniques basing on the developing of the advanced delay-tolerant 5G ATM-like MPMP MFMAC techno logies [ 8 , 12 ] which in turn should be adapted to conditions of the satellite platforms ’ DVB-2S-RCS [ 10 ], VSAT, etc. The main breakthrough drivers for RRD-oriented 5G communications include also a push MFMA C-based next generations of wireless asynchronous trans fer mode (ATM/MFMAC), of multi-protocol label switching (MPLS/MFMAC), and also of IP over DVD-S/MFMAC integrate d networki ng tech- nologies [ 9 ]. Fig. 3. MACs state entropy, or overhead in fi mum (a), and MACs throughput supreme (b) versus packets duration laws, SER = 1.0E-3. 10 A. Markhasin Author Proof 5 Conclusion In this paper, the green, ecological and cost-ef fective advanced approach to creation of the fl exible QoS-guaranteed ubiquitous 5G IoT/M2M/H2H multifunctional RRD communications has been designed. Of fered approach rely on implementation of the extremely fl exible, energy and spectral ef fecti ve 5G PHY-MAC techniques: (i) smarter increase of the SINR through beamforming/antenna/ orthogonality gain, without rise of the transmitter power; (ii) closing “ on-th e- fl y ” the fundamental minimum of po wer consumption ICPE; (iii) providing “ on-th e- fl y ” the pro fi tability/po wer ef fi ciency aimed fundamental trade-of fs for rural green 5G networks in practical invariant variables notions. It should be noted the key mission critical opportunities of a perfect rural 5G MAC: (j) the reachable low overhea d close to fundamental in fi mum; (jj) the fl exible 5G scheduler adapt “ on-the- fl y ” the superframe formats and optimally allocate the massive Fig. 4. Rural extremely green 5G Hypercelle. Fig. 5. Ubiquitous Green Rural 5G Hybrid Architecture. Extremely Flexible, Energy, and Spectral Ef fective Green PHY-MAC 11 Author Proof machine type and also multiservice traf fi c by equal ATM- like minimal bandwidth block per second, wi thout superframe over fl ow or redunda ncy. References 1. Cicconetti, C., de la Oliva, A., Chieng, D., Z úñ iga, J.C.: Extremely dense wireless networks. IEEE Commun. Mag. 53 (1), 88 – 89 (2015) 2. Boccardi, F., Heath Jr., R.W., Lozano, A., Marzetta, T.L., Popovski, P.: Five Disruptive Technology Directions for 5G. IEEE Com. Mag. 52 (2), 74 – 80 (2014) 3. Chen, Y., Zhang, S., Xu, S., Li, G.Y.: Fundamental trade-of fs on green wireless networks. 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