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c (4) Set PC = Pk,n ; (4a) If n > 0, set PT = PT n (4b) Set ck,n = ck,n 1, ck,n = ck,n + 1 GOTO Step (1a) c (5) If {PC = mink,n,c (Pk,n k,n )}, nish.

v)(n + v - p + 1)]

(10.4.17)

-(m!~ m2) )

(10.4.18)

are the Wigner 3j symbols [Edmonds, 1957]. We note the following: (1) The m index consists of m = 0, I, 2, ... , n and tL index consists of tL = 0, I, 2, ... , v. (2) AJ.Lvmn, BJ.Lvmn may not be of the same dimension as M mn and N mn. For example, we may truncate M mn and N mn at a multipole order of n = N M . However, for AJ.Lvmn and BJ.Lvmn, the summations of (10.4.8)(10.4.11), we may need to sum over v = 1,2, ... , to beyond N M to have sufficient accuracy. This means AJ.Lvmn and BJ.Lvmn can be non-square matrices. (3) For the Wigner 3j symbols in (10.4.18), m1=0, I, m2=0, I, Also , j1 , j2

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The vertical swapping algorithm (VSA) does vertical swapping for every pair of users. In each iteration, users try to swap their subcarriers such that the power allocation is reduced. There are different types of vertical swapping. For instance, in triple swapping, user i gives its subcarrier to user j and in the same way user j to user k and user k to user i. In Koutsopoulos ad Tassiulas [55], pairwise swapping is modi ed to cope with the adaptive modulation case. In this case, there is more than one class where each class is de ned with its modulation (i.e number of bits loaded to a subcarrier) and swapping is only within the class. Each pair of user swap their subcarriers that belong to the same class if there is a power reduction. In this way, adjustment of subcarrier is done across users, to try to approximate the optimal solution. VSA is described as follows. VS algorithm (1) pair of user {i, j}; c c (1a) Find Pi, j (n) = Pi,n P j,n and (1b) Find (1c) Set (1d) Add (2) Select (3) If (4) If

(10.4.19)

The symmetry relations for Wigner 3j symbols are, for even permutations, m2 (IO.4.20a)

h ) = (

With this file in your current working directory, you would simply run the QuickCert command:

(4) In view of (10.4.20a) and (1O.4.20b),

(10.4.20b)

Pi, j = max Pi, j (n), n Si ; = max P j,i (n), n S j ;

-(mP+fL))

(~ ~ ~)

(10.4.21a)

In -

(1O.4.21b)

c c P j, i(n) = P j,n Pi,n n P j,i n, n Pi, j = n Pi, j + n P j,i ; n, n Pi, j to the { } list;

Equations (1O.4.21a) and (10.4.21b) can be applied to the summations in (10.4.19) and (10.4.20), respectively. Next we apply the translation theorem to (10.4.6). Note that (10.4.22) and (10.4.23) Also r = rrl +rl. We have on using translation addition theorem in (10.4.6),

L [w~~)(l)RgMmn(krrl) +w~(l)RgNmn(krrl)] = mn LL{ a~~) [RgAmn/w(krl)RgMmn(krrl) +RgBmn/w(krl)RgNmn(krrl)]

This generates the following files:

a~~) [RgBmn/w(krl)RgMmn(krrl) + RgAmn/Lv(kr1)RgNmn(krr1)]}

L L {w1J;;)(j)TS M )(j) [Amn/_w(krZrj )RgMmn(krrz)

+ Bmn/w(krzrj)RgNmn(krrz)] + w1~)(j)TSN)(j)

= max(i,n),( j, n ) ; GOTO STEP (1a);

. [Bmnl-w(krzrj)RgMmn(krrz)

+ Amn/w(krzrj)RgNmn(krrz)]}

(10.4.24)

(M)(Z) = "'" [R 9A mnl-w (k-) al-w w mn 0 rz (M)

21.4.2 Resource allocation to maximize capacity Suppose there is no xed requirements per symbol and the aim is to maximize capacity. It has been shown in Viswanath et al. [60] that, for point-to-point links, a fair allocation strategy maximizes total capacity and the throughput of each user in the long run, when

+ 00 "'" "'"

w~J(Z)

CA/ cacertpem crl/ newcerts/ cert_1pem cert_2pem private/ cakeypairpem serial hello-client/ cert_hello-clientpem csr_hello-clientpem hello-client_keypairpem hello-server/ cert_hello-serverpem csr_hello-serverpem hello-server_keypairpem

(1O.4.25a)

L [RgBmn/-Lv(krz)a1J;;) + RgAmn/-Lv(krz)a1~)]

(1O.4.25b)

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